BUILDERS

How Collate turned 12,000 open source users into an inbound sales engine | Suresh Srinivas

Collate is building a semantic intelligence platform that unifies fragmented metadata tooling across the modern data stack. With 12,000+ community members, 3,000+ open source deployments, and 400+ code contributors, the company has proven that open source can be a systematic GTM engine, not just a distribution tactic. In this episode of BUILDERS, I sat down with Suresh Srinivas, Co-Founder & CEO of Collate, to explore his journey from the Hadoop core team at Yahoo, through founding Hortonworks, to architecting data systems processing 4 trillion events daily at Uber—and why that experience led him to rebuild metadata infrastructure from scratch.
Topics Discussed:
Why platform builders at Yahoo and Hortonworks struggled to drive business value despite powerful technology
The metadata fragmentation problem: how siloed tools lack unified vocabularies and end-to-end context
Collate's contrarian decision to build Open Metadata from zero rather than spinning out Uber's internal tooling
Engineering an open core GTM model that generates nearly 100% inbound sales from technical practitioners
Scaling community contribution: moving from feedback loops to 400+ code contributors
Hiring a CMO to translate technical value into business-leader messaging without losing practitioner trust
The convergence thesis: structured data, knowledge graphs, and semantic layers as the foundation for reliable AI
GTM Lessons For B2B Founders:
Architect your open source for GTM leverage, not just distribution: Suresh built Open Metadata as a unified platform consolidating data discovery, observability, and governance—previously fragmented across multiple tools. This architectural decision created natural upgrade paths to Collate's managed offering. The lesson: open source architecture should solve a complete job-to-be-done that reveals commercial value through usage, not just demonstrate technical capability.
100+ daily practitioner conversations beats any user research: Collate maintains ongoing dialogue with their community across Snowflake, Databricks, and other integrations. Suresh called this "a product manager's dream"—immediate feedback on what breaks, what's missing, and what workflow improvements matter. For infrastructure startups, this beat rate of validated learning is nearly impossible to replicate through traditional customer development.
High-velocity releases build credibility faster than pedigree: Starting from scratch without Yahoo or Uber's brand meant proving commitment through shipping cadence. Collate's strategy: demonstrate you'll be around and responsive before asking for production deployments. This matters more in open source than closed-source where sales cycles force commitment conversations earlier.
Separate technical-buyer and business-buyer GTM motions explicitly: Collate's founding team spoke fluently to data engineers and architects who lived the metadata problem daily. Their CMO hire (after establishing product-market fit) brought expertise in articulating business impact—ROI on data initiatives, compliance risk reduction, AI readiness—without the founders faking business-speak. The timing matters: hire for the motion you're entering, not the one you're in.
Play the long game with builder-culture companies: At Uber, internal tools were 2-3 years ahead of vendor solutions but became technical debt as teams moved to new problems. Suresh's advice: "Keep in touch with these larger companies. Your technology will improve and you will have better conversation with larger technical companies." The wedge is timing—catch them when maintenance burden outweighs building pride, typically 24-36 months post-launch.
Design for all company scales from day one: Unlike Uber's internal metadata platform built for massive scale with corresponding complexity, Open Metadata works for small teams through enterprises. This wasn't just good design—it was GTM expansion strategy. Building only for scale locks you into enterprise-only sales. Building only for simplicity caps your ACV. The middle path requires architectural discipline upfront.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How WindBorne Systems landed their first Air Force contract through Defense Innovation Unit | John Dean

WindBorne Systems is transforming global weather forecasting by deploying long-duration weather balloons that fly for weeks instead of hours. What began as a Stanford Student Space Initiative project has scaled to 100 balloons aloft simultaneously, targeting 500 by end of next year, with an end goal of 10,000 balloons monitoring Earth's atmosphere. In this episode of BUILDERS, I sat down with John Dean, Co-Founder and CEO of WindBorne Systems, to explore how the company secured its first government contract in under three years without lobbyists, achieved 4x annual manufacturing growth, and built Weather Mesh—an AI weather model that outperforms competitors from Google DeepMind.
Topics Discussed:
The technical evolution from Stanford project to operational constellation of altitude-controlled balloons
Strategic decision to pursue government revenue before building B2B forecasting products
Navigating Defense Innovation Unit and Air Force Lifecycle Management Center procurement as a founder
Timeline from founding to first grants (within six months) and first data delivery contract (two and a half years)
Current roughly 50/50 revenue split between civilian agencies (NOAA, international weather services) and Department of Defense
Building Weather Mesh after Huawei's Pangu Weather validated end-to-end AI forecasting viability
Transitioning from founder-led sales by promoting a Palantir hire from proposal writer to public sector growth leader
The 30-year vision of millions of fingernail-sized atmospheric sensors creating a planetary nervous system
GTM Lessons For B2B Founders:
Study the bureaucracy's incentive structures before pitching product value: John spent years mapping how government procurement actually works rather than leading with product capabilities. The critical insight: in DoD sales, the warfighter (end user) doesn't control purchasing decisions. Success requires understanding each stakeholder's specific mandate and aligning your solution to their organizational incentives, not just operational needs. For civilian agencies like NOAA, the dynamics differ entirely. Founders entering govtech should invest 6-12 months learning procurement mechanics before expecting revenue.
Use government contracts as non-dilutive scaling capital for hardware businesses: WindBorne secured SBIR grants within six months, then landed their first Air Force data delivery contract through Defense Innovation Unit at the two-and-a-half-year mark. John explicitly treated early grants as equivalent to venture funding but without equity dilution. For companies building physical infrastructure at scale (satellites, hardware networks, manufacturing operations), government contracts provide the runway to reach technical milestones that unlock larger B2B opportunities. This sequencing—government funding first, then B2B products built on that foundation—proves more capital-efficient than attempting to raise massive venture rounds upfront for unproven hardware.
Integrate with legacy systems rather than attempting wholesale replacement: WindBorne doesn't aim to replace the 1,000 radiosondes launched daily worldwide—they're expanding coverage from the current 15% of Earth (where humans can launch traditional balloons) to 100%. The hardware is revolutionary (weeks of flight versus two hours), but the go-to-market integrates into existing weather agency workflows and feeds into established models like GFS and ECMWF. This approach accelerated adoption because agencies could add WindBorne data without overhauling their entire forecasting infrastructure. The displacement of radiosondes becomes economically inevitable long-term, but only after proving the system at scale.
Move fast once adjacent technology validates your thesis: WindBorne wasn't investing in AI-based weather forecasting until Huawei's Pangu Weather paper demonstrated that end-to-end neural weather models could compete with physics-based simulations. Once that validation appeared, John's team moved immediately—adopting the open architecture and expanding it into Weather Mesh before the approach became widely adopted. The lesson isn't to wait for competitors, but to monitor adjacent technological developments and move decisively when validation emerges. They built a top-performing model by being early to a proven approach, not first to an unproven one.
Hire for mid-level roles and promote based on demonstrated judgment: John hired Dana from Palantir as a proposal writer, not as a sales executive. He watched her demonstrate strong opinions that consistently proved correct, then promoted her to build and lead the entire public sector growth organization. This internal promotion model worked better than external executive hires because the person already understood WindBorne's technology, customers, and internal culture. For specialized domains like government sales, bringing in experienced operators at individual contributor levels and promoting them as they prove their judgment builds more effective organizations than hiring executives to parachute in.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.
Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How deskbird pivoted from near-bankruptcy to $10M+ ARR in the flexible workplace category | Ivan Cossu

Ivan Cossu is Co-Founder and CEO of deskbird, a flexible workplace management platform that's scaled past $10 million ARR. Founded in April 2020 during COVID's most uncertain period, deskbird survived a near-death pivot just months in and scaled across 10 international markets within six months—an unconventional path that challenged conventional wisdom about market domination strategies. Ivan shares the tactical decisions behind their international expansion, the shift from founder-led to scalable sales, and why they're deliberately targeting an underfunded VC category.
Topics Discussed:
The critical pivot from an Airbnb for co-working spaces to workplace management software in July 2020, months before running out of capital
The counterintuitive decision to scale internationally within six months rather than dominating a single market first
Balancing consumer-grade UX with enterprise-level customization in a category where competitors felt like "database queries"
The mechanics of transitioning from pure inbound to incorporating outbound without breaking what's working
US market expansion from Europe with higher close rates than home markets—and what that signaled about timing
Why traditional email outbound is dead in the AI era and what actually works for breaking through
GTM Lessons For B2B Founders:
Scale your proven funnel globally before you perfect it locally: When deskbird saw strong early traction, they launched landing pages across UK and US markets within months to test demand signals. Ivan's contrarian take: "If you have a good funnel that's working, be bold enough to scale it globally" rather than spending years dominating Germany first. The key qualifier—you need solid core product and conversion metrics, not just initial traction. They were "way too scared of going international because it always worked out way better than we thought," often seeing better metrics in new markets than home markets. Most founders over-index on local penetration when they should be testing international demand.
Choose validation channels by cycle time, not potential scale: In the first 6-12 months, avoid any channel with an 18-month feedback loop, even if it's your eventual ICP. Ivan targeted paid search and lower mid-market specifically because "you get a good sample size quite fast." Fast feedback loops let you iterate positioning, messaging, and ICP assumptions weekly rather than annually. Once you have conviction from high-velocity channels, then layer in longer-cycle enterprise motions. This sequencing prevents burning 12+ months on the wrong strategy.
Founder-led sales is a permanent muscle, not a phase to exit: At $10M+ ARR, Ivan still joins sales calls regularly, citing a top entrepreneur-investor's rule: "Sales always needs to remain a final topic." The evolution isn't binary—it's additive. First hires (around 9 months post-MVP) were generalist "hard workers" who could sell vision over process. Today's hires are more disciplined as repeatable plays emerged. But the founder never exits—they shift from doing all deals to strategic deals, competitive situations, and maintaining direct customer insight. Even Benioff at Salesforce's scale still jumps into deals.
Outbound in the AI era requires anti-scale tactics: Ivan's blunt assessment: "I don't believe in emails and any kind of written communication, especially not in the age of AI—it's just inflated." What works: (1) Targeted account selection—not 1:1 but not 1:1000 either, find the sweet spot of focused ABM, (2) Physical mail and offline media, (3) Cold calling with proper infrastructure. The challenge isn't the tactic—it's "having all the BDRs and AEs knowing which accounts they have to call, seamlessly calling account after account." Most companies can't operationalize the calling machine. Best results come when marketing warms leads with intent data, then hands them to outbound teams—not pure cold outreach.
Underfunded categories force better unit economics: Deskbird's space isn't flooded with VC dollars—Ivan mapped 50-60 European competitors but limited mega-rounds. His take: "There's a downside, it's harder to get VC money, but once you get it you don't have the problem that some spaces are overfunded and it's crazily driving up customer acquisition cost." Markets with excessive capital often have one winner and "very sad consolidation" for positions 2-4. Constrained capital forced deskbird to build profitably and focus on product differentiation (Airbnb-like UX meets enterprise customization) rather than outspending competitors.
Close rates in new markets signal expansion timing better than absolute numbers: Deskbird closed US deals from Europe with European AEs in mismatched time zones—and saw the highest close rates of any market. Ivan's logic: "If we can close them from Europe with our European AEs working in different time zones who cannot deliver the same SLAs, and we then go to the US, it should get even better." Don't wait for perfect execution—if you're winning despite structural disadvantages, that's your signal to invest. They hired their first US-based team only after proving they could win remotely.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.
Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How Maxima moved upmarket from 10-person startups to 500-1,000 employee companies after early customer feedback | Yogi Goel (Maxima)

Maxima is building AI agents that automate enterprise accounting while maintaining the auditability and control standards finance teams require. In a recent episode of BUILDERS, we sat down with Yogi Goel, CEO and Co-Founder of Maxima, to explore his eight-year journey at Rubrik from Series C through IPO, and how those lessons shaped his approach to solving the 70-80% of finance time currently wasted on manual work.
Topics Discussed:
Why Rubrik's approach—entering stagnant markets with first-principles thinking—became Maxima's blueprint
Securing $3K-$5K POC commitments from Figma mockups before writing code
Why Scale AI and Rippling rejected a point solution and demanded 3-4 modules from day one
The compound startup model: building multiple products simultaneously to meet buyer expectations
How 17% of CFOs are adopting AI tools today (vs 51% in software development)
Why finance teams view AI agents as "digital college freshmen" who need proof of work
Hiring from YouTube Studios, Apple, and Robinhood instead of legacy finance software companies
How NetSuite World conference booth sizes revealed the data integration infrastructure gap
The $3K-$5K validation threshold that proved finance pain was urgent enough to pay pre-product
GTM Lessons For B2B Founders:
Demand generation unlocks engineering potential: Yogi learned from his Rubrik mentors: "focus on demand and if you have great engineers then they will solve the problems." Maxima built products in 2-3 months they didn't initially know were technically feasible—because customer demand pulled the engineering team forward. For founders with strong technical teams, customer demand should drive the roadmap, not engineering's comfort zone. Trust your engineers to solve hard problems when customers are waiting.
$3K-$5K is the pre-product validation threshold: Before writing any code, Yogi secured POC commitments at this price point based solely on Figma mockups. This isn't about revenue—it's about proving urgency. Verbal interest means nothing. Small pilot commitments mean "we'll try it someday." But $3K-$5K pre-product means "this problem is urgent enough to pay before seeing a working solution." Use this threshold to separate real pain from polite interest.
Sophisticated buyers will reject your narrow MVP: Scale AI and Rippling told Maxima explicitly: "If you will only build this one thing, we will not buy. You have to commit to building three, four modules." Conventional wisdom says start narrow, but enterprise buyers with complex workflows won't adopt point solutions that create new integration headaches. When sophisticated buyers articulate their real buying criteria, ignore the startup playbook. Yogi built a "compound startup" with 4-5 modules from day one because that's what the market demanded.
Target acute pain over easy access: Early-stage companies (10-30 people) were easier to reach but finance wasn't urgent enough. At that scale, it's "build product, ship product"—finance operations aren't broken enough to warrant urgent attention. Companies at 500-1,000+ employees have finance teams drowning in manual work that prevents strategic contribution. Target where pain justifies urgent action and budget exists, not where calendar access is easiest.
Hire intensity and first-principles thinking over domain knowledge: Maxima deliberately hired zero engineers from legacy finance software companies. Their frontend engineer came from YouTube Studios. Others came from Apple, Robinhood, Netflix—none with financial product experience. Yogi's three hiring criteria: "incredible intensity, huge confidence in themselves, and fast thinking mode." Domain expertise creates pattern-matching to old solutions. First-principles thinking creates breakthrough products. One team member didn't finish high school but is "one of the best out there."
Make AI explainable or finance teams won't adopt: Finance teams adopted faster than expected because Maxima showed every calculation step. "If they can prove by looking at the Math, you know, 18 plus 88 plus 36 is X. And I can see the step of the work, they are willing to give it to them." This isn't about fancy UX—it's about auditor-grade proof of work. Finance professionals won't trust black box outputs. Build transparency into the product architecture, not as an afterthought. This explainability became Maxima's competitive moat.
Conference booth sizes reveal infrastructure gaps: At NetSuite World, the largest booths weren't ERP vendors or payment processors—they were data integration companies. This single observation validated that enterprises are desperately solving data fragmentation problems. Companies manually download from Stripe, Snowflake, Salesforce weekly to build Excel pivots. Maxima invested in upstream integrations as core infrastructure from day one. Use industry conferences to validate where companies are spending money on workarounds—that's where infrastructure gaps exist.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.
Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How Jome scaled from 500 to 1,500 builder partnerships in 12 months | Dan Hnatkovskyy

Jome built a marketplace for new construction homes by solving a transparency problem most people don't know exists: the vast majority of new builds never appear on Zillow, Redfin, or traditional MLS systems. In this episode of BUILDERS, I sat down with Dan Hnatkovskyy, CEO and Co-Founder of Jome, to unpack how he identified a massive category gap during Austin's pandemic housing boom and scaled from scraping builder websites to partnering with 1,700+ builders including 92 of the top 100. Dan shares the specific market moments that unlocked builder partnerships, how he discovered Google's separate product category for new construction, and why early LLM traffic became a meaningful acquisition channel.
Topics Discussed:
Why IDX feeds and MLS requirements systematically exclude new construction inventory
The three market inflection points that accelerated builder partnerships from 500 to 1,500+ in 12 months
How Google's separate new construction product category created an arbitrage opportunity against brand-focused builders
The manual MVP: Typeform + text message delivery before building any real product
Why the mortgage rate lock-in effect (50%+ of mortgages under 3.5% vs 6-7% prevailing rates) compounds the housing shortage
Accidentally discovering ChatGPT and Perplexity were driving closed transactions through analytics instrumentation
The decision to optimize entirely for buyers despite builders being the sole revenue source
GTM Lessons For B2B Founders:
Map structural exclusions in existing distribution systems: New construction homes can't enter MLS because they often lack finished addresses, real images, or completed properties—requirements designed for resale homes. This structural incompatibility created a $400B+ blind spot. Dan didn't just find underserved customers; he identified a category systematically locked out of dominant distribution. B2B founders should analyze whether incumbent platforms have structural requirements that exclude segments of the market, not just underserve them.
Exploit paid search category mismatches between buyer intent and seller behavior: Dan discovered Google maintains separate product categories for new construction versus resale homes. Zillow and Redfin competed intensely in resale, but new construction was dominated by individual builders (Lennar, DR Horton) who assumed brand-driven intent—similar to car manufacturers. The reality: buyers search "new construction homes in Austin," not "Lennar homes." This category/behavior mismatch created immediate arbitrage. B2B founders should audit whether buyers search by problem/outcome while incumbents bid on brand terms, creating white space for aggregators.
Time enterprise outreach to industry stress events, not product readiness: Jome scaled from 500 to 1,500 builders in one year by capitalizing on three specific moments: (1) pandemic demand surge when builders needed millennial/Gen Z reach, (2) 2022 quantitative tightening when builders feared demand collapse, (3) Zillow's 2023 policy change excluding builders with under 10 communities. Dan didn't wait for product-market fit—he mapped when prospects would be most receptive to any solution. B2B founders should create a calendar of industry stress events (regulatory changes, market corrections, competitor policy shifts) and time outreach to these windows regardless of product maturity.
Instrument conversion funnels to detect emergent channels before consensus forms: Jome discovered meaningful lead volume and closed transactions from ChatGPT and Perplexity through analytics, not strategy. Only after seeing the data did they experiment with what Dan calls "reinforcement learning with LLMs"—promoting positive results to train the models. This wasn't about SEO or prompt engineering; it was about measurement infrastructure that surfaced signal before the channel was obvious. B2B founders should track referral sources at the closed deal level, not just top-of-funnel, to catch emerging platforms while unit economics are still favorable.
Manually deliver value at zero margin before building product: Before any integrations or platform, Jome ran Google Ads to a Typeform, manually created searches in their agent-facing tool, and texted results to buyers. Dan's framework: "Start with manually creating value...and then step by step, improve it, automate it, make it more efficient." He launched this on a personal credit card and got immediate signal. B2B founders should resist the urge to build scalable product until they've proven someone will pay for (or convert on) manual delivery of the outcome.
Optimize for the non-paying side when you're building a two-sided marketplace: Despite 100% of revenue coming from builder commissions, every product decision optimizes for buyer experience. Dan's logic: "If we want to bring value to the builders...we need to start with the buyers. We need to create the best possible home buying journey." This isn't idealism—it's recognition that in transaction-based models, buyer liquidity determines builder participation. B2B founders in marketplace businesses must identify which side is supply-constrained and build obsessively for the other side.
// Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.
Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Why Radical AI targets markets frozen by innovator's dilemma | Joseph Krause

Radical AI is building scientific superintelligence—AGI for science—through a closed-loop system that combines AI agents with fully robotic self-driving labs to accelerate materials discovery. The materials science industry has a fundamental innovation problem: discovering a single new material system takes 10-15+ years and costs north of $100 million. This economic reality has frozen innovation across aerospace, defense, semiconductors, and energy—industries still deploying materials developed 30 to 100 years ago. In this episode, Joseph Krause, Co-Founder and CEO of Radical AI, explains how his company is attacking the root causes: serial experimentation workflows, systematically lost experimental data, and the manufacturing scale-up gap. Working with the Department of Defense, Air Force Research Lab on hypersonics systems, and as an official partner to the DOE's Genesis mission, Radical AI is focused on high entropy alloys that maintain mechanical properties in extreme environments—the kind of enabling technology that unlocks entirely new product categories rather than optimizing existing ones.
Topics Discussed:
The structural economics preventing materials innovation: 10-15 year timelines, $100M+ discovery costs, and why companies default to decades-old materials
Three fundamental process failures in scientific discovery: serial workflows that prevent parallelization, the 90%+ of experimental data that lives only in lab notebooks, and the valley of death between lab-scale discovery and manufacturing scale-up
How closed-loop autonomous systems capture processing parameters during discovery—temperature ranges, pressure requirements, humidity impacts, precursor form factors—that map directly to manufacturing conditions
High entropy alloys as beachhead: 10^40 possible combinations from the periodic table, requiring materials that maintain strength and corrosion resistance at 2,000-4,000°F in oxidative environments created by hypersonic flight
The strategic rationale for simultaneous government and commercial GTM: government for long-shot applications like nuclear fusion and access to world-class science institutions; commercial customers in aerospace, defense, automotive, and energy for near-term product applications
Why Radical AI focuses on enabling technology rather than optimization technology—solving for markets where novel materials unlock new products, not incremental margin improvements
GTM Lessons For B2B Founders:
Engineer downstream adoption barriers into your initial system architecture: Joseph identified that customer skepticism centered on manufacturability, not discovery speed. Most prospects understood AI could accelerate experimentation but questioned whether discoveries could scale to production without restarting the entire process. Radical AI's response was architectural: their closed-loop system captures processing parameters—temperature ranges, pressures, precursor concentrations, humidity effects, form factors like powders versus pellets—during the discovery phase. This data maps directly to manufacturing conditions, eliminating the traditional restart cycle. The lesson: In deep tech, the adoption barrier isn't usually your core innovation—it's the adjacent problems customers know will surface later. Engineer those solutions into your system from day one rather than treating them as future optimization problems.
Select beachheads where problem complexity matches your technical advantage: Radical AI chose high entropy alloys not because the market was largest, but because the search space is intractable for humans—10^40 possible combinations that would take millions of years to experimentally test. This creates a natural moat where their ML-driven autonomous system has exponential advantage over traditional approaches. Joseph explicitly distinguished "enabling technology" (unlocking new products) from "optimization technology" (improving margins on existing products), then targeted markets with products ready to deploy but blocked by materials constraints. The strategic insight: beachhead selection should optimize for where your technical approach has structural advantage and where success unlocks new market creation, not just better unit economics.
Structure dual-track GTM to derisk technology while building commercial pipeline: Radical AI simultaneously pursues government contracts (DOD, Air Force Research Lab, DOE Genesis) and commercial customers (aerospace, defense primes, automotive, energy). This isn't market hedging—it's strategic complementarity. Government provides access to the world's most advanced scientific institutions, funding for applications with 10-20 year horizons like nuclear fusion, and willingness to bridge the valley of death that scares commercial buyers. Commercial customers provide clear near-term product applications, faster revenue cycles, and market validation. Joseph views them as converging rather than divergent, since transformative materials apply across both. The playbook: in frontier tech, government and commercial aren't either/or choices—structure them as parallel tracks that derisk each other while your technology matures.
Reframe the economics of the innovation process itself: Joseph didn't pitch faster materials discovery—he reframed the entire process from serial to parallel, from data-loss to data-capture, from discovery-manufacturing gap to integrated workflow. This changes the fundamental economics: instead of 10-15 years and $100M+ per material, the conversation shifts to discovering and scaling multiple materials simultaneously with manufacturing parameters already mapped. This reframing unlocks budgets from companies that had stopped innovating because the traditional process was economically irrational. The insight: when industries have stopped innovating entirely, the problem isn't usually that existing processes are too slow—it's that the process itself is structurally broken. Identify and articulate the broken process, not just the speed/cost improvement.
Lead with civilizational impact to filter for long-term aligned stakeholders: Joseph explicitly positions Radical AI as "building a company that fundamentally impacts the human race" and tells prospective talent, "if you are focused on a mission and not a job, this is the place for you." This isn't recruiting copy—it's strategic filtering. In frontier tech with 10-15 year commercialization horizons, you need customers, partners, investors, and talent who think in decades, not quarters. Mission-driven positioning attracts stakeholders aligned with category creation over optimization and filters out those seeking incremental improvements. It also provides air cover for decisions that prioritize long-term technological breakthroughs over short-term revenue optimization.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.
Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How Rainforest justifies the ROI of hosting a podcast and conference | Joshua Silver

Rainforest enables vertical software companies to embed payment processing directly into their platforms - solving the complexity that previously forced software companies to direct customers to separate banks or resellers for payment processing. Founded by Joshua Silver, who spent nearly 20 years in payments starting with PatientCo (a healthcare billing company that scaled to process billions for major healthcare organizations), Rainforest now serves as the enabling layer for thousands of vertical software companies. In this episode of BUILDERS, Joshua shares the unconventional GTM decisions that shaped Rainforest's trajectory: from making contracts a product feature to implementing a zero bugs policy, and why he measures podcast success by qualified lead conversion rather than download counts.
Topics Discussed:
The embedded payments opportunity: why software companies stopped directing customers to banks
Building in highly regulated environments where traditional MVP approaches fail
The extended foundation-building phase required before processing the first payment
Transitioning from 2.5-3 years of founder-led sales to a scalable GTM motion
Using contract terms as competitive differentiation rather than negotiation leverage
Implementing a zero bugs policy and its impact on service costs and retention
Building thought leadership through the Payment Strategy Show and Vertex conference
Lead quality metrics over vanity metrics for content investments
GTM Lessons For B2B Founders:
Hire from the industry and invest disproportionately in technical onboarding: Rainforest maintains one of the highest concentrations of payments talent on a percentage basis—nearly everyone has worked in payments or payments-adjacent roles. But hiring isn't enough. Joshua obsesses over training because in complex sales, prospects ask detailed technical questions and "the moment that you give bad answers or don't know your stuff, they're going to detect that and that's going to detract a lot from the trust." When selling technical infrastructure, surface-level product knowledge kills deals. Every touchpoint—engineers, support, account execs—must understand not just how the product works, but why it works that way.
Engineer your standard contract to eliminate negotiation cycles: Joshua inverted conventional wisdom by making Rainforest's standard contract "overly favorable to the client"—no hidden terms, no punitive clauses, no exclusivity provisions. The result: "We don't have to spend a lot of legal time going back and forth. We don't have to invest a lot of time and by the way, burning a lot of goodwill too in contract negotiations." Prospects consistently report the legal process was shockingly easy compared to competitors. This isn't about being naive—it's strategic capital allocation. Joshua's philosophy: "Pick the fights that really matter and everything else is just rounding." Time spent in legal negotiations is wasted time that could be spent onboarding customers.
Embed sales capabilities into your customer success function: Rainforest trains their CS team on negotiation tactics, value selling, and objection handling—competencies rarely developed in post-sale teams. Joshua noted the primary goal is customer assistance, but growth is an underlying objective. This isn't about making CS "do sales"—it's about equipping them to have commercial conversations when customers naturally express expansion interest. The key enabler: strong product-market fit means "we don't have to sell it that much. It's really a conversation about solutioning."
Enforce a zero bugs backlog in high-stakes environments: Joshua's unofficial core value—"don't f with the money"—manifests in their zero bugs policy. It's not that they never create bugs; it's that "we don't tolerate living with them. We don't have a backlog of bugs to fix." When a bug is validated, they fix it immediately. His head of engineering recently discussed this on a podcast because people find it radical. The payoff: "When you have a higher quality product, you don't have to invest as much in service because the product just works and you have naturally happy customers." For infrastructure products where errors cascade into customer incidents, the accumulated cost of technical debt vastly exceeds the upfront investment in quality.
Qualify content success by whether it's converting your ICP: Joshua rejects vanity metrics entirely. When asked about podcast ROI, he said: "I'd rather have 100 highly qualified listeners that are great targets for us than have 100,000 listeners and not have 100 qualified ones." They track this rigorously—every inbound lead is asked how they discovered Rainforest, and an increasing percentage cite the podcast. Prospects explicitly say "we heard the podcast and nobody else is putting this content out there." The metric isn't downloads; it's whether qualified buyers are self-identifying through your content and entering sales conversations pre-educated and pre-sold.
Build ecosystem assets without demanding immediate attribution: Rainforest launched Vertex—a curated conference for vertical software founders and operators—that explicitly isn't a Rainforest sales event or user conference. Joshua doesn't track lead conversion from the conference: "That's not one of the key metrics. We actually look at NPS score as one of the key metrics. Did people find value in the conference?" They're running it twice this year because attendees report it's the highest-quality conference they attend annually. His philosophy: "Go create value, legitimate, genuine value for the ecosystem and they will come to us." They deliberately limit attendance to several hundred and choose venues that physically can't accommodate massive scale—maintaining intimacy as a forcing function against growth-for-growth's-sake.
Plan for extended pre-market build phases in regulated industries: Joshua's advice for payments founders: "Make sure you know what you're getting into. It's a big build and there's very low tolerance for misses." Before processing their first payment, Rainforest had to achieve PCI compliance, SOC2 compliance, and implement comprehensive security infrastructure. Only then could they begin customer development with close network contacts. He contrasts this with his standard founder advice: build an MVP, sell quickly, get feedback, iterate. In payments, that playbook doesn't work—"you actually have to build so much of the foundation first just to process your very first payment." Founders in regulated spaces need patient capital and realistic timelines that acknowledge compliance infrastructure isn't optional.
Institutionalize "ruthlessly simplify" as an operating principle: One of Rainforest's core values is ruthless simplification, which Joshua applies to "the legal contract, the engineering documentation, anything." He asks his team repeatedly when reviewing anything: "Can we simplify it? Can we simplify it? Can we simplify it?" The output quality dramatically improves. He references the Tim Ferriss framing: "What would this look like if it were simple?" When applied consistently, it cuts approximately 50% from plans, strategies, and deliverables—even when the creator thought they were already building simply.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Why aiOla targets CFOs — not IT buyers | Amir Haramaty, Co-Founder at aiOla

aiOla is pioneering speech-to-data technology that transforms unstructured speech into actionable data for enterprise operations. As a serial entrepreneur on his sixth startup, Co-Founder Amir Haramaty built aiOla after witnessing firsthand how traditional AI implementations fail to deliver ROI in enterprise settings. The company has developed proprietary technology that achieves near-100% accuracy in challenging environments with heavy jargon, multiple languages, and difficult acoustics. With strategic investors including a major airline and partnerships with Nvidia, Accenture, and USG, aiOla is addressing the fundamental challenge that 95% of enterprise AI pilots fail to show value by focusing on immediate, measurable ROI through speech-based data capture.
Topics Discussed:
The genesis of aiOla from consulting work revealing AI's implementation gaps in traditional enterprises
Solving the triple challenge of speech recognition: accuracy in jargon-heavy environments, separating signal from noise, and converting speech to structured workflow data
aiOla's "jargonic" approach: creating hyper-personalized language models for specific processes without retraining
Early customer acquisition through serendipitous encounters and demonstrating immediate ROI
Vertical expansion strategy from food manufacturing to aviation, travel, hospitality, and retail
Channel partnership strategy refined from previous startups to achieve scale
The shift from convincing customers about speech technology to being pulled into diverse use cases
Building the aiOla Intelligate orchestration layer to dynamically select optimal speech recognition models
GTM Lessons For B2B Founders:
Make CFOs your best friend, not IT departments: Amir explicitly targets CFOs rather than IT as primary buyers because "it doesn't matter how small or big you are, you still have to do more with less." While IT serves as facilitators, CFOs control budgets focused on operational efficiency and ROI. B2B founders should identify which executive truly owns the pain point and budget authority, even if IT will implement the solution.
Deploy capital strategically to remove obstacles before they emerge: aiOla convinced their airline investor to provide working capital specifically to fund POCs for prospects without existing budgets. This eliminated the "we don't have pilot budget" objection before it arose. B2B founders should proactively identify and neutralize common barriers in their sales process, whether through creative deal structures, proof-of-concept funding, or implementation support.
Prioritize instant ROI over long-term transformation promises: Amir explicitly avoids "digital transformation" conversations, instead selecting use cases delivering "biggest impact within shortest period of time with minimum obstacle possible." The airline baggage tracking example saved 110,000 hours immediately, creating momentum for expansion. B2B founders should resist selling comprehensive transformation and instead identify narrow use cases with quantifiable, rapid returns that create internal champions.
Replicate proven use cases across customers rather than customizing: Once aiOla achieved success with specific applications like CRM data entry or pre-op inspections, they "stop, print, replicate" rather than reinventing for each customer. This approach reduced a two-hour inspection process to 34 minutes in food manufacturing, then replicated across industries. B2B founders should document successful implementations as repeatable playbooks and resist the urge to over-customize for each prospect.
Channel success requires speaking the partner's economic language: When working with telcos, Amir demonstrated that his solution increased ARPU by 34% and reduced churn by 17%—the only two metrics telcos prioritize. He built predictable models showing exactly how many units each channel rep would sell by geography. B2B founders pursuing channel strategies must translate their value proposition into the specific KPIs that drive partner economics and compensation.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.
Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How Doctronic became the first AI licensed to practice medicine through Utah's regulatory sandbox | Matt Pavelle

Doctronic became the first AI in the world legally licensed to practice medicine through Utah's AI Learning Lab regulatory sandbox in December 2025. In this episode of BUILDERS, I sat down with Matt Pavelle, Co-founder and Co-CEO of Doctronic, to learn how he and his co-founder (a physician) launched an AI-powered primary care chatbot in September 2023, validated demand through Facebook chronic condition groups and minimal Google Ads spend, and navigated uncharted regulatory territory to offer $4 prescription renewals for chronic conditions—targeting the medication non-adherence problem that causes 125,000 preventable deaths and costs $100B annually.
Topics Discussed:
Why friends with excellent health insurance still couldn't get medical answers quickly Building clinical accuracy into GPT-3.5 when context windows were small and hallucinations were rampant The tactical launch: Google Ads plus Facebook chronic condition groups in September 2023 Architecting safety: RAG with tens of thousands of physician-written clinical guidelines The study: 99.2% agreement rate between AI treatment plans and human doctor reviews across 500 patients Navigating Utah's AI Learning Lab: the only regulatory sandbox that mitigated medical licensing laws Securing AI malpractice insurance through Lloyd's Market—a first in the industry The three-phase oversight model: 100% human review, then 10%, then spot checks Expansion strategy: targeting other state regulatory sandboxes and international governments
GTM Lessons For B2B Founders:
Launch with the minimum feature set that proves your core hypothesis: Pavelle shipped Doctronic in September 2023 without user accounts—chats disappeared when closed unless users saved them manually. Within days, user requests for persistent chat history validated demand. The insight: your MVP should test one assumption, not solve every user need. If you're hesitating to launch because features are missing, ask whether those features are actually required to validate your hypothesis or just things you assume users want.
Use specificity to unlock early adoption in skeptical markets: Rather than targeting "healthcare" broadly, Pavelle posted in Facebook groups for specific chronic conditions, offering a free AI backed by clinical guidelines. Half the groups banned them for commercial activity, but the other half engaged immediately. The lesson: in regulated or skeptical markets, narrow targeting with explicit safety mechanisms (clinical guidelines, physician co-founder credibility) converts better than broad positioning. Identify where your skeptics congregate and address their specific objections upfront.
Design system architecture to prevent failure modes, not just tune models: Doctronic's safety architecture separates AI decision-making from prescription execution. The LLM asks questions and determines renewal safety, but deterministic code outside the AI verifies the prescription exists, checks dosage accuracy, and confirms the schedule. Even if adversarial prompting compromises the LLM, the deterministic layer prevents bad outcomes. Founders building high-stakes AI products should architect multiple independent verification layers rather than relying on prompt engineering or temperature tuning alone.
Target regulatory pain points with quantified deaths and costs: Pavelle approached Utah with specific numbers: 125,000 preventable deaths annually from medication non-adherence, 30-40% caused by renewal friction, and a $100B economic burden. These statistics—combined with Utah's rural population and physician shortage—made the problem impossible to ignore. When approaching regulators, lead with mortality and cost data that make inaction untenable, not just efficiency gains or convenience improvements.
Regulatory sandboxes require proof of safety methodology, not just technology demos: Utah's AI Learning Lab didn't just grant Doctronic permission—they required a three-phase oversight structure where human physicians review 100% of initial prescriptions in each medication class, then 10%, then ongoing spot checks. Pavelle also secured AI malpractice insurance through Lloyd's Market before launch. The insight: regulatory innovation offices want risk mitigation frameworks, not promises. Build and fund your oversight methodology before approaching regulators, and treat insurance underwriting as a third-party validation of your safety claims.
Publish clinical validation studies before scaling—they become your regulatory and sales asset: The study showing 99.2% agreement between Doctronic's AI and human physicians across 500 patient encounters became the foundation for regulatory conversations and public trust. Founders in regulated spaces should budget for formal validation studies early—these aren't marketing expenses, they're the permission structure for everything that follows. Work backward from what regulators and enterprise buyers need to see, then design studies that generate that specific evidence.
// Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Vanessa Larco on Building, Investing, and What Makes Great Founders [VC Edition]

After building products at Microsoft (Xbox, Surface), a gaming startup acquired by Disney, Twilio, and Box, Vanessa Larco joined NEA where she led seed investments in Greenlight (debit card for kids), Majuri (C2C jewelry), and Limitless (acquired by Meta). She served on Robinhood's board for five and a half years through IPO and the GameStop crisis. In this conversation, Vanessa breaks down the specific traits that separate top 1% founders from the rest, why venture capital is experiencing structural chaos from simultaneous mega-fund expansion and generational transition, and why technical founders who deeply understand consumer behavior change represent the next wave of breakout companies.
Topics Discussed:
How customer-focused decision-making at Robinhood during GameStop contradicted public perception
The specific paradox great founders must balance: maniacal focus versus recruiting ability
Why venture is simultaneously dealing with fund size chaos and generational leadership transition
The decision framework for staying in venture versus returning to operating
Why consumer is radically underinvested despite users' demonstrated willingness to pay for "magical" experiences
How AI tools create internet-scale behavior change by synthesizing information rather than just accessing it
The authentic voice problem in VC personal branding and platform-specific challenges
GTM Lessons For B2B Founders:
Great founders possess maniacal focus on the right problems, not all problems: Vanessa describes exceptional founders as having an "insatiability" where "they pick the thing and they can focus on the thing and not get distracted by anything else and be maniacal about it." This isn't generic persistence—it's the ability to identify which specific problem deserves obsessive attention while ignoring everything else. Employees often push back ("we have these other fires"), but top founders maintain "one track" focus. The implementation challenge: most founders spread maniacal energy across too many initiatives. The best founders are "obsessive compulsive about how they build" on 1-2 things maximum, then deliberately de-prioritize everything else, even when it feels irresponsible.
Incentive structure misalignment creates unwinnable scenarios: During GameStop, Robinhood faced retail traders whose incentives were fundamentally incompatible with traditional market participants. As Vanessa notes, "if your team and your company is bound by a certain set of incentives and you're up against someone with a very different set of incentives, that never really ends well." The Wall Street Bets mantra—"we can stay irrational longer than they can stay solvent"—explicitly weaponized this mismatch. For founders: map not just competitor strategies but their underlying incentive structures. Are they optimizing for growth, profitability, strategic acquirer appeal, or something else? When your incentives conflict with a market participant's (customer, partner, regulator, competitor), you cannot win through superior execution alone—you need structural repositioning.
Technical founders who ship faster capture AI-era market position: Vanessa specifically seeks "technical founders with an eye for consumer behavior change" because "speed is really important in this era." This isn't about being first to market—it's about iteration velocity. When foundational models improve every few months and user expectations evolve weekly, the team that can "deliver on it faster than anyone else" compounds advantages. Non-technical founders add product/sales/fundraising cycles between insight and deployment. Technical founders collapse these cycles, testing behavioral hypotheses in days rather than quarters. In markets where "what's possible" changes monthly, this velocity differential determines who owns category definition.
Behavior change wedges beat feature superiority: Vanessa looks for founders who understand "how this new technology is changing how people behave and changing what people expect of their tools" and can identify "what need can I fulfill better because I can build this thing that couldn't be built before." The critical insight: users don't adopt based on capability—they adopt when technology enables a behavior they already want but couldn't execute. She emphasizes products that are "radically faster, radically cheaper, radically easier" (not 10% better) and founders who understand "how they'll wedge into behaviors." Implementation framework: don't ask "what can this technology do?" Ask "what behavior is currently blocked by cost/speed/complexity that this technology removes the blocker for?"
Category creation happens post-problem-solving, not pre-launch: Discussing Robinhood's positioning, Vanessa reveals how the team "stayed focused" on enabling "people to continue participating in the markets" rather than defending an abstract category. The company focused on structural problems (settlement times, capital requirements) rather than category messaging. For founders: solve the acute problem your customer articulates, even if it seems tactically narrow. Category definition emerges after you've solved related problems for enough customers that the pattern becomes obvious. Premature category creation forces you to defend an abstract positioning rather than deepen specific problem-solving.
Personal brand building only works at the intersection of authenticity and utility: Vanessa admits "I can't find my authentic voice on Twitter to save my life" and her successful posts are "when I'm on an airplane and it's delayed by like over an hour and I'm angry." Meanwhile, "video and audio, way more my comfort zone" but requires "discipline that I don't think I yet possess." The lesson for founders: audience building helps ("people then know what you are, what you stand for... it helps establish trust faster, it helps people find you") but forced authenticity backfires. Better to own one channel where your natural communication style works than maintain mediocre presence across all platforms. LinkedIn for thoughtful analysis, Twitter for real-time reaction, podcasts for deep conversation—pick the format that doesn't require you to perform.
//
Sponsors:
Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co
//
Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.
Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM