Wildfires rarely begin as large-scale disasters. They start as subtle shifts—drier vegetation, rising temperatures, changing wind patterns—signals that, if understood early enough, can change outcomes entirely. But increasingly, the systems designed to monitor and interpret those signals are under strain. Research stations are closing. Data pipelines are thinning. And in many cases, the people responsible for managing risk are left operating with incomplete visibility.

That’s the gap Rhizome is stepping into.

Rhizome works with utilities and grid operators—organizations that sit directly in the path of wildfire exposure. Their platform translates environmental and infrastructure data into clear, operational insight: where risk is forming, how it’s evolving, and what actions can be taken before a spark becomes something far more costly.

From the outside, it can look like a data problem. In reality, it’s a decision-making problem. When risk isn’t well understood, responses tend to be blunt—broad power shutoffs, reactive measures, and trade-offs that carry real consequences for communities. What Rhizome enables is something more precise. A way to act with context, not just caution.

When we first spent time with the team, what stood out wasn’t just the technical approach, but how grounded it was in the realities of the people using it. Utilities don’t need more dashboards—they need clarity in moments that matter. That focus on usability, on translating complexity into something actionable, felt both pragmatic and necessary.

It’s also where Mishal Thadani brings a clear point of view. He’s spoken about the growing concern around the loss of wildfire research infrastructure, particularly in high-risk regions like California and Oregon. The implication is straightforward: as foundational systems weaken, the burden shifts to new layers of intelligence to fill that gap. Not as a replacement, but as an adaptation to a changing reality.

That perspective shaped how Rhizome is being built. Not as a static model of risk, but as a living system—one that continuously ingests environmental signals and reflects how conditions are changing in real time. It’s less about predicting a single outcome, and more about helping operators stay aligned with a dynamic environment.

From an investment standpoint, this is the kind of work that tends to matter more over time. It sits at the intersection of climate, infrastructure, and decision-making—areas where the cost of inaction is rising, and where better tools can meaningfully shift outcomes.

What makes it compelling isn’t just the scale of the problem, but the specificity of the solution. Rhizome isn’t trying to solve everything. It’s focused on a critical layer—helping the systems we rely on every day become more aware, more responsive, and ultimately more resilient.

Looking ahead, it’s hard to imagine a future where infrastructure operates without this kind of intelligence embedded into it. As risks become more complex and less predictable, the ability to see clearly—and act early—becomes foundational.

Rhizome is building toward that future, one decision at a time.

Read the full article on Fast Company

Some of the most meaningful shifts in technology don’t arrive all at once. They show up in workflows—quietly changing how things get done until the old way no longer fits.

That’s what’s happening with AI-generated code.

Developers today are increasingly guiding systems that can write, test, and deploy code on their own. It’s a leap in speed and capability, but it also introduces a new kind of risk—one that’s harder to see. When code is created autonomously, understanding how it was generated, what it accessed, and where vulnerabilities may exist becomes far less straightforward.

This is where Operant AI is focused.

With its Endpoint Protector, the company is addressing the rise of “shadow AI” and autonomous coding agents operating beyond traditional oversight. Instead of relying on static defenses, Operant AI focuses on runtime behavior—observing how AI systems interact with code, data, and infrastructure in real time.

What stood out to us early was the clarity of that approach. As AI changes how software is built, security needs to evolve alongside it—not as a constraint, but as an embedded layer of understanding.

That perspective is shaped in part by Vrajesh Bhavsar, who has consistently pointed to the growing gap between how quickly AI is being adopted and how slowly traditional security models are adapting. It’s not a future problem—it’s already here.

From our lens, this is where new categories begin to form. When foundational workflows shift, the infrastructure around them has to be rebuilt. And the companies that matter most tend to be the ones that recognize that early.

Operant AI is building in that direction—toward a world where AI-driven development is not only faster, but also more visible, accountable, and secure.

Read the full article on CXOtoday.com

Mallaby opened with a question that’s been haunting the best minds in technology: what does it actually take to build something that changes everything? His book traces Demis Hassabis and DeepMind’s decades-long quest toward superintelligence. It’s a story about conviction held long before the world caught up and it felt like exactly the right place to start for the moment we’re all living through. Hassabis has famously said, “First you solve AI. Then you solve everything else.”

The story of DeepMind, and of AI, is the backdrop of today’s entrepreneurial world. At Everywhere Ventures we’re not focused on these obvious trends, but where the tailwinds are taking us. We’re looking at the second, and third-order effects, and where founders are expanding on this new premise. As such, it couldn’t have been more fitting to have Mallaby set the stage for our AGM.

Our Story

Jenny and Scott founded Everywhere Ventures eight years ago with a simple belief: the best founders don’t always come from the places most funds are looking. Instead they’re everywhere, building in places that feel early, uncomfortable, and not yet obvious to everyone else. Today, we’ve invested into hundreds of companies and have built a thriving community of founders. Trends evolve, and tailwinds shift, but what remains the same are founders building at the edge, innovating and pushing us forward in new ways. The premise of Everywhere is that it’s our community that keeps us on this frontier, even as the tides shift, and the world changes. The best founders perennially move to the edge of the technology map, and we trust in their stewardship to lead us toward the non-consensus frontiers the world hasn’t fully adopted.

How We Got Here

Venture capital is a high-dispersion asset class. The difference between a top-quartile manager and a median one isn’t incremental, it’s enormous. This means differentiation isn’t a nice-to-have; it’s the whole game. Our job is to find non-consensus ideas where price still lags inherent value.

Today, we see three second-order effects creating mis-priced, non-consensus opportunities.

The first is fintech infrastructure. The fintech boom of the past decade created a wave of consumer-facing products, and underneath them, a tangle of legacy plumbing that was never built for what it’s being asked to do. The obvious bet is on the apps. Our bet is two layers down: KYC and identity management, fraud and risk tooling, data layers, stablecoin rails. That’s where the durable margin is, and that’s where we’ve backed Complyance, founded by Richa Kaul. Complyance automates regulatory compliance for financial institutions, replacing manual, error-prone processes with an AI-powered platform built for the pace of modern regulation. That’s the infrastructure financial institutions actually need for the world they’re operating in now.

The second is AI infrastructure. Everyone is betting on the large models. We’re betting on what the models can’t run without. Security, energy, orchestration, the unsexy, load-bearing infrastructure that makes AI deployable at scale. Operant.ai, founded by Vrajesh Bhavsar, Ashley Roof, and Priyanka Tembey, sits squarely in this thesis. Operant provides runtime security and observability for AI systems, giving enterprises the visibility and control they need to deploy AI safely in production. When enterprises ask how they actually run AI reliably at scale, Operant is part of the answer.

The third is AI-native companies, but not just any AI wrapper. The ones that win will do three things: generate net new data that didn’t exist before, take action rather than just surfacing insight, and amplify humans rather than replace them. Those companies become genuinely impossible to displace. Keebler Health, founded by Isaac Park and Andrew Stickney, is a company we believe fits that profile. Keebler Health uses AI to streamline the prior authorization process, cutting the administrative burden that slows down patient care and burns out clinical teams. That’s AI building in a space where it can meaningfully change outcomes, not just automate busywork.

The One That Made Us Look Twice: Pair Eyewear

Speaking of non-consensus…we’re a fund focused primarily on b2b software opportunities, and yet we wrote a pre-seed check into a consumer eyewear company with co-ceos still in university. But when we met Nathan Kondamuri and Sophia Edelstein, we knew they were special, with a vision for launching an entirely new category of eyewear: weekly product drops, a subscription membership, on-demand manufacturing, and a lens lab with 90+ patents. They built an incredible brand with the average customer owning more than eight top frames. They’re now in more than 1200 retail stores and gaining strong traction. Sometimes the best bet is the one nobody expected you to make.

Hot takes, Macro trends

We closed the AGM with new General Partner Anna Barber and Fortune’s Allie Garfinkle in a wide-ranging conversation about the new world of venture. One that’s headed away from bloated firms, consensus trades, and old assumptions about how companies scale, and back toward something smaller and more human. Drawing on both venture history and today’s market, Allie argued that the firms built for true venture-scale returns will increasingly separate from the asset managers simply deploying ever-larger pools of capital. The middle is getting squeezed, high AI valuations are masking fragile companies, and secondaries may do more than the long-awaited IPO window to reshape liquidity. Her core point was that venture still matters because it remains one of the few financial structures designed to back ambitious people with unproven ideas. We agree. We think the future belongs to small, focused firms staying close to founders and true to the craft of early-stage investing.

Looking ahead

We left the AGM feeling what we always feel after spending time with this community: optimism and momentum. The future of venture capital belongs to firms that are genuinely differentiated: in their sourcing, their diligence, their networks, and their conviction. Not funds that follow the consensus, but firms that form their own view early and hold it. We’re glad you’re part of it.

Looking to explore more insights from our team? Dive into Jenny’s book, and follow Scott and Anna on Substack.

E-prescribing was meant to modernize how prescriptions move through the healthcare system. In practice, it often digitized the same fragmentation. Scripts are sent, but patients are left to navigate pricing, availability, and fulfillment on their own.

Photon is taking a different approach. Rather than treating prescribing as a handoff, the company is rebuilding it as an end-to-end experience that connects providers, pharmacies, and patients in a single flow.

At the center of this shift is Otto Sipe, who is focused on making prescriptions more transparent and actionable. The goal is not just to send a prescription electronically, but to give patients clarity and control at the moment decisions are made.

Photon’s platform allows providers to guide patients through key steps during the visit itself. Pricing options, pharmacy selection, and fulfillment paths are surfaced upfront, reducing the uncertainty that typically follows a prescription. Instead of a fragmented process, it becomes a coordinated one.

This reframing addresses a deeper issue. E-prescribing has long been optimized for transmission, not experience. By shifting the focus to outcomes and usability, Photon is redefining what that infrastructure layer can do.

The approach also aligns with broader expectations in healthcare. Patients increasingly expect visibility into cost and choice, while providers are looking for tools that reduce friction rather than add to it. Bridging that gap requires systems that work across stakeholders, not in silos.

Photon’s model suggests that the next phase of healthcare infrastructure will be less about digitization alone and more about integration. Connecting the full lifecycle of a prescription, from decision to fulfillment, creates a more reliable and patient-centered experience.

As platforms like Photon gain traction, the definition of e-prescribing itself begins to shift. What was once a simple electronic transfer is becoming a coordinated system that supports both clinical decisions and patient outcomes.

Read the full announcement on Hospitalogy

Homebuilding is a major pillar of the U.S. economy and is one of the largest markets still running on outdated infrastructure. The top 500 U.S. builders sell roughly $250–500 billion of new homes each year, which is about half the size of U.S. e-commerce. Yet most of the buyer experience still happens through phone calls, paper forms, and scattered legacy systems. Foundation is bringing buyers and teams online with the native customer experience suite for enterprise‑scale homebuilders. They provide white‑label mobile and web apps that give buyers a modern, branded journey, while sales and operations teams get powerful tools and workflows that increase speed and efficiency. They support single‑family, townhome, and multifamily builders, and part of their job has been to underwrite their decisions by proving the product works across all these builder types. The ultimate goal is to help builders sell more homes, make more profit, and give buyers a better experience from start to finish.

Co-founder and CEO Luke Groesbeck considers building Foundation a full-circle story. His co-founder and CCO Derek Schairer previously sold homes for Lennar, one of the leading homebuilders in the world, and Luke interned at Lennar in college before moving into tech. Luke and Derek met later at Opendoor, where Luke led product for field tools before moving to partnerships to help scale the company’s fastest-growing customer acquisition channels and Derek was the GM of homebuilder partnerships. Working closely together, they saw firsthand how large-scale homebuilding and transactions actually operate in the field, from construction workflows to customer experience. That shared context shaped their decision to start Foundation, where they now combine their backgrounds to build consumer-grade buyer experiences, operational tools for builder teams, and an API platform for integrations and automation.

Why Foundation and why now?

At Opendoor, we worked on the homebuilder partnerships channel, which turned out to be one of the company’s most efficient and scalable customer acquisition channels. As we worked with homebuilders, we kept hearing the same request: they wanted better technology to run their sales process and improve the buyer experience. Most builders were still relying on outdated, offline systems despite selling hundreds of billions of dollars of homes each year. That’s when we realized there was a massive opportunity to bring modern software to one of the largest industries that had been left behind.

What’s Foundation’s mission?

Our mission is to build Silicon Valley–grade technology that helps homebuilders sell more homes, more profitably, and deliver a better experience for buyers.

Tell us about some recent milestones that Foundation crushed.

• In 2025 we grew 5x.

• By the end of 2025, our builders collectively sold more than 10,000 homes a year through Foundation. That’s the equivalent scale of a top‑10 public U.S. homebuilder.

• We launched our first builder‑branded mobile apps less than 18 months ago, and in that time we’ve grown to power more than 40% of the homebuyer and homeowner apps offered by top‑200 builders.

How does Foundation inspire ”customer love”?

Foundation turns a fragmented and stressful homebuying process into a simple, modern experience. Buyers can track construction progress, manage checklists, and communicate with their builder in one place during the 6 to 12 months their home is being built. For builders, that means happier customers, fewer manual touchpoints, and teams that can focus on building and selling homes instead of constantly managing updates.

Why is Foundation going to win?

You have to have an ROI‑driven product, but beyond that, winning comes down to two things: who moves the fastest, and who’s closest to their customers. We’ve built Foundation around that intersection. We ship quickly and iterate constantly based on real feedback from builders. Most of our relationships are built on the ground and that proximity gives us a deep understanding of their problems. I believe that combination of speed and closeness is what will ultimately make us hard to beat.

Any favorite podcasts?

The only podcast I consistently listen to is Odd Lots, a Bloomberg show that’s generally business‑oriented but features fascinating guests across many industries. I like hearing from people who are deep experts in their own strange corners of the economy.

Fun fact:
I have two daughters under six and we’ve become the typical Boulder family: spending our time outdoors hiking, rock climbing, snowboarding, and skiing.

Listen to Alfie Pearce-Higgins with Jenny Fielding, on the Venture Everywhere podcast: Not My First Rodeo. Now on Apple & Spotify. Check out to all our past episodes here!

Healthcare is increasingly moving toward convenience, privacy, and accessibility. &you is part of that shift, offering a model that brings consultations, treatments, and ongoing care into a more seamless digital experience.

In a recent Tatler Asia feature, Emil Eriksen, founder and CEO of &you, shared how the company is addressing gaps in how people access healthcare. Many patients still face barriers such as stigma, limited availability of specialists, or the inconvenience of traditional clinical visits. These challenges are particularly visible in areas like sexual health, dermatology, and wellness, where discretion and ease of access matter.

&you’s approach is to remove those barriers by combining telehealth consultations with end-to-end treatment and delivery. Patients can consult with licensed doctors online, receive prescriptions when appropriate, and have treatments delivered directly to their homes. The experience is designed to feel simple, private, and continuous rather than fragmented.

Eriksen’s perspective is rooted in the idea that healthcare should fit into people’s lives, not the other way around. By focusing on accessibility and user experience, the platform is helping normalize conversations around conditions that are often under-addressed in traditional systems.

The company’s growth reflects a broader shift in consumer expectations. Patients are increasingly seeking healthcare that is not only clinically effective but also convenient and discreet. Digital platforms are becoming an important layer in meeting those expectations, particularly in regions where access to care can be uneven.

&you is positioning itself within that evolution by building a model that integrates consultation, treatment, and follow-up into a single experience. This reduces friction for patients while improving continuity of care.

As digital healthcare continues to expand, platforms that prioritize both access and experience are likely to play a larger role in shaping how care is delivered. Under Eriksen’s leadership, &you is building toward a future where healthcare is more approachable, responsive, and aligned with how people live.

Read the full article on Tatler Asia

Tinned fish is having an unexpected resurgence. What was once considered a pantry staple is now being reintroduced as a premium, design-forward product with growing cultural relevance. Fishwife is at the center of that shift.

In a recent Chowhound feature, the brand received a notable nod from Alton Brown, who highlighted Fishwife as a standout in the category. The recognition reflects a broader movement, where consumers are rediscovering tinned seafood not just for convenience, but for quality, sourcing, and experience.

Built alongside co-founder Becca Millstein, Fishwife has approached the category differently from the start. Rather than competing on price or shelf space alone, the company has focused on elevating both the product and the brand. From packaging to storytelling, Fishwife positions tinned fish as something to be enjoyed and shared, not just stored.

This approach aligns with changing consumer behavior. As food culture continues to evolve, there is growing interest in products that combine quality, sustainability, and aesthetic appeal. Tinned fish, once overlooked, is benefiting from that shift.

The mention from Alton Brown underscores how far the category has come. Influential voices in food are helping reframe perceptions, introducing tinned seafood to a new audience that values both taste and presentation.

For Fishwife, the opportunity goes beyond a single product category. By redefining how consumers engage with tinned fish, the company is contributing to a broader reimagination of pantry staples.

As demand continues to grow, brands that combine strong product quality with thoughtful positioning are likely to shape the next phase of the category. Fishwife’s rise reflects how even the most traditional products can find new life when approached with a fresh perspective.

Read the full article on Chowhound

In episode 116 of Venture Everywhere, Jenny Fielding, co-founder and general partner at Everywhere Ventures, talks with Alfie Pearce-Higgins, co-founder and CEO of Rodeo — an AI-powered careers platform helping people understand the job market, build personalized career plans, and find the right opportunities. Alfie shares how watching startups outperform years of institutional work in developing countries convinced him that the right people, tools, and capital could change everything — a conviction that led him back to the UK to fix one of the most broken markets he’d seen: the job search. He explains how the collapse of the traditional job application market, driven by zero-click application on one side and AI screening tools on the other, created a Akerlof-style market failure that Rodeo is purpose-built to solve.

In this episode, you will hear:

• How synthetic applicants and fake job posts are breaking the job application market.

• Rodeo’s voice-first onboarding approach to building rich, personalized career profiles.

• Combining AI efficiency with human advisors for the most powerful careers solution.

• How AI is making parental and school career advice dangerously out of date.

If you liked this episode, please give us a rating wherever you found us. To learn more about our work, visit Everywhere.vc and subscribe to our Founders Everywhere Substack. You can also follow us on YouTube, LinkedIn and Twitter for regular updates and news.

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Transcript:

00:00:04 VO: Everywhere Podcast Network.

00:00:14 Jenny Fielding: Hi, and welcome to the Everywhere Podcast. We’re a global community of founders and operators who’ve come together to support the next generation of builders. So the premise of the podcast is just that, founders interviewing other founders about the trials and tribulations of building a company. Hope you enjoy the episode.

00:00:32 Jenny: Hi, everyone. Welcome to Venture Everywhere. This week, we’re very excited to talk to Alfie Pearce-Higgins, who’s the co-founder and CEO of a London-based company called Rodeo, which you’re going to hear all about.

00:00:44 Jenny: Because it’s a startup building the tools that help job applicants plan their careers. This couldn’t be the most opportune moment to talk about this. So I’m really excited. Because everything that’s going on in the world of AI, when it comes to job opportunities and preparing professionals, it’s a very important time. Welcome to the show.

00:01:03 Alfie: Hi. Thank you very much. It’s great to be here.

00:01:06 Jenny: Awesome. I’d love to start a little bit at the beginning because you, like me, started in a very different place. I worked at J.P. Morgan, seems like you worked at Barclays. So I’d love to hear a little bit of the journey of going from finance and big company to starting your own startup.

00:01:23 Alfie: I’ve definitely had, what you’d call a nonlinear career, which is an interesting start for someone trying to build advice tools for other people. I studied economics and maths, and the natural place to go was going into the city and do some finance.

00:01:35 Alfie: I did a bit of M&A and then ended up trading credit default swaps back in the post-financial crisis days, which was quite fun. I think I’d do the same again.

00:01:55 Alfie: I always recommend to young people, big companies are great places to get training, to understand the world of work and to get that platform. But it didn’t take me that long to realize it wasn’t something I wanted to do for 30, 40 years.

00:01:53 Alfie: So I then left and went into international development and spent the next five years in Nigeria and then Nepal implementing economic reform projects. Trying to help privatize Nigerian electricity companies, trying to support investment into agriculture and tourism in Nepal after the earthquakes there.

00:02:11 Alfie: I enjoyed it, but I didn’t realize that… there were frustrations working for big donors. I love the work environment, but not necessarily the structure of the industry.

00:02:21 Jenny: Were you living in these places or you were just traveling?

00:02:24 Alfie: I was in Nigeria for two and a half years and then Nepal for about the same. And then lots of travel to various other parts of sub-Saharan Africa along the way.

00:02:31 Alfie: And I really enjoyed the environment. So I then very fortuitously got an opportunity to join SafeBoda, which was an early stage company in East Africa doing motorized taxis.

00:02:41 Alfie: Uber on two wheels is the easiest way for the European or American audience to understand it. And that was amazing. We were training drivers, we were giving them helmets, generally for the first time. And then we were helping to improve driving standards.

00:02:53 Jenny: And so interesting because you were working on the other side of that, which I imagine was slow and institutional. And then all of a sudden you’re like on the ground with the drivers. You’re actually seeing things happen from a consumer point of view every day, I imagine.

00:03:07 Alfie: There’s a marked contrast between what startups can achieve in developing countries versus some of the very slow institutional top-down structures. We’re all amazed and impressed by what startups can do in the UK or the US.

00:03:19 Alfie: That’s nothing in terms of the power that can be achieved by the right people with the right tools and a bit of capital in developing countries. Be that in healthcare, be that in education or consumer services.

00:03:28 Alfie: I was blown away by how powerful that can be. I certainly think that I achieved more with SafeBoda in three years than any of the development projects that I’d seen.

00:03:37 Jenny: Incredible. Incredible. So then what gives you the confidence or idea to start your own company?

00:03:42 Alfie: Well, lots of things that turned out not to be true. And we’ve come a long journey since then. So, the thesis with which one starts a company is often not the same thesis that one ends up building around.

00:03:52 Alfie: We started building tools for gig economy workers in the UK. Interesting. I saw how in developing countries, the economy can be very powerful because, in fact, you’re taking even more informal labor and adding more structure to it. Whereas in developed countries, it’s often perceived as taking structured jobs and removing security and making them less secure and more flexible.

00:04:11 Alfie: So I was amazed coming back to the UK by some of the challenges in the gig economy in the UK. I teamed up with an old friend who is ex-delivery. We started building tools for gig workers in the UK to understand and optimize their earnings.

00:04:24 Alfie: We had some success with that. We built a tool that took a lot of traction. There were real challenges around the data. To cut a long story short, the platforms didn’t see data the same way we did and were very aggressive about us helping drivers to understand their data.

00:04:38 Alfie: I think similar stories have played out in the US. It’s a longer story there. But we’ve then adapted that. But what we’ve stayed true on is that our aim is always to build tools that help workers navigate the world of work.

00:04:50 Alfie: What that’s evolved into is AI-powered careers advice to help people understand what the job market looks like, understand what their strengths are, how they can best fit into the job market and build a career plan.

00:005:01 Alfie: And then take it from there into finding live opportunities for training, for learning, for earning, for accommodation of all of that, And helping them secure those opportunities.

00:05:10 Alfie: Any of us who have had any engagement with the job market in the last couple of years will realize it’s changing extremely fast. What jobs are out there is changing. What skills are needed for them, what the jobs are called, how to apply for them.

00:05:21 Alfie: There is a speed of transition going on in the labor market that I think is unprecedented. And unfortunately, the people who are bearing the brunt of this are younger people entering the workforce for the first time. That’s very much part of our mission is to help younger people understand and enter the world of work.

00:05:37 Jenny: I would imagine also mid-career people that are getting caught in the transformation that’s happening. They grew up under one paradigm. And now, the way you get a job, the way that you approach a job search probably changed from when they enter the workforce. So I imagine that’s a big opportunity as well.

00:05:56 Alfie: Absolutely. I think looking for a job, planning a career, these have gone from occasional things that we will do to an ongoing, evolving question.

00:06:04 Alfie: We haven’t seen entire job categories destroyed or removed in the way some people have predicted. So I don’t think there are a whole bunch of mid-career people who suddenly wake up one morning and find that industry is no longer there.

00:06:14 Alfie: That may happen. Who knows? So I think a lot of people are seeing their jobs evolve. And the smart ones are realizing that if they want to progress or if they want to take their career forward, they’re going to adapt what their skill set is or how they’re going about it or where they’re specializing.

00:06:28 Alfie: This spans across the whole of careers, but I think it’s felt most acutely at the early stage of phase.

00:06:34 Jenny: So can you just talk more specifically what was broken about traditional job boards that you guys sought to transform and rodeo? As investors, we’ve seen so many iterations of this over the years. And so I’d love to kind of get your perspective on what you were really focused on.

00:06:52 Alfie: There are two things we should reference. One is job boards and the other is careers advice. Job boards are definitely broken. The model of a job board has always been someone turns up, searches for something, whether that used to be in the back of a newspaper or on a website or an app or with an agent. And then they try and identify the right roles.

00:07:10 Alfie: It’s broken a number of different ways. Job boards are typically optimized for volume. And that’s been same the metric. If you put up a job, you want to get enough applicants. And then you kind of assume that there are enough applicants, somewhere in there will be the right applicant. And we’ve seen that.

00:07:24 Alfie: The first job I applied for was, I think, in a supermarket stacking shelves. And at that point, it was a form. I had to stop in at the supermarket, pick up a form, fill it in and take it back in order to be able to spend my Saturdays stacking shelves.

00:07:36 Jenny: I did that as a waitress. I walked in and I was like, “Hey, are you guys hiring?” And they’re like, “Yeah.” And then they went behind the counter and they handed me a form. I mean, this was a long time ago, but that was wild.

00:07:46 Alfie: Exactly the same. And then the… next would be banking internships. And that was online. But I remember each of them taking about half a day because I had to write a creative essay about why J.P. Morgan was so close to my heart. You had to write out these answers and it took a while.

00:08:01 Alfie: And then you fast forward a bit and then you got one click, apply. Then you got your LinkedIn one click apply. Indeed did something similar. We’re now in a world where there’s zero click apply. You don’t even need to apply now. You can have an agent apply for all these jobs in your sleep.

00:08:13 Alfie: You can apply for a thousand jobs by next week without lifting a finger. Now, the reality is that in some ways, a rational approach on the applicant side, it’s a numbers game.

00:08:21 Alfie: What we’ve seen then on the business side is that they’ve deployed a whole bunch of AI screening tools because no one can conceivably sort through a thousand CVS between now and next week.

00:08:31 Alfie: It’s a really interesting case of market failure that both sides of the job application market have behaved rationally in adopting AI. And the combined result has been a complete breakdown of the actual mechanism.

00:08:42 Alfie: I remember studying Akerlof’s lemons and the second hand car markets and how asymmetric information causes market collapse in that sense. There’s lots of parallels with what’s happened on the job market.

00:08:53 Alfie: If someone applies, you’ve got no idea what they’re serious. You maybe don’t even know they’re a real person. And as an applicant, you don’t know whether it’s worth putting effort into applying for this job because you don’t know whether your CV is going to be read by a human being, how serious they are on their side.

00:09:08 Alfie: So I think there’s been a definite breakdown there. And ironically, to your point, we might be going back to a world where you stop in the cafe and ask for a job. I’ve heard people talking about going back to handwritten applications, because if someone sends you a handwritten application, you know that they’re real, they’re serious.

00:09:22 Alfie: We’ve seen a lot of job fairs because it’s much easier to do that early stage of applications if someone’s in front of you. That’s kind of on the job market side.

00:09:30 Jenny: It’s like I hadn’t really thought about that, but everyone’s creating synthetic users. So I imagine there’s synthetic applicants that these people have to deal with all over the place.

00:09:39 Alfie: Absolutely. And synthetic jobs. There’s a lot of fake jobs that are either swiping data or just collecting CVs. It’s a real mess. That’s connected to what we’re doing. We haven’t set up just to try and solve that problem. And there are bits that we can’t solve.

00:09:52 Alfie: In the other side is the careers advice. I don’t know who gave you careers advice, but this has always been a slightly messy market for how people get that advice. Parents still rank highest as a source of careers advice.

00:10:03 Alfie: That’s a challenge because… it’s always been out of date. What your teacher or your parents say to you is probably always got like a 20-year time lag. That’s always been an issue.

00:10:11 Alfie: Now it’s a serious issue because 10-year-old information about the job market is worse and useless when it comes to advising someone entering the job market today. So what the market people are advising on bears no resemblance to what their children are actually going to be entering into.

00:10:26 Alfie: People get careers advice from social media. That’s become a common source. It’s mostly about highly aspirational, get-rich-quick, not particularly reliable advice, but it can be quite useful in some cases.

00:10:36 Alfie: And then obviously people go to ChatGPT, off-the-shelf AI tools that we see in the data, are now cited as one of the most common sources for careers advice. And that can be really powerful.

00:10:46 Alfie: I’m sure that many of your listeners have probably experimented with giving Claude a copy of their CV. They are really powerful tools for brainstorming, for ingesting this information, but they come with quite big risks.

00:10:58 Alfie: One of the ones that we’ve seen mostly is sick fantasy. I’m sure that if I put my CV into ChatGPT, it’ll tell me that I should absolutely be a FTSE 100 CEO in five years and do I want him to make me a step-by-step route to getting there? Which is lovely to hear, but can be quite damaging.

00:11:14 Alfie: And those are not very good with structured data. Getting an AI tool to do a job search for you often will result in unreliable information and there’s no safeguarding, if you’re talking about young people who engage with this to make quite consequential decisions for their lives.

00:11:28 Alfie: So AI is already playing a big role in this. Our aim is to build the responsible tooling around that, which means being able to enable, to turn it into a properly useful tool for people to understand, build up a rich picture of who they are, what they need to do right now, what their current situation is, what their long-term ambitions are, how this could be mapped into their local job market – because a lot of this is contextual and local – and then turn it into an actual plan and help support them through putting that in place.

00:11:52 Jenny: I love the part about career advice. In my generation, the people that I asked were my friend’s parents. I was going to law school and my best friend’s father was a lawyer. My parents weren’t lawyers.

00:12:04 Jenny: And so I asked him. There we are in like, his Hampton’s house. He was like a partner at some big firm. I was like, Steve, what’s the advice you would give? Because like I think I was going into law school, so I was like 20.

00:12:14 Jenny: And he was like, well, Jenny, I think you should join a members club, a private club, and you’re going to get a lot of business there. And I was like… 20 years old. And I was a woman. I feel like a lot of those members clubs of that generation were these old guys and whatnot.

00:12:27 Jenny: I just like… remember looking at him and being like, “Wow, that seems a little out of touch.” But like that was literally the advice that I got.

00:12:35 Alfie: Absolutely. I’ve had so many experiences of going into a degree and then being like, how come this isn’t what I thought it was going to be? Because that’s what it was like 20 years ago while I was being told about that world. It’s always been a problem. But the speed of change of AI has just radically exacerbated that.

00:12:50 Jenny: So you mentioned this idea of agents. And just for anyone who’s not fully caught up, how do you see the agent on behalf of the person looking for a new career, looking for a new job?

00:13:02 Jenny: In the future, how do you see that actually playing out? I’m really interested. We obviously hear a lot of talk about it. There’ll be agents out there running around, looking for jobs. How do you actually see it benefiting individuals?

00:13:13 Alfie: In the first instance, it’s about helping people to understand themselves, the job market, the intersection of those two points and make a plan. In the longer term, there are a lot of open questions.

00:13:22 Alfie: It’s interesting to think about how human agents work in, say, the creative industries. If you’re an actor or musician, you will have an agent. Or maybe if you’re a writer.

00:13:30 Alfie: And that agent will know you quite well, go out into the market and source opportunities on your behalf and then bring them to you and say, Jenny, there’s a new film next year. Do you want to do four months’ work in Hawaii playing this? Here’s a script.

00:13:44 Alfie: So, you’ve got this idea of human agents in some sense. I think there’s a world in which we professionally have that type of structure. Whereby rather than us ourselves trawling through LinkedIn or Indeed or any of these job boards and trying to identify opportunities, we are represented by an agent who understands a great deal about us and we share information.

00:14:05 Alfie: We update that over and over and it iterates and it learns us better and better and then goes out and represents us. I think that’s particularly the case in areas of work which could become more freelance-dominated.

00:14:15 Alfie: One of the questions that we’re really interested in is what AI does to the employment versus self-employment balance. We’re already seeing some indications that that could be… there could be a bit of a tipping towards more self-employment because in some ways, AI makes it much easier to manage freelancers.

00:14:32 Alfie: In the UK, we’ve also got challenges around cost of employment going up and up, which has always been a sort of nudge towards the use of self-employed workers. So I think there… there are really open questions around what the medium to longer term structure of the labor market looks like.

00:14:47 Alfie: When people talk about labor market, they talk about both the market for work and the market for matching. On the matching side, I think, sourcing applicants is way more common than in the past now and there’s been a lot of tooling built around that.

00:14:59 Alfie: We don’t profess to have a clear view on what that’s going to look like in the longer term, but I think the idea of a personal creation that understands you and helps you frame your thoughts, understand your local job market, and identify the best opportunities for you to learn new skills, apply for work, and get the job and career that you want is very much in keeping with what people need right now.

00:15:21 Jenny: Let’s talk a little bit about that idea. You guys focus on personalization. You can’t train agents or think about getting great recommendations without it being personalized. So can you talk about some of the signals and architecture that you’re using to really understand the user and their context and really what they’re looking for?

00:15:39 Alfie: The personalization is all about understanding the user. And we’ve iterated a bit on how to do that. Most of us, if we’re asked a question, what do you want to do with your life and given a blank piece of paper, we struggle.

00:15:49 Alfie: And the reason why human beings are good at this stuff is because they’re good at encouraging us to open up. The prompts, the nudges, the encouragement to reveal more information and to share and to frame your thoughts.

00:16:00 Alfie: We found that voice calls are just by far the best way of getting the early information out of people and building the starting point of a profile. So our onboarding is quite heavily structured around voice calls. We still use CVs as well, because it’s useful to get that information early on for people. But voice calls are generally a very good way of understanding more about someone’s situation.

00:16:18 Alfie: And then after that, there’s always the opportunity to go back to that and add more context. But it’s also intuitive. A user will come to us, they’ll upload a CV if they have one. They’ll chat to their personal career agent in a voice call. They will then be presented with this starting point of a career plan.

00:16:35 Alfie: They will give feedback on things they like, things they don’t like. We’ll start sharing opportunities that we think might be a good match. They will give feedback on them and we’ll improve it over time.

00:16:45 Alfie: Their situation may change. They may suddenly decide they want to go in a different direction. And this can all be incorporated into it. And that’s what AI is really good at, is piecing together this information into where a human careers advisor often struggles. Because remembering what happened in the last meeting, keeping notes, updating it all when you’ve got 30 different people you’re speaking to today, it’s super tough.

00:17:05 Alfie: The personalization is a question of gathering early information in a way that makes the user comfortable and encourages them to open up and frame their thoughts, and then constantly improving and adding to that to build a rich picture of the person that you’re trying to help.

00:17:18 Jenny: Just out of curiosity, are candidates recording their calls and then feeding that information to their coaches? The best way to get feedback is to be on a call with someone. You can’t usually be on a call with someone who’s in an interview, but if that was recorded… Sometimes it’s recorded by the employer and shared, and sometimes you’re using your Granola or whatever. That could be interesting.

00:17:39 Alfie: At the moment, people are generally using us as an alternative to... They may be using a career service on the side. And then we’re hoping to work or we’re scoping out opportunities to work directly with career services.

00:17:49 Alfie: I can tell you more about where we see the hybrid approach. But no, we haven’t encountered people sort of recording one meeting and feeding that back in. But it’d be a great way of testing.

00:17:57 Jenny: Yeah! Again, everyone needs to opt in. But you know, everything is getting so transparent now. It’s like, everyone assumes in our meetings as VCs that that meeting is being recorded on both sides.

00:18:09 Jenny: And so oftentimes those meeting notes are just shared amongst the parties. And that a year ago, if you would have told people that that was happening, people would have freaked out and be like, no, I just want to have an intimate conversation. And now it’s just normal.

00:18:22 Alfie: Give it a year or two and AI-powered glasses will mean that every conversation you have in person is also recorded and filmed. Our goalposts definitely moved on that in terms of what people assume is recording.

00:18:33 Jenny: So do you think that the traditional CV and traditional way is just dying? Or this is a subset of people that are taking things to the next level? I mean, I notice when we’ve had job roles, people don’t even really offer to send a CV. They just like send their LinkedIn and maybe a little paragraph. And obviously, if you ask for it, they’ll do it. But I feel like it’s really changing.

00:18:54 Alfie: Yeah. It’ll vary a lot sector to sector. LinkedIn is great for some sectors. It doesn’t work for others. I think there’ll be more sector-specific tools for different areas of expertise.

00:19:05 Alfie: The truth is, I think, the CV is evolving. People are always lying on their CVs. They’ve always exaggerated stuff. I’m sure that’s happening in the US. But certainly, the UK has had its fair share of political scandals, where it turns out someone was quite liberal with the truth when it came to what their professional record says.

00:19:21 Alfie: So that’s nothing new. I think any good hiring process only ever seen a CV as a very small part of the bigger picture. Anyone who’s hired based purely on CVs is probably not going to get the results they wanted.

00:19:32 Alfie: The two major things that have changed is that it used to be that a well-written, tailored CV… a real sign of seriousness for an applicant. That’s no longer the case.

00:19:41 Alfie: The most beautiful CV that speaks directly to the job that you’ve advertised and looks lovely, and it could have been generated in two seconds passing. So that’s no longer a good signal of seriousness.

00:19:53 Alfie: And then the other side is that CVs have stopped being written for human beings. Applicants have had to adapt what they’re doing, because it may well be that these CVs are getting screened by some sort of AI feature, whether that’s in an ATS, whether that’s separately.

00:20:07 Jenny: Can you give us an example of that? What’s a tweak that a candidate would make to their CV because they realize a person isn’t looking at it?

00:20:15 Alfie: Reflecting back the exact language of the job description, which means it doesn’t always read that naturally. And I’m very skeptical about that. I think there are lots of people promising candidate screening tools. The risk with AI that we mistake precision and accuracy. You can put 100 CVs into your AI screening tool, and it will tell you that I’ve scored 64.2%.

00:20:34 Alfie: Now, that sounds really precise. Could just be very randomized. Put the same information again and see how much variance there is in results. And it may well be that you rank 10 candidates using your whatever AI screening tool you’ve been pitched by some company. And they come up with different ranks. That’s a pretty big drawback.

00:20:52 Alfie: The second is that they completely overlook non-traditional candidates, which I think is an issue in terms of bias, fairness, and also just not good sense. Mostly applied for jobs that I haven’t been properly qualified for, but have managed to, at some point, convince someone that the skills that I do have offset the things that I’m missing.

00:21:12 Alfie: They may well have regretted it. But the good hiring processes always have that subjective, qualitative approach and are willing to accept that maybe what they thought they were looking for isn’t actually what they need and be persuaded of that. If you automate a lot of the hiring process on the employer’s side, you lose that flexibility.

00:21:30 Jenny: So really, the way to stand out is not in that first round of screening. You want to basically mimic what the job description is. And then the place that you stand out is potentially in the interview or the next rounds.

00:21:42 Alfie: If there is that sort of objective hurdle that you need to get through early on, then yes. I think one of the things that worries me, and this applies less to the world we’re looking at, more to the sort of white-collar mid-career, is it feels to me like there’s been a bit of a return to nepotism.

00:21:56 Alfie: Because the application market is broken in many of the ways that we’ve discussed, the easiest result is, well, look, I know so-and-so who’s recommended so-and-so, or so-and-so has got a connection into the company, or whatever it happens to be.

00:22:09 Alfie: And LinkedIn kind of makes it a lot easier because you can look at connections. And you end up hiring people through warm introductions. That’s something like the VC world has always been, if I could say, a little bit guilty of. The way money is allocated, the way people raise money, the way people get injections, has always been quite warm introduction-driven.

00:22:27 Alfie: And there’s some logic to aspects of that. But I think it’ll be a sad sign if that becomes more widespread in the jobs market, because it’s not marriage granting. It’s about connection that favors some people over others.

00:23:38 Jenny: Right. So getting back to Rodeo, you guys have had some iterations, and I’d love to just hear a little bit more of where you are today and how you’re thinking about the future of the company.

00:22:48 Alfie: Today we’ve got a product and a whole bunch of users using it to do everything from plan their careers to find opportunities to apply for, to supporting them with their applications. It’s a free tool.

00:22:58 Alfie: It’s really important to us. We’re getting a lot of good validation. I love talking to people who are using the product. I love getting negative feedback. I love getting positive feedback. That’s working well.

00:23:06 Alfie: Ultimately, we see this ideally as working in partnership with traditional career services. There’s a risk of a sort of either or debate between human careers advisors and AI. We’re very strongly of the belief the most powerful solution to ensuring everyone gets the advice and support they need is for a hybrid approach.

00:23:27 Alfie: There’s some people who will prefer to lean more on an AI solution. And this is particularly true because setting up a careers appointment in two weeks time when you’re trying to juggle two jobs that you’re working and family commitments, everything, can be really difficult. AI is amazingly convenient, can enable people to fit it around their lives a lot more easily and has some super powerful aspects to it.

00:23:49 Alfie: But ideally, it can also be combined with human career support so that other people who need the human support most can get access to that. So that there could be safeguards in place, things can be escalated if they need to.

00:24:00 Alfie: Or the AI can be used for something AI’s really good like speedy onboarding via an agent voice call or skills mapping from CVs, job database searches. And then the humans can be used for other aspects that they’re really good at like some of the empathy and support and sense checking. I think there’s a lot of opportunity.

00:24:18 Alfie: So we’re talking to everything from the government through to career services, colleges and schools and further education colleges and charities that work in this area.

00:24:27 Alfie: So the whole ecosystem of traditional career support, which we think is and will remain super valuable. We hope that we can turbo charge it and augment its impact and scale because there is this massive problem that… unemployment is high in the UK and a lot of people have dropped out of the labour market.

00:24:43 Alfie: I’m ultimately an optimist. I think AI is a productivity enhancement. It should make society richer, but the transition is going to be highly disruptive and could be very painful. Giving people support and advice to help them through that transition is going to be super vital.

00:25:00 Jenny: I mean, you’ve mentioned the word impact a couple of times. So what does success look like for you and Rodeo?

00:25:06 Alfie: Our mission is to ensure that all young people have the advice and support they need to help them find the right career path. Now, there are a whole range of different metrics that. But that’s a mission and success will be judged by how many people we’re able to help through that process.

00:25:19 Jenny: Love it. All right. We’re going to just move to the speed round. So just quick, one sentence answers. Book, newsletter, podcast, some media that you’re enjoying right now?

00:25:28 Alfie: I’m currently reading Alison Gopnik’s The Gardener and the Carpenter. She is a professor of psychology and philosophy somewhere on the West Coast, Her work spans everything from childhood development through to AI and cognitive models.

00:25:41 Alfie: I just think that if we’re going to understand what artificial intelligence is, then the starting point and crucial bit needs to be to understand what human intelligence is. And the best place to start back is to understand how babies and children develop and like how we develop human intelligence.

00:25:54 Alfie: Probably also helps that I’ve got a small daughter and so I spend most of my time trying to like understand her. Try and be a vaguely good parent in terms of supporting her.

00:26:02 Alfie: And then I spend a lot of my work life trying to understand what AI is doing, how it works, how it’s going to change society. And so I think her work is this really great intersection of those two areas of understanding like what intelligence is and how it develops, both in a human and artificial sense.

00:26:18 Jenny: Love it. If you could live anywhere in the world for just one year, where would it be?

00:26:22 Alfie: I mean, I’ve been lucky enough to live in a few places. I really enjoyed my time in East Africa. I mean, I was in Uganda, but across Uganda, Kenya, Rwanda. And so given the chance, I would love to go back there at some point in my life, probably not just yet. But the scenery, the outdoors, exploration and activities were just amazing.

00:26:38 Jenny: I love it. Favorite productivity hack?

00:26:41 Alfie: I find handwritten to-do lists are just so much better than anything else. Having a notepad and writing down each morning what I’ve got to do, physically crossing stuff off.

00:26:50 Alfie: I’ve tried over the years any number of tracking tools or perhaps Linear tickets or any of those other tools. But I just want to be able to write everything down in bullet points in a… on pen and paper and then cross it off when I’ve done it.

00:27:03 Jenny: That’s great. And then where can listeners find you?

00:27:05 Alfie: We’ve talked about LinkedIn. It’s not my natural environment. I’m as critical as probably many other people are of that environment, but it’s functional. So either that or, I don’t know, Strava.

00:27:15 Jenny: LinkedIn or Strava? First time answer on that one.

00:27:18 Alfie: Depends what you want to ask me.

00:27:20 Jenny: There you go. All right. Well, this was a real pleasure, Alfie. Thanks so much for taking the time. And we are excited about Rodeo and all those lives that you’re going to be impacting. So thanks for joining.

00:27:30 Alfie: Great. Lovely to talk. Thanks, Jenny.

00:27:34 Scott Hartley: Thanks for joining us and hope you enjoyed today’s episode. For those of you listening, you might also be interested to learn more about Everywhere. We’re a first-check pre-seed fund that does exactly that, invests everywhere. We’re a community of 500 founders and operators, and we’ve invested in over 250 companies around the globe. Find us at our website, everywhere.vc, on LinkedIn, and through our regular founder spotlights on Substack. Be sure to subscribe and we’ll catch you on the next episode.

Read more from Alfie Pearce-Higgins in Founders Everywhere.

• Strong: Maintain inputs, generate greater output with AI amplification

• Skinny: Truncate inputs, generate the same output on AI efficiencies

Ten years after publishing my book, THE FUZZY AND THE TECHIE, I still get invited once a quarter to speak to corporate audiences about the evolution of technology, and importance of human skills, soft skills, in the stewardship of that technology toward the gravest problems. This story has evolved from one of spotting bias in big data, providing context to code, into one that revolves around human skills in the era of AI. Today AI proliferation has further deepened the leadership trade-offs around AI adoption for efficiency gains and cost cuts, weighed against AI adoption for growth and output expansion through human labor amplification.

In 2017 I gave the example of radiologists, whom many at the time claimed would be “out of a job,” to highlight where this “skinny” myopia overlooked the reality that AI would not obviate all radiology jobs, but bring costs down, expand the demand for MRIs, and fuel a massive boom in radiology where there might be net new demand. In those ten years since the book we’ve seen the rise of Prenuvo, Ezra, EverLab, Function Health, Axo Longevity, and a number of players bringing this reality to fruition. While many feared a “skinny-only” outcome, what prevailed was predominately strong. Inputs remained relatively fixed, meaning not all those radiologists became unemployed, output expanded, costs came down, and demand skyrocketed. Today there are more radiologists than there were ten years ago. Opposite of expectation.

As AI efficiencies brought radiology costs down, and expanded demand, radiologists were pushed farther out onto the frontier of the “map,” working on edge cases that AI could not fully automate. What was truncated were not radiology jobs, but the rote tasks within radiology that made the work inefficient. By streamlining these rote tasks with the aid of AI, the time required to perform and interpret a scan went down, and thus radiologists were able to perform more scans in the same unit of time. This expansion in output on the same inputs (Strong), drove costs down. Relatively price sensitive consumers were suddenly able to afford something previously inaccessible, and so demand expanded, yielding a much larger than expected consumer market.

In every organization there are many jobs. And Jobs are comprised of individual tasks. Those tasks break down along two vectors. Tasks can be manual or cognitive, and they can be routine or non-routine. For rote manual tasks, robotics can substitute for human labor. For rote cognitive tasks, artificial intelligence can enable significant gains. Within these subsets of tasks, like routine radiology, AI can yield efficiency gains that allow leaders to make a choice. If they opt for “Skinny” they could cut inputs, and perhaps still generate the same output. But in a competitive market where your competition may not do the same, “Strong” is often the preferred choice, where inputs are maintained or only marginally cut, and AI-enabled outputs drive growth. In the case of radiology, given the relative price sensitivity of consumers, this growth actually yielded expansion in market size, demand, and net new jobs were created.

In practice, there are adoption timelines for technological substitution, and even in a “Skinny” scenario where a company chooses to cut human labor for machine, there are, in nearly every case, situations in which a human steward is still required. Technological capability still belies the organizational complexity of adoption, so the headlines will always front-run the reality we experience as employees.

For most jobs, however, a different story exists. Most jobs contain a high proportion of non-routine tasks that require creativity, collaboration, communication, and these are jobs wherein AI adoption is not an ultimatum, but a serum for higher productivity. These are the domains of “Strong” AI adoption, where AI might rather be called IA, or intelligence amplification. Human skills are enhanced, not obviated, and AI pushes these employees out of the rote and routine tasks into more human capabilities.

Omar Haroun, CEO at Eudia, talks about a “Pareto Compression,” where the old adage of 20% of inputs driving 80% of outputs is being compressed. In this new world, expertise is rewarded exponentially, with perhaps 5% of inputs driving 95% of outputs. This doesn’t mean we’re all doomed. What it means that in every role, every job function, humans will be pushed into that zone of genius, that 5% where what they do truly counts. In the case of radiologists, it’s the interpretation of non-routine cases, more patient engagement, an expansion in the need for soft skills, coordination, and communication. Pareto Compression does not mean a compression in the number of people to do the job; it means a compression in the task-sets within every job, pushing every performer to higher, more satisfactory marginal work, on top of AI. Like the radiologists, it can expand demand, and push the role to the frontier of accretive human capability. In other cases, it doesn’t mean everyone must become an expert; on the contrary, it broadens the base of who can do the job, and opens doors.

In a competitive environment the choice of Strong vs Skinny is not an ultimatum, or a zero-sum choice; it is the requirement of every organization to dive deep into jobs, identify tasks, and choose where to apply “Skinny” and where to apply “Strong.” Most organizations will have to do both by trimming non-routine tasks with robotics and AI, and by amplifying non-routine tasks with these extraordinary new tools. The world of AI adoption is one of rote task elimination, a broadened base of who can do the work, and a Pareto Compression of expert work amplified significantly. The error is in thinking that AI adoption is only one zero-sum choice; in fact, it is many, and in most cases leaders will find needing to have a “Yes, And” conversation about cost cuts and Skinny, and growth drivers and Strong, a widened funnel of whom they can employ, and a premium paid for true domain expertise and depth of experience.

Special thanks to David Travers and the ZipRecruiter leadership team for inviting me to speak on these and other themes in April 2026, and further refine the ideas. For more about Everywhere Ventures, subscribe to our 40,000 person newsletter.

Fertility care remains one of the most expensive and unpredictable areas of healthcare. Flora Fertility is working to change that by introducing a new approach to how fertility treatments are financed and accessed.

In a recent Athletech News piece, the company announced a $5 million raise to expand its platform and bring its model to more patients. Laura J. McDonald, co-founder and CEO is focused on creating a system that aligns incentives between patients, providers, and outcomes.

Flora’s model is built around the idea of customer-owned reproductive insurance. Instead of traditional insurance structures that can be restrictive or opaque, the platform allows individuals to contribute toward fertility care in a more flexible and transparent way. The goal is to reduce financial uncertainty while improving access to treatment.

The need for new solutions in this space is clear. Fertility treatments often come with high costs and variable success rates, leaving many patients navigating both emotional and financial challenges. Existing insurance options are limited, and out-of-pocket expenses can be significant.

Flora aims to address this by creating a system where patients have greater visibility and control. By aligning financial incentives with outcomes, the platform is designed to support better decision making throughout the treatment process.

The funding will be used to further develop the product and expand access, as the company continues to build its network and refine its offering. The broader vision is to create a more patient-centered approach to fertility care, where financial structures support rather than hinder access.

Flora’s approach reflects a growing trend in healthcare innovation. Companies are rethinking traditional insurance models to make them more flexible, transparent, and aligned with patient needs.

For Laura and the team, the opportunity lies in transforming how fertility care is financed, making it more accessible while giving patients a stronger role in their healthcare journey.

Read the full article on Athletech News

People assume hospitals bring in big money because healthcare is expensive, but the reality is very different. The average health system in the U.S operates on margins as low as 0.5% to 2%, and many are even in the red. Instead of generating steady profits, many providers are effectively living on 30-day cash cycles, relying on timely reimbursements just to stay afloat. The biggest lever they have is how efficiently they collect revenue from insurance companies. Recognizing this, Adonis set out to modernize one of healthcare’s most overlooked systems. They are building an AI-powered platform that automates the full revenue cycle, from claim submission to denials and appeals, helping providers increase collections, reduce administrative overhead, and get paid faster. Adonis recently raised a $40 million Series C to expand further into large health systems, invest in product development, and to hire and grow its New York–based team.

Co-founder and CEO Akash Magoon started Adonis with his brother, Aman Magoon, CPO, building on a partnership that began with their first company, an employee benefits software that acted as a turbo-tax like experience for choosing benefits during open enrollment. While working closely with insurers at that company, the two gained an inside look at how claims are evaluated (and often denied), giving them a rare understanding of the system from the payer side. After exiting the company, they saw an opportunity to flip that insight on its head and build for providers instead. With a background in computer science and experience as a software and machine learning engineer, Akash brings a technical and product-driven approach to a deeply operational problem. The brothers are now focused on transforming one of healthcare’s most complex financial systems into something far more automated, predictable, and efficient.

What inspired you to build Adonis?

My brother and I grew up in an entrepreneurial Indian‑American household where being a doctor was always the highest calling. We realized that practicing healthcare itself wasn’t what excited us, but building for healthcare did. We realized we could still make a significant impact on the lives of so many patients by building at the intersection of healthcare and software. That’s the part we fell in love with and motivates us to build everyday.

What’s Adonis’ North Star?

Our goal is to minimize friction around revenue so hospitals can reinvest those proceeds back into improving patient care. Five to seven years from now, we want the revenue cycle for a provider group to be as automated as it is for a local coffee shop, where you swipe a credit card and get paid consistently. The practical version of that is moving from a world where every claim is touched by a human to an exceptions‑driven revenue cycle, where maybe 1 out of 100 claims (the gnarliest and hairiest ones) gets human attention.

Tell us about a recent milestone that Adonis crushed.

We recently closed our $40 million Series C, with a strong mix of existing investors, like General Catalyst, Bling Capital, and Max Ventures, plus new investors like Quadrille Capital, who led our round with the largest check. It’s a great combination of long‑term believers and new growth‑stage partners as we hit this next inflection point. 2025 was a breakout year, with strong product‑market fit, several major health‑system wins, and more than 4x revenue growth, which set the stage for this round.

What I’m personally proud of is that we’ve done this while building a New York–based, in‑person culture. We opened our office in 3 World Trade Center in month one and have been very intentional about making Adonis one of the most challenging but rewarding places our team will work. We recently put together a video to show what it’s like to work at Adonis, check it out here! We have 80+ employees today and are hiring; you can see open roles on our careers page.

What makes Adonis a “must‑have” vs a “nice-to-have”?

I like to answer that by asking: what happens if a customer wakes up tomorrow without Adonis? If that happened, they’d probably collect 10–15% less cash that month and have to staff up their revenue cycle team by 30–35%. That combination would likely create a pretty hard cash crunch within the quarter. That’s the must‑have story for us, if you pull us out of the system, the financial and operational hit is immediate and painful.

How does Adonis inspire “customer love”?

We’ve built an AI platform that studies all the claims, learns how insurance companies are denying claims for specific reasons, and then uses AI agents to automate the entire loop: submission, denials, and appeals. At a high level, we focus on improving three core KPIs for our customers: net collection rates, headcount costs, and speed to payment.

• Net collection rates – most hospitals collect about 90% of what they’re owed; we’re trying to get them into the upper 90s.

• Headcount costs – revenue cycle teams are a big chunk of the workforce and there’s a lot of administrative bloat; we focus on reducing that overhead.

• Speed to payment – today it often takes 60–65 days for a provider to get paid after a visit; we’re working to cut that in half.

Fun fact:

I stay closely connected to my alma mater, the University of Maryland, by actively giving back. I founded a scholarship, serve on multiple university boards, and mentor students, helping the next generation of Terps break into tech and startups.

Listen to Elliot Katz with Scott Hartley, on the Venture Everywhere podcast: In the mixus. Now on Apple & Spotify. Check out to all our past episodes here!

Healthcare systems are under increasing pressure to manage risk, improve outcomes, and operate more efficiently. Keebler Health is focused on addressing that challenge by applying artificial intelligence to clinical and operational decision making.

In coverage by Fierce Healthcare, the company announced $16 million in new funding to expand its platform and accelerate adoption. At the center of the company is Isaac Park, CEO of Keebler Health, who is leading the effort to bring AI driven insights into everyday healthcare workflows.

Keebler Health’s platform is designed to help providers identify risks earlier, using data to surface patterns that may not be immediately visible. By doing so, healthcare teams can intervene sooner, improve patient outcomes, and reduce downstream costs.

The need for this type of technology continues to grow. As healthcare data becomes more complex and abundant, providers are looking for tools that can translate that data into actionable insights. Traditional systems often fall short, leaving gaps in visibility and delayed decision making.

Keebler Health is positioning itself within that gap. By integrating AI into clinical workflows, the platform supports more proactive care, helping organizations move from reactive treatment to earlier intervention.

The funding will support continued product development and expansion as the company scales its impact across healthcare systems. It also reflects broader momentum in AI driven healthcare solutions, where investors are backing platforms that can deliver measurable improvements in both outcomes and efficiency.

For Keebler Health, the focus remains on building tools that fit naturally into how providers operate, ensuring that technology enhances rather than complicates care delivery.

As the healthcare industry continues to evolve, platforms that can combine data, intelligence, and usability will play an increasingly important role. Keebler Health is working to be part of that transformation.

Read the full article on Fierce Healthcare

In episode 115 of Venture Everywhere, Scott Hartley, co-founder and general partner at Everywhere Ventures, talks with Elliot Katz, co-founder and CEO of mixus AI — a legal AI platform that lets attorneys delegate work to agents directly from email. Elliot shares how riding in early autonomous vehicles and seeing the gap between the hype and the technology convinced him that humans would always need to stay in the loop — a conviction that drove him from law to co-founding mixus. He discusses how mixus is cutting through a crowded legal tech market by demanding zero behavior change from attorneys, meeting them in email and Word rather than asking them to learn yet another dashboard.​​​​​​​​​​​​​​​​

In this episode, you will hear:

• Applying the human-in-the-loop thesis from autonomous vehicles to legal AI.

• Winning AmLaw 20 firms through zero behavior change integration.

• Taking financing workflows from days to minutes with email-native agents.

• Shifting corporate legal work from billable hours to fixed-fee engagements.

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TRANSCRIPT

00:00:04 VO: Everywhere Podcast Network.

00:00:14 Jenny Fielding: Hi, and welcome to the Everywhere Podcast. We’re a global community of founders and operators who’ve come together to support the next generation of builders. So the premise of the podcast is just that founders interviewing other founders about the trials and tribulations of building a company. Hope you enjoy the episode.

00:00:32 Scott: Hi everybody, Scott Hartley, co-founder and general partner at Everywhere Ventures. Super excited to have my really good friend, longtime friend, and portfolio CEO, Elliot Katz on the call here today with mixus AI.

00:00:45 Scott: So Elliot and I both grew up together in Palo Alto, California. We’ve known each other since we were probably 10 years old playing knockout basketball in the driveway. Elliot went on to Vanderbilt and Cornell Law, and then built a career at DLA Piper, where he was an attorney.

00:01:02 Scott: I know you started the autonomous vehicles practice well before that was a thing. You really had incredible foresight to dive in deep and build the AV practice at DLA.

00:01:12 Scott: And then, I think from that, you learned a ton about this whole world of human-plus-machine automation, went on to found Phantom Auto, raised a lot of money for that. And then saw this movie replaying in the legal space with mixus AI. We’re super excited to be investors in the company, and welcome to the podcast, Elliot.

00:01:31 Elliot: Thanks, Scott. Great to be here. It’s been quite a journey for us over, I think, about 30 years at this point.

00:01:37 Scott: I know we’re not gonna recount trampoline stories or knockout basketball stories today, but there’s plenty of that for the off-podcast conversation later.

00:01:47 Scott: Walk everybody through your journey because you started on a traditional career path in law. Went to a great firm, became a partner. What was it that you saw in this development of autonomous vehicles and human plus machine and robotics that made you want to start the AV practice and then jump out into Phantom Auto and into mixus.

00:02:06 Elliot: As you mentioned, I started at DLA Piper. I became the chair of their Autonomous Vehicle practice. Then I went to McGuireWoods, became a partner and chair of their Autonomous Vehicle practice.

00:02:18 Elliot: But by dint of the fact that I was very early on autonomous vehicles, I was one of the only attorneys at the time—if not the only attorney—that was focused on legal, regulatory, and policy issues pertaining to that space. Because of that, I got to represent a lot of the biggest players in the space at that time.

00:02:41 Elliot: It was still very, very early days. And through that, I got to ride in all of their vehicles. I had a front-row seat to see the delta between the actual state of the technology at the time and the marketing.

00:02:58 Elliot: So if you asked my grandma in 2014, she read a New York Times article that told her she was gonna fall asleep in Palo Alto and wake up in New York and never have to touch the steering wheel in between. The car was just gonna do everything.

00:03:12 Elliot: And at that point in time, that couldn’t have been further from the truth. When I’m riding in these vehicles, my clients’ vehicles, you couldn’t go more than 100 yards without something going wrong.

00:03:23 Elliot: What I started to think about at that time was if you actually want to commercially deploy these vehicles at scale, there has to be some sort of technology that can keep a human in the loop. There’s just too many things that were going wrong and that would go wrong in the future. There’s just such a long tail of these edge cases. A lot of weird things happen out on our roads.

00:03:48 Elliot: And so fast forward to 2017, I was connected with my now co-founder, Shai Magzimof. There was a VC that I was doing some work with that came to me and said, “Hey, there’s a new guy in town. He built this technology and we think it’s the technology that you’ve been talking about for some time. Go meet with him.”

00:04:06 Elliot: “We’re thinking about making an investment.” So I went over to Shai’s house in Palo Alto. He put me in a car in his garage. He went to his living room. He drove me around the block in Palo Alto via remote control. My brain basically exploded because that was exactly what I had been dreaming about.

00:04:23 Elliot: What happens when something goes wrong with these vehicles? Well, if you can have a human sitting thousands of miles away, that’s able to remotely assist or even operate the vehicle, then you have a full system.

00:04:35 Elliot: And so at that point, I left the practice of law entirely. We started Phantom Auto together, and our technology was just that. Now, the problem there with autonomous on-road vehicles is it was still quite early days. I mean, now you can actually get a Waymo, especially if you live in the Bay Area. I would highly recommend it. It’s an amazing experience.

00:04:58 Elliot: By the way, they still use some form of remote-assistance technology—exactly what we were talking about all the way back then. But it was very early days, so no one had actually gone to market.

00:05:09 Elliot: We ended up pivoting to vehicles that were more so in enclosed areas like forklifts in a warehouse, like yard trucks in a warehouse yard. That was a great business because even when you’re in an enclosed environment, again, you still need a human to help out the autonomy. So that took us through Phantom Auto.

00:05:31 Scott: Just to jump in there, I remember it was probably around that time, 2016 or so, 10 years back, maybe even before that, where we had lunch at the Four Seasons on University Avenue in Palo Alto and you told me that you were thinking about leaving law to go and be a startup entrepreneur.

00:05:48 Scott: Even though I live in this world, I think I said, “Time out. Beware of what you’re wishing for. Don’t do it. Don’t do it. Don’t leave the confines of a highly paid, nice office to come out into the wilds.” But you had such conviction at the time and really had the foresight to make that leap.

00:06:03 Scott: It was something that really resonated with me as well, because that was around the same time that I was writing my book about human and machine and all these interfaces that needed to come together.

00:06:12 Scott: Actually, I think you inspired me to talk to a woman that’s featured in my book, Melissa Cefkin, who’s the lead anthropologist at Nissan, but running the autonomous vehicles practice. The whole idea there was that the edge cases of autonomous vehicles are often tacit communication. They’re human edge cases issues.

00:06:31 Scott: And so why would you have at the helm of an autonomous vehicles practice somebody who has a PhD in anthropology? It really confirmed all of those things that were the thesis behind Phantom Auto and even the thesis behind mixus today.

00:06:45 Scott: That there’s rote and routine tasks that can be automatable up to a certain point. And then there’s generally a gap where you have to have human in the loop. You’ve been beating this drum for 10 years, and I think you’re still right on the money.

00:06:59 Elliot: What myself and Shai, my co-founder, like to say when we open any meeting is “We are the human-in-the-loop guys.” If you believe that AGI is here and humans are just going to be able to go frolic at the beach and the AI is just going to do all the work, we’re not those guys.

00:07:16 Elliot: Our view is that autonomy and autonomous vehicles, they can do so much. Again, you will be blown away if you ride in a Waymo or if you’ve already rode in a Waymo, but they have their limitations.

00:07:29 Elliot: We took that same concept and now applied it to high-stakes work. In legal. there’s amazing things that our AI agents can do for attorneys. They can do so much of the work, but they can’t do all of the work.

00:07:48 Elliot: There’s so many things that you need human judgment for, especially in the law. Typically, people don’t come to lawyers for just straight-up black letter law. They’re looking for their interpretation, their judgment, their assessment of risk, et cetera.

00:08:05 Elliot: Even though AI can do a very good job with the basics, you still need to “mixus” together. That’s the name of the company—mixing together human intelligence with artificial intelligence. That is the way that you’re going to get a complete product.

00:08:23 Scott: 100%. Shifting gears, so Phantom Auto obviously had human in the loop, remote operators and drivers of forklifts in facilities, say, in the US where you could have that vehicle driven from Mexico. You could do cost arbitrage and 24/7 support without needing to deal with some of the current issues that we have around immigration and various things like that.

00:08:46 Scott: But fast forward to where you guys are today with mixus. Taking that same principle, but rather than a forklift operator operating remotely from Mexico to Central Valley, California for Home Depot, it’s instead a lawyer being able to offload tasks to agents in specific workflows where they can interface with both their associates, but also with AI agents powered by mixus to supercharge the expertise that those lawyers already have.

00:09:14 Elliot: That’s exactly right. There’s a lot of differences between Phantom and mixus. It’s a different space. But at Phantom, you hit the nail on the head. So, we worked with very large Fortune 50 customers, some of the biggest businesses in the world. They had remote operators sitting literally, in some cases, thousands of miles away, in some cases on a different continent.

00:09:41 Elliot: Those remote operators were not employees of our customers. They were employees of Phantom Auto. Now here, everyone who’s working with our system is an employee of whatever the organization is that’s using the system.

00:09:56 Elliot: So right now, we’re working with some of the largest law firms in the world, multiple AmLaw 20 firms. And to be clear on exactly what we’re providing them, we’re providing them email-based AI agents with that built-in firm-level oversight.

00:10:15 Elliot: What is important about that is a couple of things. First of all, we are mimicking exactly the way that attorneys work today. What attorneys do today, they’re mainly on email, they’re in Word.

00:10:29 Elliot: So, when you want to use one of our agents, instead of emailing your associate “@John do X, Y, Z,” you email the agent, agent@mixus.com, and say “@Agent do X, Y, Z.” It’s all collaborative because the law’s a team sport, so you can CC any of your colleagues. Everyone can talk to the agent together. Anyone can review the outputs.

00:10:53 Elliot: But the point is that you just email. You do exactly what you’re already doing today. You email the agent, the agent is going to email back the work product. Then there’s a human attorney who will review and make sure that everything looks good.

00:11:07 Elliot: A very overlooked piece of this whole transformation that we have in AI is that change management piece. A lot of other tools in the space, it’s providing a net new tool with a net new UI, and you’re asking attorneys to learn that and bring that into their workflow.

00:11:28 Elliot: We’re doing the opposite thing. We’re starting where the attorneys already are and just saying, “Keep on doing what you’re doing, but now do it with an agent involved.”

00:11:38 Scott: It’s a really important point because I think that as these tools, we’ve seen a whole glut of legal AI tools come to market. This was a space that probably wasn’t that heavily trafficked five years ago.

00:11:49 Scott: Nobody was in their thesis, from the investor standpoint saying, “We’re looking for legal automation software.” That wasn’t a thing. Now, it’s probably one of the hottest categories that there is. You see the rise of forms like Harvey and others in the space.

00:12:03 Scott: But to your point, they really have a new work dynamic where they’re not catering directly to how law partners and operators are historically working. Which, to your point, it’s… you’re running between meetings, you’re running from a launch to something else, you’re rifling off a contract to an associate to redline and come back with feedback.

00:12:23 Scott: And instead of that workflow being at the desk, sitting down with the dashboard, it’s primarily happening over email. It’s happening on a mobile device. And that’s where mixus is trying to embed is in these specific workflows that partners to associates are already doing and have been doing for a hundred years.

00:12:41 Elliot: Absolutely. The work is also happening in Word. So, we have a Word plugin as well, but we are tracking exactly where they work. It’s all in the Outlook, Microsoft Outlook, and Word. That’s where we sit.

00:12:52 Elliot: What I will say is that when I was at DLA, for example, when I was a very junior attorney, I remember working with one much older partner who he was a brilliant attorney, but I don’t even know if he knew how to turn on his laptop. I’m not exaggerating.

00:13:11 Elliot: Attorneys are not always at the bleeding edge of technology, especially in the older generation. I think the newer, newer generation, the folks that are going to law school now and coming out of law school, they’re going to be trained on this new technology because it’s such a big part of how you practice the law.

00:13:27 Elliot: But this idea that you can get this certain subset, which is a large subset of attorneys to learn this new technology and integrate it into their practice, I think is a non-starter.

00:13:39 Elliot: We’re seeing that in real time. Most of the firms, if not all of the big firms that we’re working with, they already have seat licenses to use other legal AI tools. But what we hear consistently is they brought in those tools, not because they don’t think they’re going to be value add. Of course they do. But the uptake isn’t there amongst their attorneys.

00:14:02 Elliot: So again, that zero behavior modification that we’re enabling, I think is often overlooked, because people are really focusing on the technology, but critical piece in getting AI technology into his attorney’s hands and having them use it on the daily as opposed to something that’s on the side, “Okay, maybe I’ll use it once a week.”

00:14:23 Scott: And that’s a prime case of having domain expertise, understanding workflows, understanding the ICP, the customer profile and how these guys operate day to day. You’re not building technology in the abstract and then trying to shoehorn it into a law firm in the form of how Salesforce works.

00:14:40 Scott: What you’re trying to do is look back historically at how you operated as an acting attorney and partner at multiple law firms and saying, “This is really where the rubber hits the road. Our go-to-market has to be through zero behavior change integration into existing workflows,” which I think will serve you guys well.

00:14:57 Elliot: Absolutely. It’s hard to think like an attorney if you’ve never been an attorney. I am a recovering attorney. When I was practicing law, my brain was always thinking about how can I bill the next six minutes of time.

00:15:13 Elliot: And if you have to take six minutes, let alone an hour or two to learn a new tool and then get used to that new tool and integrate it into your practice, that equation is tough. You want to keep on doing what you’re doing and effectively bill time pretty much all of your day.

00:15:27 Scott: Thinking about like the specific workflow is, where have you guys seen the most traction as far as hyper-specific point solutions around specific legal examples? Is it in redlining? Is it in contract review? What are some of the workflows where you guys have come to market with the initial agents and where you’re seeing a lot of uptick from these AM 20 law firms?

00:15:48 Elliot: First of all, we have many, many different agents that we’ve deployed that do everything across the board. That’s from document generation to document redlining to data extraction.

00:16:00 Elliot: But I’ll use an example that’s near and dear to my heart as a startup founder and probably near and dear to yours as a VC, which is… we work with a lot of ECVC practices. We can take them with our agents, soup to nuts, through that financing process.

00:16:18 Elliot: Let’s say that Everywhere sends me a term sheet today. What’s the first thing that I’m going to do? I’m going to send it to my ECVC partner and that partner is probably going to send it to one of their associates to do the actual underlying work. And then a few days later, I’ll get back what I want, which is a red line of the term sheet and an issues list.

00:16:39 Elliot: If you’re using mixus, if our attorney is using mixus, I forward them those materials, they forward it to agent@mixus.com. The agent in a couple of minutes will send them back the exact same thing, which is a red line of the term sheet and an issues list, which is exactly what I want. So, that’s step one.

00:16:58 Elliot: What’s the next thing that you have to do in the process? Well, as a founder, I want to see the pro forma cap table. So again, the attorney emails the agent. You attach the previous cap table in the new term sheet. A few minutes later, it’s going to give you the pro forma cap table.

00:17:12 Elliot: What’s the last step of the process here? Well, let’s say that we’re raising series A and in our seed, we had the MVCA docs, but they’re for seed. So now, we need the MVCA docs for the A round.

00:17:23 Elliot: So again, you email the agent and they’re going to provide you with those new docs. Soup to nuts, we’re taking them through this whole process that used to take days in minutes. It’s a great outcome for them. It’s a great outcome for us.

00:17:37 Scott: It seems like, in the go-to-market, the benefits of this for the law firm could be two-fold in the sense that if you’re a top tier law firm utilizing these tools, where you can gain more efficiencies.

00:17:48 Scott: The obvious question for a lot of these guys is, isn’t this going to reduce my billable hours and therefore my business revenue? The general consensus is it allows the attorneys to up level and upskill, have more human interaction, and obviously offload the really rote and routine tasks that they didn’t want to do anyway.

00:18:05 Scott: That assumes that there’s unlimited business maybe behind that law firm where they can continue to eat away at more interesting work and give away this less interesting work.

00:18:14 Scott: The other bucket is maybe empowering smaller law firms to be able to compete in the sense that you have this idea of strong and skinny with AI. Skinny being you can save costs and cut corners here and there and have the same output.

00:18:29 Scott: Strong being you could be a really small team and suddenly punch way above your weight, where you may be a team of 20 attorneys. But now with mixus with supplemented and enhanced and amplified with AI, you could compete with a law firm that has 200 attorneys.

00:18:44 Scott: Where are you seeing more uptake or demand? Is it more in the big law firms enhancing efficiencies and outputs, or is it in the smaller law firms that really now can punch above their weight and compete?

00:18:55 Elliot: There’s a couple things there because you looked in the billable hour too. So let’s cover that. First of all, I was shocked at the pace with which the firms that we’re working with now engaged with us, in the sense that law firms are very conservative. It’s like enterprise sales.

00:19:13 Elliot: But they’re moving very quickly right now because if their competitors are leaning into AI and they’re not, they have a big problem, potentially an existential problem. That’s number one.

00:19:23 Elliot: Number two, in terms of the billable hour, we work with and speak with a lot of different law firms, some of the biggest law firms in the world. Maybe that won’t change on the litigation side, but I get the sense that on the corporate side, there’s going to be much, much more fixed fee work.

00:19:40 Elliot: Meaning, you handle our entire financing. Instead of billing us by that hour, we’ll pay you a hundred thousand dollars and you do all of it. And then the client doesn’t care if it got done in 10 minutes or it got done in 10 hours. They’re just looking for an outcome.

00:19:57 Elliot: I think that the way that large firms are looking at this right now is… listen, we have a ton of competition out there. Everyone’s kind doing the same thing. If other people are getting these gains, they’re going to pull clients away from us.

00:20:10 Elliot: Now on the small firm side, we are working with a firm that’s about 100 attorneys. They’re very, very innovative. And I think that they’re very much so thinking about AI in the right way.

00:20:22 Elliot: They’re very much leaning in with our product and they are already rolling out a client facing version, where their clients can email in to firm email address, their AI email address. They can email in term sheet or MSA or an NDA, whatever it is.

00:20:40 Elliot: The agent is going to take the first pass at doing the work. And then our agent is going to route that to the appropriate attorney, the subject matter expert within the firm, to just review and make sure that everything is okay. They’re going to charge a lower fee to do that.

00:20:56 Elliot: Now, My initial thought was, how is this going to work? Because if you’re just charging a lower fee, you’re going to take a revenue hit.

00:21:03 Elliot: The founder of the firm, who’s a very forward thinking person, said, “No, you’re not seeing it. If we do it this way and it catches fire, which I think it will, we’re going to have more and more clients coming to us. Because they can get the same service.” It’s not better. The agent does an incredible job and you still have the human in the loop for a much lower cost.

00:21:24 Elliot: That’s the basic ways that I think firms are thinking about this. Now, the interesting thing here is a lot of firms are using these legal AI tools that have been on the market now for some time.

00:21:38 Elliot: But I don’t know where the advantage comes at the end of the day if you’re all using the same thing. So they’re all still trying to seek out alpha and see where the edge is. Only time will tell as to which firms really pull ahead and which do not.

00:21:53 Elliot: Now, one other thing that I’ll mention, Scott, real quick is we’ve had some very interesting discussions with some elite law firms, old school, white shoe law firms, which from a technological perspective, I’m pretty concerned about their ability to lean in.

00:22:13 Elliot: There could be a big shakeup in this space because we talk with firms that have not yet migrated to the cloud, right? They’re still completely on-prem.

00:22:23 Elliot: So I think that there’s going to be a separation, not based on how people have viewed these firms before, meaning their level of lawyering, but based on their ability to lean in to AI. Because now everyone, or soon everyone, will have access to the same intelligence. It’s how you’re able to use and maneuver with that intelligence.

00:22:47 Scott: It’s fascinating. I wonder if you looked back at the prior rise of LexisNexis or the earlier technology waves that hit the legal industry where you had old school law firms literally utilizing law libraries and looking up case law versus those in the 90s or the 2000s were heavily leveraging the new systems like LexisNexis at the time.

00:23:09 Scott: If there was a big inflection point of who won clients and who took market share during that time, it’d be interesting to see because we’re probably at another inflection point, where those firms that can lean in and adopt these new tools are going to have a structural advantage to be able to win clients, get back faster.

00:23:27 Scott: The other parallel it reminds me of from 10 years back was the debate about radiology and medical imaging. And everybody said AI is going to take away all these jobs because what’s a radiologist do but look at images and find certain anomalies.

00:23:43 Scott: Of course, what it did was it lowered the cost of MRIs, made radiology a more in-demand service, and you have the rise of things like Pronovo, Ezra, Everlab, all sorts of at-home almost MRI scans where you can, for 500 bucks or 1,000 bucks, get something that used to cost 20,000.

00:24:00 Scott: It really democratized the space. It didn’t erode the demand on radiologists. It actually made that a more sizable career path because the costs of running MRIs went virtually to zero.

00:24:13 Scott: Similarly, to the partners comments about increasing demand, if the cost and the marginal cost of doing some legal service was super low, I would probably get more feedback, more advice on a much higher cadence than I currently do because we play defense as much as we can and only talk to lawyers when we want to pay them $2,000 an hour, which is not very often.

00:24:32 Elliot: By the way, there’s more radiologists today than there were five years ago. People ask me all the time, even attorneys. We work with a ton of attorney. Is AI going to take my job completely away?

00:24:45 Elliot: And my answer is a resounding no. You are not going to lose your job to AI. The risk to your job is losing it to another attorney who’s very good at using and savvy at using AI. I do think that attorneys absolutely need to lean in to using these tools immediately.

00:25:07 Elliot: Because like you mentioned Westlaw, LexisNexi, those are all tools that I used when I was an actual practicing attorney. They’re helpful for doing the job. With our agents, you’re talking about things that do the job completely.

00:25:20 Elliot: And so, the attorney needs to get used to being the final sign-off, being the person who has the knowledge to be able to make the judgment call. Did the agent get it right? Did it not?

00:25:32 Elliot: AI is just guessing the next most probable word. Actual attorneys have the experience to know, “Hey, I need to make a judgment call here. I need to base this on risk. I need to base this on the risk profile of my client, who the counterparty is, et cetera.” Lawyers are still going to play a huge part of the role. It’s just a changing part of the role.

00:25:53 Scott: There’s a great piece that somebody that you know. Omar Jarun from UDF, wrote a piece a week ago about the compression of Pareto. And so this Pareto principle that came from wherever it was decades ago, that 80% of outputs are driven by 20% of inputs.

00:26:09 Scott: And the compression of Pareto being that with AI, maybe that 20% compresses down to 5% where each attorney needs to find their edge where they have a real true comparative advantage in whatever domain. Because those that are the best in those domains, they’re in the top 5%, they’re really going to be able to supplement 95% with AI.

00:26:30 Scott: You got to be farther out there as the tip of the spear in whatever domain is your expertise. And a closing question, existential question for the bottom rungs of the ladder. The way I think about it is maybe the middle rungs are the ones at risk to your point where attorneys that are in the practice don’t fully yet adopt AI.

00:26:50 Scott: Because as you said, the new graduates coming out of law school are going to be heavily adept with this stuff and come in swinging way above their weight. And they’re going to be supercharged from day one as first year associates. And then maybe you have the bleeding edge AI doctors that are the tip of the spear, those top 5% in their practice areas.

00:27:08 Scott: And where it seems the real erosion in the legal industry could happen is in folks that are already in the role but are not savvy enough to adopt AI or lean heavily into tools like mixus. Where do you kind of see that hierarchy or where the opportunities might be or the erosion might happen?

00:27:24 Elliot: I already see it today. When we work with firms, it depends on how long we’ve been working with them. Usually, we start with a practice group or maybe 20, 25 people.

00:27:35 Elliot: The people that are using the tool every day, and I know they’re using the tool every day because they’re constantly giving us feedback. They’re excited. They’re pinging us. How can I do X, Y, Z?

00:27:44 Elliot: Oftentimes that’s the first-year associates, first and second year associates. They’re very much leaning into AI. So, those folks, I’m very bullish on their careers, not because they know a ton yet. Law school doesn’t actually teach you how to practice law. It just teaches you how to read cases.

00:28:03 Elliot: And so, they still have to learn the practice of law, but they have a very unique in right now, is they understand how to use the AI tools. That’s making them very uniquely situated at these firms to be value add.

00:28:17 Elliot: Because in the same way that partners, long time partners at those firms are teaching them how to practice law, they’re essentially teaching the partners how to adopt AI technology. So, that’s on the low end.

00:28:29 Elliot: On the much higher end, say a 30-year partner or whatever it is, those partners have years and years and years of practice under their belt of being able to make these assessments, being able to make these judgment calls because they’ve gone through all the motions.

00:28:46 Elliot: Law is not about black letter laws. It’s interpreting that based on many different client interactions. Those people have a very valuable knowledge base that the AI, at least at this point, cannot replace.

00:29:01 Elliot: I do think that those people similarly need to lean into AI and/or have very savvy junior associates that can do the AI component of their practice and they come in from above.

00:29:12 Elliot: The portion that I’m worried the most about is if you are, say, a senior associate. You’ve been practicing law maybe for six or seven years. So, you don’t have that same knowledge base as a 30-year partner who knows this stuff like the back of their hand. They have the judgment. It’s almost a reflex at this point.

00:29:34 Elliot: That seventh year is still learning how to practice law and if they’re not leaning into AI, I would be worried about them. Because again, you can get the same baseline intelligence now that a 30-year partner has. You don’t have the judgment.

00:29:49 Elliot: But if you’re not using the tool that gives you that baseline knowledge and you don’t have the judgment, you’re left in this murky middle. And that’s what I’m seeing playing out in real time. Even at the firms that we’re working with, the people who are really pulling ahead are leaning into using the tool.

00:30:04 Elliot: Now, to figure out how amazing the tool can be for your practice, you have to experiment some. You have to get used to using AI. But there seems there’s an inflection point right now where the firms themselves are really coming in from the top and saying, you must use this tool. We’ve seen other attorneys make massive gains and we want to see that for everyone here.

00:30:28 Scott: It’s such a fascinating time to be building and congrats on everything that you guys have done at mixus. We’re super excited for the path forward and can’t wait for my law firm bills to go down through the floor when they start using more of these AI tools.

00:30:42 Scott: I guess in quick lightning rounds, you’ve spent a lot of your life between Tennessee, New York, and obviously Northern California. If you were to live anywhere else outside of those spots, where would you pick to live?

00:30:54 Elliot: I’m a California boy through and through, but if it was outside of California, I’ve spent a good amount of time in Austin, Texas. I really, really like it there. It gets a little too hot and humid for me, for my likes, during the summer, but I think it’s an amazing place to live. They’ve got a thriving tech ecosystem. So, I think that’s where I choose.

00:31:16 Scott: You’re going to follow the train of every other Silicon Valley entrepreneur to Texas for one reason or another.

00:31:24 Scott: What’s one podcast or book that you’re reading you found really insightful recently?

00:31:30 Elliot: I love podcasts. That’s my favorite medium because I’m generally quite busy, but you can listen to it on the run. What is my favorite podcast?

00:31:40 Scott: Other than Venture Everywhere, of course.

00:31:42 Elliot: Obviously, obviously. That goes without saying. I really like the Hard Fork Podcast. The New York Times puts it out. They do a lot of good coverage on AI and other stuff as well.

00:31:55 Elliot: But I think they have a very good and balanced take on where this is all going. What I mean by that is I feel like AI right now, the sector is very similar to American politics, in the sense that it’s very extreme.

00:32:14 Elliot: Either you think that AGI is here and you’ll never have to work another day in your life and the AI is going to handle everything. Or you think this is total and utter BS and these things are guessing the next word and they’re not going to be that helpful.

00:32:30 Elliot: What I like about Hard Fork is they take a very measured approach. They’re journalists, so they’re not trying to hype the technology, but they use the technology a lot themselves. They’re like, both of these extremes are wrong. It’s somewhere in between. And they do a nice job of breaking things down from that lens, which I appreciate.

00:32:46 Scott: I love that. Finally, where can listeners find you online?

00:32:49 Elliot: You can go to mixus.ai. The main other place that you can find me is LinkedIn. If you message me on LinkedIn, I might not be the quickest turnaround, but I’m usually able to get back to those messages. So, that’s a good place to find me.

00:33:04 Scott: Awesome. Elliot, always great to see you. Great to chat. Super excited about mixus and thankful for 30 years of friendship with you and getting to work with you now more than ever. So, it’s great.

00:33:15 Elliot: Likewise. Likewise. If you had told my sixth grade self that we’d be doing this podcast in 2026, I would have been pretty happy about that. So great to be here. Glad to do it.

00:33:24 Scott: Awesome. Thanks, Elliot.

00:33:27 Scott Hartley: Thanks for joining us and hope you enjoyed today’s episode. For those of you listening, you might also be interested to learn more about Everywhere. We’re a first check pre-seed fund that does exactly that invests everywhere. We’re a community of 500 founders and operators, and we’ve invested in over 250 companies around the globe. Find us at our website, everywhere.vc, on LinkedIn, and through our regular founder spotlights on Substack. Be sure to subscribe, and we’ll catch you on the next episode.

Most staffing firms operate on a simple formula. They sit between companies and talent, mark up rates, and make money by adding more billable headcount rather than by improving how work gets done. Pricing is usually opaque, so neither side fully sees who earns what or how much margin sits in the middle. Senior AI-enabled engineers are some of the most difficult and expensive roles to hire and oftentimes, a significant slice of what the client pays never reaches their pockets. Remotely is a platform that helps startups with access to top-tier global engineering talent, seamless hiring, and improved retention. They use a lean, AI‑driven model and transparent pricing. The company charges a fixed monthly fee, and 100% of salary goes to the engineer.

Co-founder Jose de Cabo has been building companies with the same core team for more than 15 years. He and Pau Sabria met at Columbia Business School and moved to New York as first-time founders, where they built and scaled Olapic to a successful exit. After Olapic, they created Clara Partners, a holding company that now houses Remotely, as well as Clara Ventures, a community‑driven VC that supports immigrant founders landing in the U.S. Through that journey, they met their other two Remotely co-founders, Pau Suris and Sebastian Alvarez, who both grew out of earlier roles at Olapic into long-term partnerships. Together, the team brings a long shared history of building, scaling, and shipping products across multiple companies and continents.

They will be hosting a live webinar on Monday, April 20, where they’ll dive deeper into how they are using AI agents at Remotely.

Register Here!

Why Remotely and why now?

When we were building our first company, Olapic, we experienced the pain of scaling high-quality engineering teams in a fast‑growing tech business. We solved the problem by working with exceptional Latin American talent. What stood out was not just talent quality, but also how naturally teams worked together. Shared time zones, clear communication, and strong ownership made collaboration feel easy from day one. For us, it was the difference between hiring people and building a real team. We’re now building to provide a solution at scale with transparency and better alignment for both companies and developers. The timing matters because AI is fundamentally reshaping how work gets done, moving away from headcount-heavy services toward smaller, high-leverage teams powered by software and agents. We’re building Remotely from the ground up for that new reality.

What’s Remotley’s North Star?

Our North Star is using the smallest team possible to run the highest‑quality operation with as much AI and operational leverage as we can. When you strip away the overhead that traditional staffing companies carry, you can pay developers more, charge customers less, and everyone stays longer. We think most of this industry is going to get rebuilt around that idea in the next five years.

How does Remotely inspire “customer love”?

VCs and PEs introduce us to their portfolio companies without us asking. (Many Everywhere portcos already partner with Remotely). Customers refer us without us asking, and that only happens when the experience is good. We have 8,000+ senior developers in our network, so we can move fast. We obsess over developer quality and client fit the same way a product team obsesses over user experience. When a developer isn’t working out or when a customer needs to scale, we move fast. Speed and quality compound over time, and that’s what turns a vendor relationship into a partnership.

The other thing is we don’t have lock-ins. No contracts forcing people to stay. So the bar to keep customers is higher. When they stay for three years and keep growing, that tells you something.

What’s on the horizon for Remotely?

We’re building an advisory board of executives who built and sold massive IT services companies, people who ran multi-billion dollar businesses. When they hear our team size relative to how many developers we manage, they can’t believe it. They see us as the young guys playing with AI, and we see them as people who’ve built at a scale we haven’t reached yet. Bringing those two worlds together is how we build something much bigger than a staffing company. We have the ambition to build the next-gen IT services business.

What makes you a unique founder?

I’ve been through the full cycle: management consulting, founding, scaling, an exit, and now building again from scratch. But the thing that probably makes me different is the immigrant founder lens. My co-founders and I came from Spain and figured out New York as first-time founders. We were lucky it worked. Now through Clara Ventures, we’re helping the next generation of founders from Spain and Latin America do the same thing. We run a WhatsApp community for immigrant founders, help with immigration, make angel investments, and do intros. We used to be the young ones. Now we’re the old guys, soon with grey hair, and that’s actually pretty great.

Fun fact:
My wife and I are both entrepreneurs building our businesses from the mountains in France, while raising five young children.

Listen to Dylan Lew with Scott Hartley, on the Venture Everywhere podcast: Setting the Ecotone. Now on Apple & Spotify. Check out to all our past episodes here!

In episode 114 of Venture Everywhere, Scott Hartley, managing partner at Everywhere Ventures, talks with Dylan Lew, co-founder and CEO of Ecotone Renewables, a company replacing traditional waste hauling with on-site biodigesters that convert commercial food waste into a locally distributed organic fertilizer. Dylan shares how building and operating an early digester that broke down constantly pushed him to rethink the entire food waste system from the ground up. He discusses how Ecotone is rewriting the economics of food waste management, turning what businesses write off as a disposal cost into a revenue stream and a locally sourced fertilizer supply chain.

In this episode, you will hear:

• Using state food waste bans to landfill as a distribution accelerant.

• Building a decentralized grid of on-site digesters over centralized facilities.

• Upcycling commercial food waste into a locally distributed organic fertilizer.

• Expanding from digester hardware to AI-powered waste intelligence with Athena.

• Sequencing a multi-sided business from digester manufacturing to retail fertilizer.

If you liked this episode, please give us a rating wherever you found us. To learn more about our work, visit Everywhere.vc and subscribe to our Founders Everywhere Substack. You can also follow us on YouTube, LinkedIn and Twitter for regular updates and news.

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TRANSCRIPT

00:00:04 VO: Everywhere Podcast Network.

00:00:14 Jenny Fielding: Hi, and welcome to the Everywhere Podcast. We’re a global community of founders and operators who’ve come together to support the next generation of builders. So the premise of the podcast is just that founders interviewing other founders about the trials and tribulations of building a company. Hope you enjoy the episode.

00:00:32 Scott: Hi, everybody. I’m Scott Hartley, co-founder and general partner at Everywhere Ventures. I’m super excited to have here, today, Dylan Lew, who’s normally based in Pittsburgh, Pennsylvania, founder and CEO of Ecotone Renewables.

00:00:46 Scott: Dylan’s working on some really fascinating stuff around food waste management, turning nutrient-rich foods that come off of restaurants primarily into reusable fertilizers and really helping solve the global fertilizer crisis that we’ll talk a little bit about today, pioneering a new method of doing this at scale.

00:01:05 Scott: So Dylan, thank you so much for being with us today on the podcast and we’d love for you to tell a little bit about your background. You guys started Ecotone straight out of college, made all the lists, the 30 Under 30s for people really innovating in circular economy. But maybe walk us through that decision to start Ecotone, the market opportunity that you saw and how you got started.

00:01:26 Dylan: Definitely, and thank you, Scott, for having me on the podcast today as well. I’m the CEO and co-founder here at Ecotone. My background is much more on the technical engineering side. Studied material science and engineering from Carnegie Mellon, got my bachelor’s and master’s there. And then was working for both NASA and GE Renewables, helping them manage their fleet of hardware systems.

00:01:49 Dylan: For GE, was doing failure analysis on their 55,000 operating wind turbines around the world. Every time one of them broke or collapsed, they’d send my team all the broken parts to figure out what went wrong and how we prevent it for the rest of the fleet.

00:02:04 Dylan: Really, really helpful experience as we are also building, deploying, and operating a fleet of hardware systems that are software-enabled. But for us, instead of wind turbines, it’s on-site biodigesters for commercial buildings and kitchens.

00:02:17 Dylan: We did start this while we were still in school, which is a lot to do at the same time. But I do think it was really helpful to have those first three years of the company’s life in this bootstrapping R&D phase.

00:02:31 Dylan: We actually started more as an operator. We asked and we got a custom order for a small scale digester and it was really difficult to operate. The 40-hour a week job was breaking multiple times a week and not actually running well. So we had a few key epiphanies early on.

00:02:49 Dylan: First of all, we think we can build a more reliable system. And the second piece is the automation and really the opportunity that we saw in the market of food waste management and fertilizer, which combined is over a $280 billion global market opportunity.

00:03:06 Dylan: And we saw that there was this gammacing of… you have waste management solutions that are sending all the waste typically to landfill, and you have really expensive fertilizers that are getting shipped from international countries, shipped to the US and to our farmers.

00:03:21 Dylan: There’s no interconnection of that supply chain. That’s where we saw a really interesting opportunity to create what I almost call a vertical integration play in the food waste solution space, where we are doing it all.

00:03:35 Dylan: We manage the food waste, we upcycle it into fertilizer. We actually then distribute that fertilizer to retail stores and farmers directly. That’s where we’re capturing a lot of value across the chain and also then sharing that with our customers and partners along the way.

00:03:50 Dylan: Hopefully that gave you a little bit of context in how we initially started and saw some of the opportunities in this space.

00:03:57 Scott: It’s fascinating because it’s a two-sided problem that we’re all learning about maybe for the first time with the global crisis in the Middle East and the Strait of Hormuz and the choking of global supply chain. Obviously, a lot of natural gas that goes into fertilizer production comes out of the Middle East.

00:04:14 Scott: With the global shipping routes shut down currently, I’ve just been reading about how China has really limited the export of some of the main components in fertilizers, therefore shooting the cost of fertilizer through the roof. Obviously, a lot of farmers buy these on contracts six months in the future.

00:04:31 Scott: Now, fertilizer manufacturers are reneging on those contracts under force majeure, and this stuff is happening simultaneously—not buying corn and pushing the price of crops through the floor.

00:04:42 Scott: So all these global supply chain levers that are moving as a result of conflict shed light on how integrated this global supply chain is. What’s so interesting is you may be taking a step back and talking about this two-sided marketplace where you have huge demand for fertilizer from US farmers and anybody that’s tilling land and cycling crops, contrasted with this urban development dense centers with restaurants with food waste.

00:05:09 Scott: Everybody’s walked their dog through the back alley behind a restaurant and you see the dumpsters and you see the biofuels and the storage of all of the offshoots of urban development in restaurants.

00:05:19 Scott: Tell us a little bit about the ZEUS system and what you guys have built and how you’re integrating that into large restaurant chains. I guess, the first part of the problem is offloading this food waste and how big of a problem is this? And then how you guys are then plugging that into this fertilizer market as you talked about.

00:05:37 Dylan: Very high level. The ZEUS digester is an easier and cheaper way to manage food waste. And it also, especially for businesses in the 11 US states now that have food waste bans to landfill, it helps these businesses meet new compliance requirements.

00:05:52 Dylan: The ZEUS digester is basically a fully automated anaerobic digester. It operates very similar to how our stomachs use. It’s a form of biomimicry. You’re basically using nature’s superpowers, but helping to do that in a condensed and faster way.

00:06:08 Dylan: For us, it is using trillions of different bacteria, fungi, microbes in a stomach tank to basically break down the food waste, turn it into an actual liquid organic fertilizer that we call soil sauce.

00:06:21 Dylan: Right now, our flagship product is the ZEUS digester. It’s an on-site biodigester for commercial kitchens and buildings, not just restaurants. We actually do all commercial kitchens: hotels, hospitals, corporate offices, schools, municipalities as well, are all market verticals that we currently serve today.

00:06:39 Dylan: It’s basically a trash chute on the outside of a shipping container where you dump your food waste in the trash chute, you walk away, and system takes care of the rest.

00:06:49 Dylan: Inside the box is where all of our advanced technology is that processes all of the food waste, produces the fertilizer. We hire local artists that decorate the outside to make sure it really fits in with the local communities where we deploy.

00:07:02 Dylan: The real key is really that automation piece. We’ve developed what’s called the PLC and HMI. Without getting too much into the weeds, it’s the brains of the system that lets us control and monitor these digesters fully remotely, help send our service team as needed.

00:07:19 Dylan: We also have a really advanced data analytics system as well that we’re about to be publicly launching in a few weeks too. Little sneak peek is that’s gonna be called Athena Waste Intelligence. Pairs very well with our Zeus digesters.

00:07:32 Dylan: It’s basically using camera sensors that are taking photos of the food waste, running it through a machine learning and AI program that’s basically tracking and detecting exactly what’s being wasted.

00:07:45 Dylan: These systems are not just upcycling food waste, but they’re also helping to reduce food waste of the source and food purchasing costs, which can be $50,000 to $100,000 a month, especially for some of these larger operations.

00:07:58 Dylan: Today, people have three different vendors to do this. They have a waste management vendor. They have a data analytics vendor. They currently aren’t really doing anything with any byproducts or fertilizers. Our goal is really to provide a really firm key solution that handles everything in one.

00:08:14 Scott: I love the references to Greek mythology. A lot of people are probably familiar with the backyard composters where you collect your banana peels and whatnot. And you maybe throw your food waste into a drum that you mix in sawdust and turn it every once in a while.

00:08:29 Scott: And it emulsifies and turns into a soup that you can then use in your garden. You guys are basically taking that same principle with much more technology, much more analytics, and doing this at scale for large commercial kitchens.

00:08:43 Dylan: Exactly right. What we’ve learned along the way, one of the keys in operations that we’re solving is odor and pest issues, is, especially in the summer months, food waste either sitting in a dumpster for a few days before pickup or in compost collection bins, which is definitely better for the environment, but operationally is still pretty difficult.

00:09:04 Dylan: For a hospital, for example, they cannot have flies going around or odor issues or complaints coming from their dumpsters. Being able to have fully self-contained airtight, watertight tanks, and pipes even within the shipping container really enables the system to actually reduce and eliminate a lot of those pest and odor issues, which are very typical for food waste.

00:09:27 Dylan: There’s this business piece, which we saw first, of making sure we’re reducing waste hauling costs. We’re helping to reduce purchasing costs as well along the way. But there’s also this operational piece of making sure that their operations are easier, cleaner, and faster.

00:09:42 Dylan: For those that are familiar with typical backyard composting, our digesters are basically eight times faster than that process. So instead of multiple months, it’s constant input and output that if you track up a banana peel thrown in to when it comes out as soil sauce, it’s about two or three weeks.

00:09:57 Scott: Wow. It’s amazing. For those of us who’ve may lived 11 years in New York City, we’re very familiar with the summer odor from the dumpsters and food waste.

00:10:06 Dylan: Exactly.

00:10:07 Scott: Maybe talk a little bit about these 11 states that have these requirements of no food waste in landfills. That’s an interesting development where there’s a carrot and a stick and some regulatory compliance aspects. Is this a trend that you’re seeing expand out? Are these 11 states the early leaders and then you see this continuing across the country?

00:10:29 Dylan: Definitely do. There are some states like Pennsylvania where they’re trying to pass similar regulations, but I think is gonna be… a little bit of a long haul to make it happen. There’s some amazing organizations that are really pushing that forward.

00:10:42 Dylan: It’s been interesting to see pretty much every year you see either new states adding these types of regulations or existing states reducing the threshold of who’s included. How they usually roll these out is they’ll have, let’s say, a three or five year rollout plan where they’ll start the regulation of it’s really only large producers.

00:11:01 Dylan: It’s people producing 5 to 10 tons of food waste a week. Those are the only ones that need to find a solution to their food waste that avoid sending it to a landfill. Then they usually stagger it down year over year where then it reduces to one ton a week, half a ton a week, or even less.

00:11:18 Dylan: A good example of that is Washington State actually, who just in January reduced their threshold to anyone producing 500 pounds a week or more. I think they counted it in gallons, but people don’t really understand what gallons typically look like for food waste. So the pounds, I think, is a more helpful metric.

00:11:36 Dylan: But that basically is every food service business. Every restaurant, school, commercial office building, hospital are now legally required to find either compost hauling or an on-site waste management solution like our ZEUS digesters.

00:11:50 Scott: And is that because of greenhouse gas emissions of food waste in landfills like methane? Or do you know what the rationale behind this regulation is?

00:11:59 Dylan: There’s a lot of different reasons that come into play. Honestly, one of the biggest drivers of this is landfills are filling up and starting to get capped. We are losing out on landfill space. There’s not much left in a lot of regions in the country.

00:12:13 Dylan: They’re really trying to make sure we’re intentional of diverting certain waste products out of landfill, trying to extend those lifetimes. Food waste is one of the biggest levers to reducing greenhouse gas emissions globally.

00:12:25 Dylan: For reference, food waste is 8% of global greenhouse gas emissions. That’s just wasted food waste rotting. That’s not even accounting the production and transportation of all the food.

00:12:35 Dylan: Even though people are complaining about Taylor Swift on her jet or all these people flying around, food waste rotting is double the impact of all aviation globally. Just to put that in perspective of the impact that this has.

00:12:48 Dylan: That’s what’s been driving us very early on, to be very excited about solving this problem, is this is really what helps us create global positive climate impact. States are approaching that on a similar perspective of a lot of states have these climate or carbon reduction goals.

00:13:05 Dylan: Reducing food waste into landfills is one of the biggest levers to pull that. It’s also very practical of what they’re doing, again, of whether landfills are filling up. Sometimes a lot of these states and cities are paying really high waste hauling costs to ship these to other states or countries sometimes as well. It’s also a way to actually improve business operations for a lot of facilities.

00:13:27 Dylan: Some states offer some incentives as well to switch over. I’ve seen Austin, Texas has something in place that’s been effective. But it is really helpful to see. We’re never gonna see that at a federal level anytime soon, but states are definitely taking some really practical next steps and options to keep food waste out of landfills.

00:13:45 Scott: It’s a fun action item. Rather than complain about jet traffic to Davos in January, maybe vote for your local compost bill. That’s fascinating. Talking a little bit about both partnerships on the commercial kitchen and restaurant and hospital and school side. I know that you’ve got a really exciting partnership in development with inKind and groups of restaurants.

00:14:08 Scott: Talk a little bit about that on the supply side and then how you guys package and take the soil sauce and then have a bit of a demand side as well, probably from farm communities and groups that want to buy this fertilizer as an alternative, to this heavy reliance on global supply chain and obviously probably more expensive fertilizer that’s less natural.

00:14:30 Dylan: For the digester side of the business, we work directly with a lot of these businesses. So we do just direct outbound campaigns. We’re starting to see a lot more inbound leads as well, which is really exciting to see.

00:14:42 Dylan: At the same time, a lot of my personal time and efforts are really put towards a lot of these more strategic long-term partnerships. So we basically have four or five of those in the works today.

00:14:52 Dylan: And the most up and coming one is with inKind, who is a large financier of restaurants across the country. They help make restaurants and food more affordable for consumers, help restaurants also invest in their own infrastructure and business operations, which is pretty incredible to see.

00:15:08 Dylan: We’ll be launching our fully mobile off-grid ZEUS digester out in Denver, Colorado at the end of this month for multiple restaurants to test the unit out, see if they like it or not before committing to a permanent installation.

00:15:22 Dylan: It’s been interesting. We’ve seen this mobile and off-grid ZEUS digester as a huge unlock for our sales process from start to finish, ‘cause it lets people, again, try a system out, really see if it works the way we say it will.

00:15:36 Dylan: Yes, it really is really easy for your staff to just dump their waste and walk away. And then it makes that decision process a lot easier. So we’ve seen it pretty much cut that sales cycle length in half, which has been pretty incredible.

00:15:49 Dylan: We actually have two different mobile off-grid systems in the work. We have a East Coast one that’s already been touring around the East Coast. Our engineering team is building another one in two weeks. So they’ve been very fast. And that’s gonna be the one that’s going out to Denver, Colorado, and then staying out on the West Coast throughout the end of the year.

00:16:09 Dylan: So that’s been really exciting to see that we’ve seen this coast-to-the-coast expansion that honestly follows some of those state regulations and high waste hauling bills, which go hand in hand. So we see the California, Denver, Colorado, Pacific Northwest has really high waste hauling fees. They also have these existing food waste bans to landfill. Same with the Northeast US. That’s been our two main expansion areas.

00:16:34 Dylan: For this soil sauce, it’s been really interesting to see. So, we’ve done very extensive field trials with this at this point, just to see how does this compare to synthetic fertilizers on the market.

00:16:45 Dylan: If anyone’s familiar with a compost tea, it’s a very concentrated version of that. Very low macronutrients, very high micronutrients, available carbon metabolites. We’re still trying to figure out what makes it work so well, ‘cause with these field trials, we basically saw 14 to 22% yield improvements compared to not using it on corn, soy, and potatoes so the major staple crops.

00:17:08 Dylan Our fertilizer expert… I think his theory is that it really is the available carbon and the metabolites, ‘cause it’s a very different approach to supplying nutrients and microbes to the soil and plants than is typically done.

00:17:22 Dylan: So most farmers and commercial ag, you basically dump nitrogen on the soil very intentionally. They map it all out. It’s all in terms of pounds per acre. But the plants are uptaking all that.

00:17:34 Dylan: So that’s where we also see a lot of issues of nitrogen leaching into our waterways. That’s where we get these toxic algae blooms, whether that’s local or regional. In the Gulf, we see that pretty often as well. There’s a lot of issues right now happening, just the fertilizer industry.

00:17:48 Dylan: And as you said, fertilizer prices have spiked 25% in the past two weeks. 40% of the world’s sulfur goes through the Strait as well. So we’ve seen those prices pretty much double, too. That’s where you see in the fertilizer space, this whole issue of international supply chains that are very volatile that if anything goes wrong, those prices completely destabilize.

00:18:13 Dylan: At the same time, the actual use case of these products isn’t actually the best way to be providing nutrients to the plants. That’s where we’ve seen a very unique opportunity with soil sauce where we can be a really low-cost fertilizer that’s saving farmers money compared to synthetic fertilizers.

00:18:29 Dylan: We’re also then not dumping nitrogen on the soil. So you’re actually reducing a lot of that water runoff issues. And at the same time it’s produced locally, so you’re not worried about shipping this from Russia or Ukraine or China. It’s produced at your neighborhood restaurant or from the hospital down the street.

00:18:46 Dylan: That’s really where we’ve seen really stable and reliable hyper local supply chains that we’re creating. We create these mini hubs in our operating regions. So yes, we work with local farmers and community gardens that use the soil sauce directly.

00:19:01 Dylan: It’s been interesting. We’ve actually seen a ton of traction and interest on the retail side. We actually just launched in 24 Giant Eagle store locations. These are large grocery stores in Pennsylvania, Ohio, Indiana region.

00:19:15 Dylan: Last month, they just expanded to add another dozen stores. Focused on their highest performing stores first, then planning to roll out to all 200 grocery stores pretty much by the end of this month.

00:19:27 Dylan: That’s been super exciting to see that the retail space has actually seen a ton of commercial growth. That’s for house plants and gardens for people to have a very easy to use sustainable fertilizer.

00:19:39 Scott: I need that for my own 20 plants that I have.

00:19:41 Dylan: I love it.

00:19:43 Scott: I’m always taking my coffee grinds and various things and Googling what would be a good addition to the soil. Obviously, enough finite plants that then uses all the nutrients in the dirt and you got to refresh it from time to time.

00:19:55 Scott: We have an LP, a good friend of mine, founder of a company called Farmers Business Network based in Omaha, Nebraska we should connect to you with, because they’re basically providing all the raw supply materials for commercial ag in the form of three or four hundred million dollars a year of sales, fertilizers, all these things.

00:20:14 Scott: I think what a lot of people don’t recognize in the commercial ag space is the planning that goes into each harvest and the six to nine months before that you’re buying features or you’re basically investing in fertilizer.

00:20:27 Scott: To your point, these supply chains are insanely long. Prices can move dramatically. And that in addition to the weather and the yield of the crops and the price per bushel of corn, all of these things come in tandem and determine if you have a great year or a not so great year.

00:21:43 Dylan: And it really all comes down to input costs and what you can sell your product at. The yield improvements really help bridge some of those gaps. But I think exactly as you said towards the beginning of this is that’s where a lot of farmers today are getting pressures of increased costs on inputs and actually pretty stable costs on the actual crops themselves. So they’re not really able to bridge the gap between those two.

00:21:07 Scott: Taking a step back just as a founder building a relatively complex business in the form of hardware, material science, selling into ag, maybe walk us through just the genesis of the business and obviously coming straight out of school, what have been the biggest challenges.

00:21:25 Scott: And obviously we invested three years ago, you’re probably more than four year in. What’s been some of the surprises that you’ve encountered over these last four years?

00:21:34 Dylan: It’s a lot to take on in one company. And it’s been a super exciting and interesting challenge. That’s probably the biggest challenge on its own is just the complexity of the market and the business and trying to figure out all these moving parts.

0021:48 Dylan: What we have found personally to be super helpful is the sequencing of all this. We don’t have to figure it out right away. There’s certain pieces of the business and milestones along the way that we have to hit.

00:22:00 Dylan: And we use OKRs, so just objectives and key results to really be very clear on what we are going to get done every year. And then we have a endlessly growing backlog of things that are of interest at some point we want to tackle, but intentionally postpone and put down. So that, instead of dropping the ball on certain things, we’re intentionally placing that down and pick that up at a later date that’s needed.

00:22:22 Dylan: For us specifically, how that looked is really focusing on the digesters first. It’s making sure that we’re building a reliable system, building a sales process that can scale and is repeatable so that you start to build a supply for the soil sauce.

00:22:37 Dylan: Right now we’re at that inflection point where we’ve really built that repeatable manufacturing, deployment, and sales process for the systems. We’re starting to see a lot more traction on the soil sauce side. Definitely taking some advantage of that and starting to really invest some time and effort and resourcing to making sure that that part of the business is successful.

00:22:56 Dylan: But I think, biggest challenge overall is trying to take on a lot all at once. And we also do all of our own manufacturing in a house. That’s how we have really tight control over quality of our products and services.

00:23:09 Dylan: Something that I always keep a very close eye on is really matching pace our production schedule with our sales schedule. Making sure that we ramp both up in tandem together, that’s definitely a big challenge to try figuring out.

00:23:21 Dylan: But I think over the years, we’ve really gotten into a good pace and intuition on when we need to push the levers and the buttons with additional manufacturing technicians or sales reps. At this point, we also know metrics and outputs of what we get from those investments at a company level.

00:23:38 Scott: If you were to look out five, ten years, I imagine becoming the de facto natural fertilizer brands in the form of… say, a Miracle-Gro that’s derived from food waste, from urban kitchens. Do you have the north star of where you think you’d like to take the business?

00:23:56 Dylan: Overall business goal is global climate impact and world domination of food waste solutions. It’s really true. Today we’re focused on the US market, but we’re even starting to see a lot of international business opportunities.

00:24:10 Dylan: We started working with Compass Group Canada. Compass Group is one of the biggest food service providers in the world. They have 50,000 locations that they service. I think over that at this point. That’s where we’ve seen a ton of opportunities, not just in the US, but globally too.

00:24:25 Dylan: I think a really great example is Island Nations in the Caribbean and in the Pacific as well, where right now they pay not just a truck to pick up their waste, but a boat. It’s immense cost to haul waste outside.

00:24:39 Dylan: They also are seeing a big resurgence in really trying to reclaim a lot of native recipes and local crops and trying to rebuild their food systems because a lot of these populations have basically been relying on international exports for actual food.

00:24:57 Dylan: 90% of a lot of these islands are imported food rather than stuff that’s grown locally. That’s a really good example of areas where we see long-term, where we can be providing a lot of value tapping into these existing problems and potential solutions of very high waste falling costs and really a strong desire to improve local soil health and the food system resilience as well. That’s the big picture for the company.

00:25:24 Dylan: For the different product lines as well, for the digesters, we definitely do see additional product SKUs coming out. Right now, it’s a single one-size-fits-all ZUES digester, but whether it’s smaller systems, larger ones, ones that fit inside the building is what our team is currently working on.

00:25:40 Dylan: We actually are about to deploy a system for the new Theodore Roosevelt Presidential Library opening up July 4th. So this will be our first inside the building digester, which is a brand new capability, especially for hotels, restaurants, places, offices that don’t have room outside of the building to actually have an inside the building solution.

00:26:01 Dylan: And for the soil sauce, pretty similarly as well. Right now, it’s a single brand of soil sauce and type of it, but most fertilizers have a blooming version, a flowering version, a growth stage for the plant fibers, which is basically just different MPK ratios.

00:26:18 Dylan: Additional products SKUs, international distribution as well of soil sauce too, but again, produced locally. That’s the whole point of our distributed grid of these digesters is you don’t need to ship it, the soil sauce, to a farmer across the world or a country. You actually have a local production hub that you can tap into.

00:26:38 Scott: Not only that, but you have a beautiful ZEUS machine that’s painted with local graffiti and local artists. Which I absolutely love what you’ve done in Pittsburgh to really ensconce them into the urban fiber and actually improve neighborhoods and communities with what would otherwise look like an ugly dumpster.

00:26:55 Scott: One of my last questions, I had the chance to have lunch many, many years ago with the founder of Allbirds, the shoes. And what he said is that people on the front end say, I wanna buy these shoes because they’re sustainable business and they’re coming from New Zealand sheep fibers and recycled plastics. But when we actually hold people at the point of sale, the real drivers of purchase behavior are they look cute and they’re affordable.

00:27:20 Scott: A lot of businesses may have the broad desire to do better for the world and save food waste, but probably the brass tacks that comes down to the economics of the carrot and the stick of there’s either regulatory compliance that they have to stick with or the cost of getting rid of that food waste is astronomical.

00:27:39 Scott: How do you guys think of the unit economics of installing these systems, maybe the revenue share around the production of soil sauce on the back end and basically turning this from a cost center of a business into maybe a revenue driver?

00:27:53 Dylan: You’ve hit the nail on the head of this is exactly the flipping of the script that we’re doing today. Most people see food waste as waste. They see it as a cost center. All they do is pay to have it all the way and that’s it. That’s exactly what we’re actively doing today: is turning that into an income and revenue driver for their business.

00:28:12 Dylan: What that does on a unit basis for our partners is increases, provides a little bit of revenue from the soil sauce, we collect and resell that they don’t need to do anything. They’re also reducing their waste hauling bills.

00:28:24 Dylan: So we’re usually saving businesses at least a few thousand dollars a year net, which is really exciting to see that… yes, this is a great solution for the environment and it’s easy to use, but the main driver, exactly as you said, is making sure this makes financial sense for their bottom line, which we’ve been able to prove out. That’s really the big unlock for us is making sure that’s really what helps us scale globally.

00:28:47 Dylan: One of the biggest things that we figured out pretty early on in the company’s development is equipment financing to help with that. We actually finance these digesters for our customers. We work directly with a bank subsidiary that does equipment financing.

00:29:01 Dylan: What that does is it basically turns what is usually an equipment purchase or capex expense into just an ongoing operating expense, which is immediately offset from reduction in waste hauling bills. There isn’t some 24, 36-month ROI. It’s immediate cost savings as soon as you switch over to ZEUS digester.

00:29:21 Scott: Amazing. My last question for you, and this is something that we think a lot about, is not being contrarian for contrarian sake, but predicting where you think future consensus is going and building something that skates ahead of where market trends are.

00:29:35 Scott: Everybody has frameworks that generally lag based on heuristics of past things that have happened. As an entrepreneur, it’s really your job to think about the future, think about where the world is going and make a bet that is something that you have to stick with for many years.

00:29:51 Scott: The question is: within the industry, within the expert pundits of this domain, what’s something that you guys took an approach that was different or fundamentally at odds with, or these folks would disagree with, “Hey, this is not going to work. You guys are never going to be successful.”

00:30:07 Scott: But you guys drew the line in the sand and you said, “We’re going to do it anyway.” ‘Cause I think a lot of great businesses like yours, it takes a high conviction founder, the blend of both stubbornness to continue to go in a certain direction.

00:30:19 Dylan: Very stubborn indeed.

00:30:21 Scott: And the ability to listen to feedback. It’s always that dance of humility and grit and perseverance. But what’s one major maybe industry norm that you guys have gone against or disagreed with that you think that you’re right and the rest of the market is wrong.

00:30:37 Dylan: I think the main one is this concept of centralized versus decentralized waste processing. I don’t think the market is necessarily right or wrong. Ultimately, we need both.

00:30:47 Dylan: But I think this idea of on-site decentralized waste processing systems just isn’t out there. It just doesn’t exist. The only thing we have today are these large centralized landfills, large centralized composting, or anaerobic digestion facilities. Those exist already.

00:31:04 Dylan: But they’re $50 million at a minimum to build. They take 5 to 10 years to get permitting, financing, actually constructing, get it operating. That’s where we maybe do agree with market consensus is there is a really large lack in waste processing infrastructure, specifically for food waste.

00:31:23 Dylan: We know we only have a limited amount of time to make impact for greenhouse gas reduction, also to divert food waste from landfills to keep those operating and make sure they don’t fill up. And so I think that’s where we’ve seen a very unique opportunity in the market of moving quickly.

00:31:40 Dylan: That’s why our bet is on-site solutions. That’s really where we disagree. Yes, sometimes you have to haul it. You don’t have any room. That’s the only option and that works well. And that’s why we still need these large centralized facilities. But a lot of the time, it’s actually better, cheaper, and more reliable to have an on-site digester solution.

00:32:00 Dylan: For us, it’s digesters. You can pick other options or technologies if you want to. But I think this idea of a decentralized grid of these systems is very unique. We’ve started to show people it actually does work.

00:32:12 Dylan: We had all these huge snow storms and power outages over the winter and we’re operating. We are not waiting for a truck to get through the snow and for the driveway or road to get plowed. For an operating business, that’s difficult. They can’t deal with mountains of food waste just sitting there waiting.

00:32:30 Dylan: That’s where we’ve started to show the market that by being on site, by being decentralized, it’s actually a superpower in reliability, is you never need to worry about missed pickups or refused pickups or something going wrong. It’s 24/7/365. You dump your food waste in the trash chute.

00:32:49 Dylan: That’s been exciting to see that it’s starting to work in this space. I think there’s other models and industries where they’ve done this as well. But I think for waste specifically, that really hasn’t been done before. It has always been these large centralized facilities.

00:33:02 Dylan: The financing and construction piece, it also is a permitting benefit. By being on site, you’re actually typically falling under permit by rule exemptions for states. We’re deploying these systems. I think our last system deployment was two weeks from contract signed, to system on site operating and processing their food waste.

00:33:22 Dylan: Because as soon as you start hauling food waste from one facility to another or to one centralized facility, that’s where you need these like large state permits. They’re not super expensive, but they take a while. And again, that’s the thing we don’t have time for. We don’t have time to sit around and wait for permit approvals.

00:33:37 Dylan: And so I think that’s where… initially that was a pretty large bet that the market disagreed with. We started to show that it works well and it actually enables us to scale a lot faster than a lot of other options out there on the market.

00:33:51 Dylan: My perspective is we need both. You need to build more of these centralized facilities. That’s what gets you huge capacity improvements, but we also need these smaller and faster solutions to fill in gaps in the meantime.

00:34:04 Scott: I love that. That’s such a well way of articulating agreement with just the broad gap in the market and the supply for these facilities, but then the contrarian bet to build out a more decentralized way of handling food waste.

00:34:18 Scott: In the quick lightning round that we have to wrap up the podcast, we got a couple of questions for you. What’s a book that you’re currently reading or a podcast that you’re enjoying?

00:34:28 Dylan: Oh, I think a book that I recently read and I’m due to reread soon, very opinionated as you can tell by the title is called, The Man That Broke Capitalism. It’s about the former CEO of GE and his approach of just prioritize shareholder returns above everything, above employees, above staff, the environment, the communities that you serve. It shows the results of it, of what happens when you build that system.

00:34:57 Dylan: I’m personally very interested by that. We actually founded Ecotone as a public benefit corporation. So we have a triple bottom line of positive investor returns and very strong revenue growth, but also positive social and environmental impact as well. So that’s been I think one of the most interesting reads most recently. That was from our IP attorney who’s a former GE engineer as well.

00:35:20 Scott: Amazing. If you could live anywhere, I know you’re in Florida currently and otherwise in Pittsburgh, what would be on your number one place to live?

00:35:30 Dylan: Oh, that’s a tough question. I feel like at least if we’re talking about a year or two, maybe not indefinitely. Long-term, I have to be close to family. So that’s the Northeast, New York area.

00:5:41 Dylan: But short term, I’d maybe say Spain. I’ve been studying Spanish for a while. I’ve always wanted to live in a Spanish speaking country. So I think that would be one, maybe for more personal reasons that I’d be very interested in.

00:35:55 Dylan: Half my family actually lives in Australia, but I think that’s a little too far away and my mom and dad would not be very happy if I was completely on the other side of the world.

00:36:06 Scott: And finally, what’s your favorite productivity hack as a busy CEO traveling, building a complex business? You have any secrets for us out here?

00:36:15 Dylan: Not like a super complex one. It’s really just time blocking is mine. One of my friends taught me maybe four years ago or so at this point. It’s just been a huge unlock for my productivity.

00:36:27 Dylan: Especially as a founder, as a CEO and executive, you get pulled in a lot of directions. Brain switching from sales to manufacturing to engineering to operations has a bit of a toll. So I think the time blocking helps reduce that.

00:36:42 Dylan: You can combine or have half a day that’s just sales or just engineering or just operations, switches that at task switching lag. It also really is just a way to live through your prioritization.

00:36:55 Dylan: We all talk about brutal prioritization of what is urgent and important and needs to get done now. I found that as one of the most effective ways to make sure that I’m blocking off time to complete the things that are both urgent and important. And again, intentionally postpone things that might not be.

00:37:12 Scott: Amazing. Dylan, thank you so much for being on the podcast today. Where can listeners find you if they want to reach out or learn more about Ecotone?

00:37:21 Dylan: We’re on all socials at Ecotone Renew and our website is ecotonerenewables.com. Has a ton of information on our digesters for specific business types on soil sauce. You can order soil sauce right there as well if you want. You can also learn a little bit more about the company and mission as well there.

00:37:40 Scott: Amazing. I’m gonna pick up my soil sauce today.

00:37:42 Dylan: I love it.

00:37:43 Scott: Thank you so much and we’ll talk to you soon.

00:37:46 Dylan: Thank you so much for having me, Scott. Appreciate it.

00:37:50 Scott Hartley: Thanks for joining us and hope you enjoyed today’s episode. For those of you listening, you might also be interested to learn more about Everywhere, where a first-check pre-seed fund that does exactly that invests everywhere. We’re a community of 500 founders and operators, and we’ve invested in over 250 companies around the globe. Find us at our website, everywhere.vc, on LinkedIn, and through our regular founder spotlights on Substack. Be sure to subscribe, and we’ll catch you on the next episode.

Read more from Dylan Lew in Founders Everywhere.

Managing seized assets is a complex and often overlooked part of law enforcement and financial crime. Asset Reality is focused on solving that problem by bringing structure and transparency to how these assets are handled.

In a recent Techstars profile, Aidan Larkin, founder and CEO of Asset Reality, shared how the company is addressing inefficiencies in the seizure and recovery process. Governments and agencies frequently deal with a wide range of assets, from physical goods to digital currencies, yet the systems used to manage them are often fragmented and manual.

Asset Reality’s platform is designed to centralize and streamline these workflows. By providing a unified system, it enables agencies to track, manage, and ultimately recover value from seized assets in a more organized and efficient way.

Larkin’s background in law enforcement shaped the company’s direction. Having experienced the challenges firsthand, he built Asset Reality to address gaps in visibility, coordination, and accountability across asset management processes.

The need for this type of infrastructure is growing. As financial crime becomes more sophisticated and digital assets become more common, agencies require tools that can keep pace with the evolving landscape. Managing cryptocurrencies, in particular, introduces new layers of complexity that traditional systems were not designed to handle.

Asset Reality is positioning itself at the intersection of technology and law enforcement, helping agencies modernize how they approach asset recovery. By improving processes and increasing transparency, the platform supports better outcomes for governments and the communities they serve.

The Techstars profile highlights a broader shift toward digitizing critical but underdeveloped areas of public sector operations. Companies like Asset Reality are bringing modern software solutions to spaces that have historically relied on outdated systems.

For Larkin and his team, the mission is clear. By making asset management more efficient and accessible, they are helping unlock value that might otherwise remain lost within complex legal and operational processes.

Read the full article on Techstars

Startups are often encouraged to move quickly from one fundraising milestone to the next. Each round is seen as validation, momentum, and progress. But moving too fast can create pressure that compounds over time, especially when valuation begins to outpace traction.

Scott Hartley outlines how this dynamic often leads to one of the most difficult outcomes in venture: the down round. When companies raise ahead of their metrics, expectations increase faster than the business can support. Eventually, that gap has to close, and when it does, it can result in dilution, complex terms, and strained investor relationships.

The article introduces what it calls the “Billy Madison approach” to fundraising. The idea challenges the conventional push to advance as quickly as possible. Instead, it suggests that founders should remain in their current stage longer, using that time to mature, and build strength before moving up.

The concept draws from the idea of “staying back a grade” to become the strongest in the class, rather than the precocious student skipping grades. In startup terms, this means continuing to operate at Pre-Seed or Seed while outperforming the expectations tied to that stage. Rather than stretching to meet the demands of a higher round, companies position themselves as leaders within their cohort.

This creates both strategic and practical advantages. Companies that exceed expectations and key metrics at their stage often have stronger leverage when they do raise. They are able to negotiate better terms and avoid unnecessary complexity that can come with larger, premature rounds.

The piece also emphasizes the importance of optics. Even small differences in raise size and stage name can shift how a company is perceived. A round that moves slightly beyond typical Seed levels can bring Series A expectations, changing how performance is evaluated. Managing that boundary carefully allows founders to control both narrative and trajectory.

Beyond optics, the approach reinforces fundamentals. Taking more time at the current stage allows founders to refine product, build a repeatable sales motion, define customer base, and develop a clear understanding of unit economics. These elements become critical as companies scale and face higher expectations in later rounds.

The takeaway is not to avoid raising capital, but to align fundraising with readiness. Growth should be supported by traction, not just ambition. By pacing rounds thoughtfully, startups can build stronger foundations and move forward with greater confidence when the time comes.

Read more on Scott Hartley’s Substack.

As &you expanded across markets, its financial infrastructure began to show strain. What started as a fast-growing healthcare platform quickly ran into the realities of operating across borders.

Opening bank accounts took months. International transaction fees cut into margins. Spending across entities was fragmented across tools that were not designed to work together. As the business scaled, finance became a bottleneck.

Led by Emil Eriksen, &you set out to solve this by rethinking how its financial operations were structured. The goal was not just efficiency, but building a system that could support growth across multiple markets without added complexity.

By adopting Airwallex, &you consolidated accounts, payouts, cards, and spend management into a single platform. The shift allowed the company to operate with a more unified and scalable financial layer.

The impact was immediate. Account setup timelines dropped from months to just 48 hours. International transaction costs were reduced by 80 percent. Card spend became more efficient, with measurable savings at scale.

For Emil and the team, the difference was not just operational. It changed how the company approached expansion. Finance moved from being a constraint to becoming an enabler of growth.

The broader takeaway reflects a common challenge for startups operating across borders. As companies scale internationally, fragmented financial systems can slow progress. Infrastructure that is designed for global operations from the start becomes a competitive advantage.

For &you, aligning its financial stack with its growth ambitions has created a more durable foundation. As the company continues to expand access to healthcare for Filipinos and beyond, the systems supporting it are now built to scale alongside it.

Learn more at Airwallex

Making data make sense is one of the biggest challenges in modern finance. Financial institutions process millions of transactions every day, from card swipes and online checkouts to recurring subscriptions and bank transfers. But much of that data is messy, inconsistent, and difficult to use. Spade brings clarity to that complexity by enriching transaction data in real time by adding structure, accuracy, and intelligence at every layer. Spade helps banks and fintechs better understand transactions, reduce fraud, and deliver smarter customer experiences. They recently raised a $40 million Series B to deliver a full data and AI platform for payments intelligence, expand the team and meet growing demand from financial institutions and fintechs that rely on Spade’s foundational enhanced transaction data to power AI initiatives. They are currently hiring, so check out their careers page if you want to join the team building the platform that will define the future of finance.

Co-founder and COO Tess Bloch, brings a deep operational background in fintech. Her path into the industry began early, when she cold-emailed Venmo as a college freshman and landed an internship at the fast-growing payments company. She even took time off from school to work there full-time, an experience that laid the foundation of her career in financial technology. After graduating, she joined McKinsey, where she focused on payments, followed by a brief stint in politics, before moving to Pinwheel and helping scale the team from 10 to 100. It was there that a mentor introduced her to co-founder and CEO Oban MacTavish, who was solving a problem she’d seen throughout her career: poor-quality transaction data slowing innovation. Tess took on her first founding role and helped create the team that now enriches billions of transactions each month for category-defining fintechs and Fortune 500 banks.

What’s Spade’s North Star?

Our North Star is to become the default intelligence layer for transaction data. We have two core pieces: our best-in-class merchant metadata layer and our data and AI platform, which helps financial institutions use that data across use cases like AI, analytics, authorization decisioning, and user experience. Ultimately, every financial institution and fintech that touches transaction data should rely on Spade as foundational infrastructure.

Tell us about a recent milestone that Spade crushed.

We recently closed our $40 million Series B, led by Oak HC/FT, with Andreessen Horowitz, Flourish Ventures, Gradient Ventures, NA Ventures, and Y Combinator participating. Leading up to that, we saw 470% year-over-year growth and reached 1.9 billion transactions processed daily, so it’s been a period of pretty massive scale.

What’s on the horizon for Spade?

We’re focused on expanding beyond transaction enrichment into a full data and AI platform for payments intelligence. AI-driven processes are the direction the industry is moving in, but those systems are only as good as the data underneath them, so I think Spade is going to become the default data and intelligence layer that makes that transition possible. It’s really the first step for every financial institution on an AI journey. We’re growing fast and looking to double our headcount this year. We’re hiring across the board so check out our careers page!

How has your background influenced your approach to building Spade?

I come from an operator background, so I never expected to become a founder. I used to associate founders with a “win at all costs” mindset that glorified burnout and a 9-9-6 culture, which never aligned with how I wanted to lead. That perspective has shaped me deeply: I believe empathy is a competitive advantage, and it informs how I hire, make decisions, and build our culture. I don’t believe in compromising on values to hit numbers. I feel incredibly lucky to be building the kind of company I always wanted to see: one rooted in care, ambition, and sustainability, alongside people I deeply respect and want to keep growing with.

Any favorite books?

I love The Field Guide to Global Payments by Sophia Goldberg. She’s another fintech founder and she’s amazing. We give it to all new team members, so I definitely want to plug that.

Fun fact:
I worked as a field organizer in Iowa on Elizabeth Warren’s presidential campaign in 2019. It was the hardest job I’ve ever had, and it gave me a firsthand perspective on what it’s like to live in places where access to healthcare, banks, and financial resources is more limited.

From the archives! Listen to Venture Everywhere podcast episode 12: Radicle Proof in the Pudding on Apple Podcasts and Spotify, and explore all our past episodes here!

Betting on Non-Consensus, and Finding Mis-Priced Assets

One of the tensions every venture capital manager feels is:

1. How do I remain disciplined to my thesis and entry price?

2. How do I not miss truly asymmetric venture-scale outliers?

I always say in the short run discipline matters, but in the long run your job as a venture capitalist is provide accretive capital to unseen opportunities that pre-date market consensus, and that in turn, will afford you outlier performance and make your limited partners money. Asymmetries in returns come from two things:

1. Finding consensus before the market

2. Harvesting under-priced assets, where price < intrinsic value

One empirical observation we’ve had at Everywhere Ventures over the last 8 years, and I saw during my prior 7 years investing at Mohr Davidow Ventures and founding Two Culture Capital, was that our biggest outliers were always “in the tails.” They were in the periphery of what we said that we did. “We don’t do consumer,” but we were the first check into Pair Eyewear, which has gone up 100x since we invested. “Markets like Algeria are too small,” but we returned 100x on Yassir when it became the Super App of Francophone Africa, and the Maghreb. “Hardware is hard,” but we saw Umbra build Synthetic Aperture Radar (SAR) satellites and catapult to a billion dollar valuation and massive profitability. “Data centers in space is a crazy idea,” but as cost per kilogram continues to fall with SpaceX, Benchmark validated our early bet by marking up that position 100x and turning Starcloud into a unicorn in 17 months, the fastest ever in Y-Combinator history.

Part of investing in the tails is that firms operate on conviction. Generally to do something truly out of the box, one partner on the team has to feel it viscerally, be unable to sleep, keep bringing up the idea at partner meetings until the rest of the team eye rolls and says “ok fine, if you love it so much you should just do it!”

Every deal requires a “burden of proof” to get done. Diligence. Calls with customers. Reference checks on the team, the cap table, the co-investors. But when one partner is going farther out into the tail, that burden of proof has to go up. You have to prove with unreasonable conviction that you want to make the investment anyway. Despite convention, despite disagreement, despite consensus opposition. Great deals are not lukewarm, they are polarizing. And if you’re an entrepreneur and some people don’t absolutely hate your idea, or think you’re crazy, you’re not swinging big enough.

The second truth today is that venture capital is no longer a cottage industry like it was when I was a kid in Palo Alto, when soccer dads played with Palm Pilots and talked about personal computing and the rise of DotCom opportunities. Back then there were 20 firms on the map, and there was not a glut of capital chasing the same opportunities. The frontier of the “tail” moves. The Internet was a tail bet in the mid 1990s. The social web was a tail bet in the mid aughts. SaaS was a tail bet in the early teens. Web3 was a tail bet in the late teens. Perhaps space or Cis-Lunar economy is a tail bet today.

What’s clear is that frameworks lag reality, as I’ve written about before. Heuristics of what worked last year are most certainly NOT what will work this year. Part of this means that a glut of capital is chasing a lagging consensus, and therefore any potential alpha is “priced in.” When I called my friend Clay Bavor when he started Sierra AI, he said “sure write a check, but Sequoia’s doing it at a billion.” Clay and Bret Taylor are exceptional, and Sequoia was already pricing in value at a billion. There is still certainly alpha in that company, as it’s a rising AI juggernaut, but that’s not the game we play at Everywhere Ventures. We’re primarily investing outside the Valley, and looking for asymmetries in the tails, and mis-priced assets, where there are undiscovered, yet exceptional founders, who have a mismatch of price to value.

In a consensus deal value is priced in. In the example above, the price may be nine, but the value is ten. The value capture to the investor is one. Outside of key industries, in first-time rounders, and in remote geographies, the delta between price and value is higher. In non-consensus deals (for the above reasons) price may be four when value can still be ten. This delta of six is the potential non-consensus upside, the alpha.

At Everywhere Ventures we ourselves are a non-consensus firm. We’re bicoastal, we’re very early pre-seed, we primarily invest outside of the Bay Area gold rush. But what we believe is that our network of 1,000 founders as LPs and portfolio CEOs give us unfair access into these tails via compounding network effects in venture capital. And because we constantly evaluate “where the tail is,” whether sector, geography, or founder archetype, we’re focused on finding these mis-priced assets in the market. We write three times more checks than firms our size, and we return capital. We’ve charted to the top decile every fund, every cohort, every year for the last decade.

Venture capital is an evolving game, but the lessons above hold true. Always.