Podcasts about 100m arr

Dextall is attacking a structural inefficiency in construction: the 3-year design coordination cycle that precedes every mid-rise building, combined with the chaotic on-site execution that follows. Founded by Aurimas Sabulis after years running a commercial window company and witnessing construction site dysfunction firsthand, Dextall is building what Aurimas calls a "prefab operating system"—software that connects architectural design directly to factory production of building exteriors. In a market where less than 1% of U.S. mid-rise projects use prefab (versus 75% in Scandinavia), Dextall is bridging the 3-4 year gap between design inception and approved drawings while manufacturing building components that arrive on-site as "Lego blocks." In this episode, Aurimas shares the hard lessons learned from building in construction's unforgiving risk environment. Topics Discussed: Targeting the 6-40 story sweet spot: steel, concrete, and mass timber construction where prefab delivers maximum value (below 6 stories is wood frame; above 40 enters different glass-box typology) The reality of U.S. prefab penetration: 99% of projects in Dextall's pipeline would go traditional route without them Why the physical product stayed constant from day one while software took multiple failed iterations The expensive lesson: building software that goes from design to fabrication in one day, only to learn architects rejected it because it removed their design control Evolving from 2D drawings to 3D renderings to animations to physical two-story mock-ups—and why customers only "got it" after seeing real completed buildings Launching a separate SaaS division for architects that independently generates value while creating 90% backend efficiency when connected to Dextall's manufacturing The three-to-five-year vision: prompt-engineered buildings with real-time cost, carbon footprint, and feasibility feedback GTM Lessons For B2B Founders: Domain credibility is your entry ticket in risk-averse industries: Aurimas's first customers came because he had "street credibility"—a track record of delivering complex, large-scale window projects. In construction, healthcare, and other industries where failure has severe consequences, founders without domain experience face insurmountable trust barriers. If you're building in these markets without industry background, your co-founder or first hires must bring that credibility, or you'll burn years trying to earn it. Proof velocity matters more than proof perfection: Dextall moved from 9-story buildings to 40-story projects by stacking proof points, not by waiting to debut with a showcase project. Each successful delivery de-risked the next larger bet. Founders should optimize for proof velocity—getting the smallest viable validation that enables the next larger commitment—rather than trying to land the trophy customer that "proves everything." Physical businesses require physical proof—budget accordingly: Dextall built multiple two-story physical mock-ups and actual buildings before customers truly understood their value proposition, despite having sophisticated 3D animations. Aurimas noted customers kept claiming they understood, then asking the same questions until they could physically see and touch completed work. If you're building in construction, manufacturing, or industrial sectors, your CAC will include physical demonstration costs that software founders never face. Budget 3-5x what you think you'll need for mock-ups and proofs of concept. Workflow disruption fails when you remove user agency: Dextall's software could compress 3-4 years of design coordination into one day—a 1000x improvement. Architects rejected it because it was "too heavy" and removed their control over design. The team had to rebuild to let architects control design while Dextall's system handled the backend connection to manufacturing. When your "better way" requires users to surrender control or change how they think about their craft, you're not selling efficiency—you're selling identity change, which rarely works. Find the integration layer that adds value without displacing existing agency. In mature industries, selectively challenge the status quo: Aurimas explicitly asks "is this fight worth fighting?" when Dextall encounters resistance to their approach. They focus on 3-4 nuances at a time rather than attempting to fix all 100 industry problems. When pushback happens, they evaluate whether to press the issue or "build deeper trench within the customer base" first, then return to that battle later. Founders tackling established industries should map their battles, not just their product roadmap—identify which conventions are essential to challenge for your value prop, and which can wait until you have more market power. Bridge disconnected systems rather than optimizing endpoints: The construction industry has sophisticated design tools (AI-powered generative design) and manufacturers (though often Excel-based). Dextall's differentiation is connecting these two worlds—architects can design freely, and their designs automatically translate to manufacturing specifications with real-time costing and feasibility. Many mature industries have this pattern: advanced front-end tools, capable back-end production, but manual/broken handoffs between them. The integration layer often provides more defensible value than improving either endpoint. Layer software distribution onto enterprise sales once you have proof: Dextall spent years doing "old school" enterprise sales—cold calling developers, lunch-and-learns with architects, bringing customers to job sites. Only after building credibility and understanding architect workflows are they launching SaaS for architectural firms. The software creates independent value for architects while generating 90% backend efficiency for Dextall when connected. Founders in hybrid businesses should resist the temptation to lead with software distribution before proving the full value chain works—but actively build toward that transition. // 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

hema.to is building AI-powered diagnostic infrastructure for cytometry—a specialized area of laboratory medicine analyzing immune system data to detect blood cancers like leukemia and lymphoma. Unlike radiology or pathology where AI solutions are abundant, cytometry has remained largely untouched by the AI wave, creating both opportunity and isolation for the Munich-based company. In a recent episode of BUILDERS, we sat down with Karsten Miermans, CEO at hema.to GmbH, to discuss why they're deliberately keeping sales founder-led despite having paying customers, how South America became an unexpected beachhead market, and what it actually means to build infrastructure versus point solutions in healthcare. Topics Discussed:  From consulting project to venture-backed company: recognizing scalability in hindsight  The workflow integration problem killing healthcare AI implementations  Infrastructure versus technology: why healthcare AI isn't just about the algorithm  Learning ideal customer profile after 18 months of being "all over the place"  Why South America's governance structure enables faster adoption than the US  Resisting the urge to hire sales before achieving true repeatability  The 10-year vision: shifting from "watch and wait" to "predict and prevent" in immune disease GTM Lessons For B2B Founders: Pattern matching fails when you're an outsider—budget 18+ months to find your beachhead: Karsten assumed every application of their diagnostic method was the same and spent a year and a half "blue eyed" (naively optimistic) before identifying their true ICP. The outsider advantage lets you reimagine workflows insiders can't, but you'll incorrectly assume transferability across use cases. Don't expect repeatability in year one when entering regulated, workflow-dependent markets. Infrastructure requires multi-stakeholder orchestration—resource for enterprise complexity from day one: Karsten distinguishes technology (point solutions, single users) from infrastructure (shared resources requiring data exchange and workflow integration). In healthcare, this means integration into hospital systems, databases, and electronic health records across multiple stakeholders. "Every sale becomes enterprise sales" even for individual labs because of this infrastructure requirement. Founders building horizontal platforms should model sales cycles and resource requirements as enterprise from the start, regardless of deal size. Your ICP is cognitively overloaded—they won't understand your category innovation: Doctors are "under so much pressure that they just don't have any cognitive capacity left" to philosophically evaluate why AI might be difficult to implement or how infrastructure differs from technology. They need problems solved within their existing mental models. Skip the category education. Frame everything as workflow enhancement, not innovation. Let sophistication emerge through implementation, not pitch decks. Revenue doesn't equal repeatability—know when you're still in discovery mode: Despite having paying customers, Karsten explicitly states "we're not at product-market fit yet" because they're "discovering and learning things with every new laboratory hospital" around data privacy, integration, and AI deployment. The PMF signal isn't customer count or revenue—it's when the process becomes predictable, customers refer others, and you stop discovering new requirements. Hiring sales before this point scales complexity, not revenue. Regulatory friction determines market sequencing, not just market size: US governance complexity turns every deal into heavy enterprise sales with "many stakeholders," while South America proved "much more willing to move with fewer processes," making them "just much faster to adopt innovative technology." This wasn't strategy—Karsten's CTO speaks Spanish through a personal connection. But the lesson transfers: for infrastructure plays in regulated markets, test adoption velocity in lower-governance environments first to build proof points, even if TAM looks smaller on paper. In healthcare, marketing is clinical evidence—customer success creates your GTM flywheel: Karsten spends minimal time on marketing because beyond the first 5-10 users, doctors "want to see clinical evidence, they want to see papers, they want to see maybe that a friend of theirs is using it." Marketing in healthcare isn't content or demand gen—it's peer validation and published proof. Founders should structure early customer engagements to generate this evidence, not just revenue. The "marketing sales flywheel really does kick in much more once you have product market fit" because PMF enables the evidence generation required for credibility. // 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

Empathy is pioneering bereavement care as an enterprise benefit, transforming how employers and financial institutions support employees during life's most challenging transitions. Working with 9 of the top 10 life insurance carriers in the US and Canada—covering over 40 million people—Empathy created a new category by combining grief support with practical logistics like probate navigation, account deactivation, and estate settlement. In a recent episode of BUILDERS, we sat down with Ron Gura, Co-Founder & CEO of Empathy, to learn how the company went from testing five verticals simultaneously to dominating life insurance, then leveraged the group life/employer overlap to expand into employee benefits. Topics Discussed: Testing five enterprise verticals simultaneously to find product-market fit Landing New York Life through their venture arm and innovation team Why life insurance carriers need to be risk-averse (and how to work with that reality) The strategic overlap between group life insurance and employee benefits Investing in brand at seed stage when your barrier to entry is psychological aversion Navigating dual audiences: decision-makers in their workday versus end users in crisis Expanding from loss to adjacent life transitions like disability leave and estate planning GTM Lessons For B2B Founders: Run parallel vertical tests with focus constraints, not sequential exploration: Ron identified 10+ potential verticals but intentionally tested exactly five simultaneously—hospices, funeral homes, employers, and two others before life insurance emerged as the winner at position five. This parallel testing with artificial constraints forces prioritization while dramatically compressing time-to-insight. Sequential testing would have meant potentially cycling through five failed pilots before discovering their strongest market. B2B founders with horizontal platforms should pick their top 3-5 verticals and run focused pilots in parallel, accepting that this burns more resources upfront but eliminates the risk of quitting before finding your wedge. Map the ecosystem overlap between buyer personas before choosing your wedge: Empathy's expansion from life insurance to employers wasn't growth strategy—it was recognizing an architectural reality. Half their carriers sell group life, meaning MetLife doesn't sell to consumers at metlife.com but exclusively to employer groups. When Amanda at Paramount loses her sister (not covered by insurance), she calls Paramount HR. When her husband dies (covered by MetLife group policy), the beneficiary calls MetLife. Same end user, two different enterprise entry points into the same moment. B2B founders should map these triangular relationships before choosing their wedge vertical. The question isn't just "who has budget?" but "who else touches this user in adjacent contexts?" Brand investment at seed stage is product strategy when fighting cognitive aversion: Ron's insight: "The barrier to entry isn't regulatory and isn't technology. It's us humans trying really hard not to think about our own mortality." This isn't a marketing problem—it's a fundamental go-to-market blocker. The company made what most would consider Series A investments (premium domain, design system, tone/voice framework) at seed stage specifically because brand reduces psychological friction to adoption. Contrast this with Monday.com starting as "daPulse" and rebranding years into success. B2B founders addressing taboo topics (death, mental health, financial distress, relationship issues) should model brand as a core distribution lever, not post-PMF polish. In deeply human categories, buyer's lived experience is your demo: Enterprise buyers at Citibank, MetLife, or Google aren't experiencing crisis during the sales cycle—they're evaluating ROI in their normal workday. But as Ron noted, "Everyone we're talking to...they're humans. They have parents, they had loss, they went through probate." The most common response after seeing the product: "Damn, I wish you called me a few months ago. I needed this a year ago with my mom." This turns product demo into personal recognition. B2B founders in universal human experience categories (caregiving, bereavement, parental leave, financial stress) should structure discovery and demo to activate buyer's memory of their own experience, not just their budget authority. Category creation is a resource-attraction strategy that trades speed for competitive exposure: Ron explicitly acknowledged: "There's pros and cons to defining a category. It's helpful when you attract resources, talent, capital. It also creates very fertile ground for a number two sympathy.com to come along and learn from this podcast...what to go after." Category leadership accelerates recruiting and fundraising by providing narrative clarity, but it simultaneously publishes your playbook. Every hiring blog post, podcast appearance, and positioning document teaches future competitors which verticals to target and which to avoid. B2B founders should treat category creation as a conscious bet: trade competitive opacity for talent/capital velocity. If you're not ready to defend your position, stay in stealth longer. Bridge new categories to existing budget lines through analogous benefits: When entering new verticals beyond life insurance, Ron doesn't educate from zero. With employers, he positions bereavement care alongside caregiving solutions, fertility programs, and parental leave: "This is a life transition happening in my own intimate house. Just like a new baby. I have new duties now." This isn't metaphor—it's budget mapping. Bereavement care gets evaluated against existing family benefits spending, not created from scratch. B2B founders in new categories should identify which existing line item their solution logically extends, then structure ROI narratives around reallocation, not net-new budget creation. // 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

The cross-border payments market remains stubbornly difficult despite billions in venture capital and countless smart founders attacking the problem. The core challenge isn't technology—it's economics. Western Union's margins weren't exploitative greed; they reflected the brutal reality of cash distribution networks, compliance infrastructure, and dual-country regulatory overhead. Palla Financial cracked this by inverting the entire model: instead of fighting for expensive US-based senders, they partnered with Latin American banks to let recipients pull funds. This approach taps into the world's largest remittance corridor ($160+ billion annually flowing from the US to Latin America) while sidestepping the customer acquisition bloodbath. In this episode, Enrique Perezalonso, CEO of Palla Financial, breaks down why recipient-driven payments eliminate distribution costs, how they rebuilt their product three times based on bank feedback, and why the "no CAC" embedded model still requires massive partner investment to actually work. Topics Discussed: Why cross-border payments remain broken: dual-country regulations, cash distribution economics, and two-sided transaction complexity The shift from cash-based infrastructure to digital rails and its impact on unit economics Palla's pull-based model: embedding payment requests inside bank apps to flip sender/recipient dynamics Revenue mechanics: $3 consumer fees, FX markup economics, and interchange/revenue sharing with bank partners The buy-vs-build calculus for banks and why a Central American banking group returned after a four-year internal build attempt Creating a new category and watching competitors attempt to copy the embedded approach Selling into banks with no standardized buyer: navigating from remittance teams to CEOs depending on organizational maturity The reality of "indirect" CAC: why embedded distribution still requires heavy investment in partner success Implementation failures and the shift from hands-off best practices to consultative partner enablement GTM Lessons For B2B Founders: Flip expensive distribution by attacking the other side of the transaction: While competitors burned cash acquiring US-based senders in saturated corridors (US-Mexico, US-India), Palla partnered with recipient-side banks in Latin America. Banks gained deposits, interchange revenue, and digital channel differentiation without building infrastructure. The lesson isn't just "find cheaper distribution"—it's recognizing that two-sided markets have two potential wedges, and the less obvious side may offer superior economics and strategic positioning. Target buyers who already tried and failed to build: A Central American banking group spent nine months evaluating Palla, decided to build internally, then returned four years later. This wasn't poor execution—it was competing priorities, lack of scale economics, and the reality that cross-border payments isn't their core business. The strongest signal for partnership readiness isn't interest, it's previous build attempts that stalled. These buyers understand the problem deeply and won't need convincing on value. "Embedded" and "no CAC" are myths without massive partner investment: Palla initially provided best practice guides and light coaching, assuming banks would naturally drive adoption. They saw "lackluster results" until they became "more and more hands-on," shifting to consultative implementation with proper incentive design and accountability frameworks. The volume business requires scale, and scale requires active partner management. Budget for partner success resources as if you're hiring an implementation consulting team, not just doing integrations. Use speed to rebuild the product in real-time with customers: The product Palla launched bears little resemblance to their original vision. They rebuilt features "hand in hand" with bank partners, leveraging their advantage over large competitors: no bureaucracy, hunger to make it work, and speed. This isn't about "customer feedback"—it's about treating early partners as co-developers and having the discipline to throw away your original roadmap when partners show you what actually solves their problem. Extreme focus means saying no to everything adjacent: Palla deliberately limits themselves to "two or three products" all within cross-border payments, explicitly avoiding cross-sell opportunities and adjacent revenue streams. Enrique notes this is both their moat and "a potential pitfall" when opportunities multiply with success. The discipline isn't about focus when you're struggling—it's about maintaining focus when growth creates endless plausible expansions. Each "yes" to something new is a "no" to deepening your core advantage. // 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

Ridepanda turned the failed unit economics of shared micro-mobility into a viable B2B model by eliminating operational costs that drove Lime's per-minute pricing from $0.15 to $0.55. After working at Lime and seeing firsthand why rebalancing, charging, vandalism, and theft made profitability impossible, Co-founder Chinmay Malaviya built a subscription model where employers subsidize personal e-bikes and scooters for employees. The insight: commuting is planned travel with validated enterprise budgets already allocated to parking, shuttles, and transit. Ridepanda now works with Amazon, Google, and County of San Mateo, achieving 5-15% employee adoption—triple San Francisco's 2-4% bike commute rate—with 85% being net-new riders who've never regularly used bikes or scooters before. Topics Discussed: Why shared micro-mobility's cost structure (rebalancing, charging, vandalism) made $0.55/minute pricing inevitable Targeting enterprise transportation teams versus mid-market HR benefits buyers as distinct ICPs Subscription economics: $50-$250/month with employer subsidies only triggering on employee sign-ups Converting non-riders to daily commuters: 85% adoption from people who previously didn't bike/scooter Enterprise-first strategy: going where dedicated teams and budgets already exist for employee transportation Vertical expansion into manufacturing, law firms, hospitals, and universities GTM Lessons For B2B Founders: Target existing budget holders, not net-new spending: Enterprises already fund parking facilities, shuttle services, van pools, and commuter benefits through dedicated transportation and facilities teams. Ridepanda didn't create a new expense category—they repositioned within existing line items. This meant selling to buyers with validated pain, allocated budget, and quarterly goals tied to employee transportation. When entering established markets, map where your solution fits in current spending patterns rather than forcing buyers to carve out new budget. Structure pricing to eliminate perceived risk: The subsidy only applies when an employee signs up—there's no upfront commitment or wasted spend on unused capacity. This removed the enterprise objection of "why am I paying when I'm not getting anything." For a new category where adoption rates are unproven, usage-based pricing aligned incentives and made pilots trivial to approve. When selling unproven solutions, architect your commercial model so the buyer's risk scales linearly with actual utilization. Segment ICP by buyer motivation, not just company size: Enterprise buyers (transportation/facilities teams) optimize for modal shift, carbon reduction, and getting employees out of single-occupancy vehicles. Mid-market buyers (HR/benefits managers) optimize for return-to-office adoption, wellness metrics, and benefits competitiveness. Same product, completely different value props and sales conversations. Don't assume company size determines buyer psychology—map the org chart to understand who owns the problem and what they're measured on. Attack broken unit economics, not just user experience: Lime's pricing increase from $0.15 to $0.55 per minute wasn't greed—it was fundamental business model failure. Shared services require rebalancing fleets, charging distributed assets, and absorbing vandalism/theft losses. Personal ownership via subscription eliminated every operational cost that made shared mobility unprofitable. When incumbents are struggling financially despite strong demand, the opportunity isn't better execution—it's a structural model shift. Prove behavior change at enterprise scale, not just product-market fit: Achieving 5-15% employee adoption when the city baseline is 2-4% demonstrates that subsidized access plus personal ownership drives 3x penetration. More critically, 42% daily usage from an 85% net-new rider base proves the model creates new commuting behavior rather than capturing existing cyclists. Enterprise buyers focused on emissions and modal shift care about conversion metrics, not vanity usage numbers. Define the transformation metric that proves you're changing behavior systemically, not incrementally. // 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

Positron AI is a 2+ year old silicon company targeting decode-heavy AI inference workloads where memory bandwidth, not compute, is the bottleneck. Launching end of 2025/early 2026, their architecture delivers 2TB of on-chip memory capacity versus Nvidia Rubin's 0.4TB—enabling 3-5x better performance per dollar and per watt for reasoning models, code generation, and video generation. In this episode, Mitesh Agrawal shares how Positron identified the memory bandwidth gap in a market where Nvidia controls 90%+ share, why they're prioritizing anchor customer commitments over product completion, and the hard lessons from Lambda Labs about rapid iteration and customer-driven optionality. Topics Discussed: Positron's technical approach: focusing on memory bandwidth and capacity over compute for inference workloads Why decode-heavy applications (reasoning models, video generation, code generation) are becoming memory-bound The challenge of selling silicon to hyperscalers when Nvidia controls 90%+ of the market Building optionality into product strategy: air cooling vs. liquid cooling as unexpected GTM advantage Learning to sell hardware before the product ships and why anchor customers matter Lambda Labs experience: lessons on rapid iteration and thoughtful hiring during hypergrowth Maintaining engineering-centricity: 47 of 50 employees focused on product development GTM Lessons For B2B Founders: Find technical bottlenecks in high-growth markets: Positron identified that memory bandwidth wasn't scaling as fast as compute, creating a bottleneck for inference workloads. While Nvidia dominates with 90%+ market share, they optimize for training revenue. B2B founders should analyze where dominant players are constrained by their own economics or existing roadmaps, then build specifically for those underserved segments. Markets default to oligopoly, not monopoly: Mitesh observed that customers actively seek alternatives even when one vendor is superior. "Markets want oligopoly structure to exist," he explained. B2B founders shouldn't be discouraged by dominant incumbents—customers want optionality for leverage, supply chain resilience, and risk management. Position yourself as the credible alternative in specific use cases. Discover optionality through customer conversations: Positron initially pitched performance per watt without realizing air cooling capability was a major advantage. Only after selling their first product did they learn customers valued deploying in existing data centers without infrastructure overhauls. B2B founders should systematically debrief early customers to uncover which features solve problems you didn't anticipate. Sell before shipping in hardware: The biggest priority between now and product launch is securing anchor customers willing to commit purchase orders. "If you have someone to build for, the fillip it gives the engineering team, the confidence it gives operations and supply chain vendors—we underwrite that," Mitesh emphasized. Pre-sales derisk production, prove demand, and create momentum. B2B hardware founders should treat early customer commitments as product validation, not just revenue. Build storytelling into technical sales: Convincing customers to buy unshipped hardware requires months of narrative work. "It becomes like, if I sell it to you, why will it be useful to you? Is it going to save cost? Attract new customers? Drive growth?" Success means co-creating the internal business case your champion will present. B2B founders should invest heavily in helping customers articulate ROI and strategic value before asking for commitments. Maintain rapid iteration cadence: Nvidia ships every 12-15 months versus the industry standard of 3-4 years. "If you tell me that in 10 years you've launched 10-12 products in silicon, I will give much more probability we will be successful," Mitesh stated. B2B founders should structure operations and product development for continuous iteration rather than big-bang releases, even in traditionally slow-moving industries. Delay non-engineering hires until product proves itself: With 47 of 50 people in engineering, Positron has consciously prioritized product over go-to-market. "It was a very conscious decision," Mitesh emphasized. For deep-tech companies, this focus ensures you can actually deliver before scaling sales. B2B founders should resist pressure to build balanced teams early—let roles emerge from real needs rather than theoretical org charts.     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

theion is developing lithium-sulfur battery technology targeting 500 watt hours per kilogram in their first commercial product—nearly double today's lithium-ion cells at 270-300 Wh/kg—with an ultimate roadmap to 1,000 Wh/kg. By replacing nickel-manganese-cobalt cathodes with crystalline sulfur and graphite anodes with lithium metal, theion aims to deliver three times the energy density at one-third the cost and CO2 footprint of current batteries. In this episode of BUILDERS, we sat down with Dr. Ulrich Ehmes, CEO of theion, to discuss how a production-focused CEO is navigating the journey from TRL 3-4 to pilot line, why they're targeting electric aviation first, and how a 12-year battery industry veteran evaluates what actually constitutes a materials breakthrough. Topics Discussed: Why sulfur cathodes and lithium metal anodes enable the performance jump beyond lithium-ion The critical importance of monoclinic gamma crystalline structure for cycle life  Navigating the transition from coin cells to pouch cells to industrialization  Strategic decision-making on initial market entry for deep tech hardware  Why process innovation in mixing and coating is required to unlock sulfur's full potential  Building a China-independent supply chain using oil refining waste  The 3-year development reality driven by cycling test requirements GTM Lessons For B2B Founders: Price your technology against value creation, not cost savings alone: Ulrich's market strategy centers on "markets which will pay a lot of money for super lightweight batteries"—specifically aviation applications where weight reduction directly enables business model viability. For eVTOLs, the constraint isn't battery cost but energy density; current batteries make many routes economically impossible. This is fundamentally different from cost-driven markets like consumer EVs where incremental weight savings have marginal value. Deep tech founders should map which customer segments face hard physical constraints that only your technology solves versus those seeking incremental optimization. The former will pay 3-5x premiums; the latter will demand cost parity from day one. Match CEO background to the company's primary risk: Ulrich led Leica's 600-person Portugal production facility for a decade before entering batteries, and he frames his value as "I'm a production guy...for me it's very important not to produce only one battery cell in a lab, but millions of cells in highest quality." For a battery company at TRL 3-4 moving toward industrialization, the existential risk isn't the science—it's whether you can manufacture at quality and yield. Many deep tech companies fail because PhD founders remain CEOs through manufacturing scale-up. Ulrich's hire signals that theion's board correctly diagnosed their de-risking sequence. Founders should brutally assess what will kill the company in the next 24 months and ensure the CEO's pattern recognition matches that failure mode. Seek investors where your technology is infrastructure for their thesis: theion's primary investor is "heavily invested in eVTOLs," making theion's battery technology directly relevant to multiple portfolio companies facing the same energy density constraint. This creates structural alignment on timeline expectations—eVTOL companies won't reach commercial scale before 2027-2028 anyway, matching theion's development cycle. The investor understands that battery development "takes time because always when you change a parameter, you have to cycle again to test the cells." This is radically different from a generalist VC expecting SaaS-like iteration speeds. Hardware founders should explicitly map how their technology unblocks other portfolio companies and use this to negotiate patient capital terms and strategic customer introductions. Use competitive landscape size as legitimacy signal, not differentiation: When pressed on disrupting incumbents, Ulrich immediately countered: "We are not the only company working on sulfur and this is good...there are 28 other companies out there." He then differentiated on "monoclinic gamma crystalline structure" validated by Drexel University achieving 4,000+ cycles. This is sophisticated category positioning: the 28 competitors validate that lithium-sulfur is a credible next-generation technology, while the specific crystalline approach provides technical differentiation for those who understand the chemistry. Founders should resist the urge to claim they're the only ones solving a problem in nascent categories—it raises "why hasn't anyone else tried this?" concerns. Instead, position within an emerging category and differentiate on technical approach. Communicate realistic timelines as competence signaling, not weakness: Ulrich states plainly that commercial availability is "at least the next three years" and frames this as doing "first things first and first things right." For sophisticated buyers in aviation and aerospace, compressed timelines signal naivety about certification requirements, manufacturing validation, and qualification testing. A battery company claiming 12-month commercialization would lose credibility with Boeing or Joby Aviation procurement teams who understand the actual development cycles. Deep tech founders should recognize that customer segments accustomed to long development cycles (aerospace, automotive, medical devices) interpret realistic timelines as domain expertise, while consumer/software buyers may interpret them as lack of urgency. Match timeline communication to buyer sophistication. // 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

CoreStory is building code intelligence platforms that address the fundamental limitation of today's coding agents: their inability to navigate complex enterprise codebases. While foundation models excel at greenfield development, they fail at real-world engineering tasks in systems spanning millions of lines of code. CoreStory's context layer delivers a 44% improvement on SWE-bench, the industry's standard benchmark for measuring coding agent effectiveness on actual GitHub issues. In this episode of BUILDERS, I sat down with Anand Kulkarni, CEO of CoreStory, to explore how his team is enabling the shift to AI-native engineering and seeding the category of spec-driven development across Microsoft, GitHub, and Amazon. Topics Discussed: Building with GPT-3 API 18 months before ChatGPT went public Why even GPT-5 and Opus 4.5 struggle with enterprise codebases on SWE-bench The narrative shift required when selling AI pre- and post-ChatGPT CoreStory's 44% improvement in coding agent performance through context intelligence How "spec-driven development" got adopted by Microsoft, GitHub, and Amazon without formal analyst relations The parallel between JIRA monetizing Agile and CoreStory enabling AI-native engineering Three-channel distribution: direct enterprise, coding agent partnerships via MCP, and hyperscaler/GSI routes Why specs become the source of truth while code becomes disposable in the AI era GTM Lessons For B2B Founders: Match your narrative precision to technical depth: CoreStory deploys three distinct positioning strategies based on audience sophistication. For AI practitioners tracking benchmarks, they lead with "44% SWE-bench improvement"—a metric that immediately signals meaningful progress on the hardest problem in the space. For engineering leaders aware of AI tooling but not deep in the research, they focus on velocity gains and ROI metrics. For executives, they describe reverse-engineering codebases into machine-readable specs. The key insight: technical audiences dismiss vague value props, while non-technical audiences get lost in benchmark details. Map your positioning to how your audience measures success in their world. Seed category language through earned adoption, not manufactured consensus: Anand initially called their approach "requirements-driven development" before simplifying to "spec-driven development." Rather than pitching analysts, they used the term consistently in customer conversations, gave talks at GitHub Universe, and shipped demos showing the workflow. When customers naturally adopted the language and community leaders began using similar terminology independently, Microsoft and GitHub followed with their own implementations (like GitHub's SpecKit). The lesson: category language sticks when practitioners choose to use it because it clarifies their work, not because a vendor pushed it. Focus on customer adoption as proof of concept before seeking broader market validation. Position against emergent practices, not just incumbent products: CoreStory doesn't position against legacy code analysis tools—they position as the enabler of AI-native engineering, the discipline that will displace Agile. Anand's insight from watching JIRA's success: "People don't love JIRA. What they love is Agile as a way to move away from waterfall." CoreStory is betting that 10x velocity gains from AI-native practices will drive the same categorical shift. When you're early in a technology wave, attach to the practice change (how teams will work differently) rather than feature comparisons with existing tools. Movements create markets. Design channel strategy around customer problem awareness: CoreStory's three channels map to different stages of buyer sophistication. Direct enterprise comes from teams already deep in AI engineering who've hit the context limitation wall. Coding agent partnerships (via MCP integration with tools like Cognition and Factory) serve builders wanting better AI tooling who haven't diagnosed the context problem yet. Hyperscalers and GSIs distribute into modernization and maintenance projects where AI enablement is emerging as a requirement. Each channel serves a distinct buyer journey stage. Don't force one go-to-market motion—design multiple paths based on where different customer segments are in understanding the problem you solve. Navigate pre-legitimacy markets by hiding the breakthrough: Before ChatGPT, selling anything AI-driven faced immediate skepticism about whether it was "real" or just smoke and mirrors. Anand couldn't lead with AI without triggering disbelief. CoreStory focused on delivered outcomes—"here's what you'll be able to do"—with AI as the mechanism, not the message. Post-ChatGPT, the challenge flipped: everyone expects AI, but now the differentiation question becomes harder. If you're building on emerging technology before market consensus forms, deemphasize the technology until buyers have context to evaluate it. Once the market validates the technology category, shift to demonstrating your specific technical advantage within it. // 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

Lula rebuilt property maintenance from the ground up by solving a fundamental problem: property managers spend 40% of their time coordinating maintenance with zero visibility into work order status. After pivoting from a B2C app when they discovered landlords were their actual users, Bo Lais and his team made a critical insight—deep PMS integration wasn't a feature, it was the entire go-to-market strategy. Today, Lula's 9,000-contractor network processes 1,000 work orders daily across 50 markets, performing 30 HVAC replacements per day at scale that enables direct manufacturer relationships. Now they're commercializing their internal tech stack as Foresight, a standalone SaaS platform launching Q1. In this episode of BUILDERS, Bo breaks down the strategic decisions behind building integrations as distribution, using network density to create pricing advantages competitors can't match, and knowing when to productize your internal tools. Topics Discussed: Why the B2C to B2B pivot happened after discovering usage patterns, not market research How PMS integration eliminated "swivel chair" friction and became the primary distribution channel Strategic partnership depth over breadth: enabling co-selling with AppFolio, Buildium, Yardi rather than partner proliferation The 250-door threshold where maintenance coordination breaks and technology becomes necessary Network density economics: 30 daily HVAC replacements creating leverage for direct manufacturer negotiations and flat-rate service catalogs The decision framework for commercializing Foresight based on upstream customer advisory group feedback Maintaining discipline around ICP when sales teams naturally want to expand GTM Lessons For B2B Founders: System of record integration is your distribution strategy, not a feature: Lula's standalone app created adoption friction because property managers refused to work outside their PMS. Bo's realization: "They need everything to live in their system of record...They don't want swivel chair. And then providing that real time visibility throughout the entire life cycle of the work order was really valuable because prior to that they assign it to a vendor, and then they cross their fingers and hope that it gets done." The integration solved both adoption friction and delivered continuous visibility their workflow demanded. For B2B founders: if your users live in Salesforce, HubSpot, or vertical-specific platforms all day, your integration strategy IS your distribution strategy—build there first, not alongside. Strategic partnerships require enablement infrastructure, not just signed contracts: Bo's approach rejects partnership sprawl: "It's not about stacking on another 10 partnerships, it's about how do we go deeper and enable those partners to co-sell with us and talk about the value props that together we can provide." This means building co-selling toolkits, joint value propositions, and partner success metrics. For B2B founders: one partnership where the partner's sales team actively sells your solution beats ten partnerships where you're just listed in a marketplace. Invest in making partners successful sellers, not collecting logos. ICP discipline requires sales team enforcement mechanisms, not just definitions: Lula knew their ICP but struggled with execution. Bo learned "it's one thing when we understood who our ICP was, but then it's a whole nother thing to adhere to that and get the sales team to adhere to that ICP." The specificity matters: residential (not multifamily), single-family, 250+ doors (where coordination breaks), capped at several thousand doors (before enterprise needs diverge). For B2B founders: document your ICP, but also build the compensation structures, deal approval processes, and CRM workflows that prevent sales from chasing deals outside the sweet spot—even when quota pressure hits. Message outcomes customers measure, not the technology delivering them: Bo's AI framing: "They care about the outcomes, right? If we're able to move the needle on the outcomes and provide a better experience for residents by automating communication, automating the time to schedule, automating the time to get resolution...it's not the how, it's the result." Lula's AI eliminates truck rolls through upfront troubleshooting and improves one-trip resolution rates—that's what property managers track. For B2B founders: if your customer's boss asks "how's that new tool working," they answer with metrics they're held accountable for (resolution time, truck rolls, resident satisfaction), not "it uses AI." Lead with those metrics. Productize internal tools when customer advisory groups request them and you have defensible advantages: Lula commercialized Foresight after upstream customers specifically asked for their tech during advisory sessions. Bo's competitive moat thinking: "Everyone else thinks they're going to do it better with the AI and automation they have. But our competitive moat is that our on-demand network is built inside this AI work order management system. And because of the scale of our network and the buying power, we can provide instant quotes for a lot of services...our competitors that are just doing software don't have this network of contractors nationwide." For B2B founders expanding product lines: customer pull plus operational advantages competitors can't replicate (Lula's contractor density, manufacturer relationships, 1,000 daily work orders of training data) create viable new products. Without both, you're just building undifferentiated software. // 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

Telo Trucks is reimagining the American pickup for dense urban environments. With over 13,000 reservations and plans to deliver their first vehicles in 2026, Telo is tackling one of the hardest challenges in business: starting an automotive company. In a recent episode of BUILDERS, I sat down with Jason Marks, CEO & Founder of Telo Trucks, to learn about the company's journey from building electric motorcycles to creating a mini truck that's 152 inches long—shorter than a Mini Cooper—but delivers the bed capacity of a full-size pickup. Topics Discussed: Pivoting from electric motorcycles to mini trucks after weekend street research revealed 89% preference for trucks Solving the safety engineering challenge of vehicles with no front overhang and minimal crumple zones Reaching unit profitability at 5,000 vehicles before attempting volume manufacturing Dual go-to-market strategy serving both urban consumers and commercial fleets replacing golf cart + truck combinations Navigating overlapping regulatory jurisdictions: NHTSA, EPA, CARB, IIHS, IICAR, and functional safety standards Running 100 virtual crash simulations daily using automated AI tools to accelerate safety validation Learning from 60+ failed automotive startups that rushed to high-volume manufacturing without proving fundamentals GTM Lessons For B2B Founders: Compress customer validation into concentrated research sprints: Jason spent one weekend conducting street interviews across LA and San Francisco—hitting sidewalks, motorcycle meetups, and car meets with concept drawings. 89% of respondents, including dedicated motorcyclists, pointed to the mini truck concept over the motorcycle Telo was building. This wasn't survey data or focus groups—it was showing drawings to real buyers in target markets and asking direct questions. B2B founders should design rapid validation sprints that test core assumptions with target buyers in their natural environment before significant capital deployment. Pivot immediately when validation data is definitive: Telo was in final partner meetings for their motorcycle fundraise when weekend research proved trucks were the opportunity. On Monday morning, they opened the VC call with "Stop. Before you say anything, we're pivoting 100% to mini trucks." The investors called back two hours later and committed. The lesson isn't just willingness to pivot—it's having the conviction to act on clear data even when it disrupts active processes. B2B founders should establish decision thresholds: what percentage of target customers pointing to a different problem would trigger a strategy change? Reverse-engineer failure patterns in your category: Jason systematically studied the 60+ automotive startup failures and identified the core pattern: raising massive capital ($100M-$1B+) created pressure to sprint toward high-volume manufacturing before proving unit economics or even delivering vehicles. Telo's counterstrategy is explicit: achieve unit profitability at 5,000 vehicles using one-tenth the capital of predecessors. This isn't generic "learn from failures"—it's forensic analysis of what killed companies and designing operational constraints that make those failure modes impossible. B2B founders should map the 5-10 companies that died in their category, identify the 2-3 recurring failure patterns, and build those constraints into their operational model. Announce vision publicly to surface latent demand: Telo launched with a full-size foam and fiberglass vehicle model in June 2023 targeting urban consumers. Commercial buyers—downtown construction companies, wineries doing urban delivery, city parks departments—immediately contacted them. These buyers were spending $80,000 combining golf carts for site work with full-size trucks for materials, creating maintenance nightmares. They needed one platform replacing both. B2B founders shouldn't just build in stealth—strategic public announcements surface buyer segments and use cases you didn't model, especially when your product solves problems in adjacent categories. Define unit economics constraints, then cascade all decisions from them: Telo's entire strategy works backward from one milestone: unit profitability at 5,000 vehicles. This constraint cascades: pricing structure, component COGS targets, manufacturing approach (low-volume vs. high-volume tooling), distribution model (direct vs. dealer), insurance program design. Every functional area has targets derived from the profitability constraint. B2B founders should identify their critical economics milestone, then explicitly cascade what must be true across pricing, CAC, gross margin, and operational efficiency to hit it—before building the go-to-market motion. // 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

Most AI founders race to raise capital, hire fast, and outspend the competition. Wen Sang did none of that. In this episode of the ProductLed Podcast, Wes Bush and Esben Friis-Jensen sit down with Wen Sang, CEO and co-founder of Genspark, the all-in-one AI workspace that went from zero to $100M ARR in 9 months and $155M ARR by month 10 with a team of just 50 people. Wen gets into why they refused to spend a dollar on marketing until they hit $100M ARR, how a last-minute Super Bowl ad opportunity landed in their lap and 10x'd their traffic overnight, and why he thinks Silicon Valley's "focus or die" advice is flat out wrong for AI companies. He also pulls back the curtain on the recursive learning system that keeps Genspark's output quality ahead of the pack, and makes the case for why building broadly is actually the safer bet when you're AI-native. Key Highlights: 02:20 - How a Team of Tech Veterans Decided to Rethink Work from Scratch06:02 - The Wildest Growth Timeline You'll Hear This Year12:26 - Why They Refused to Spend on Marketing Until $100M ARR14:24 - How Genspark Made a Super Bowl Ad in 10 Days (Using Genspark)20:40 - Why "Just Focus on One Thing" Is Bad Advice in the AI Era23:23 - How 50 People Ship Like a Team of 50029:12 - The Real Reason AI Companies Are Growing So Fast Right Now37:10 - Why Their Website Is Basically Just the Product42:21 - The Internal System That Keeps Their Output Quality Ahead of Everyone Else44:12 - All-In-One vs. Best-in-Class: Which Actually Wins?49:12 - What Wen Would Tell Every Founder Building in the AI Era Resources:

Qualytics is redefining enterprise data quality by positioning it as a collaborative business function rather than an isolated data engineering problem. Founded at the start of the pandemic by Gorkem Sevinc - a former CTO and CDO who spent years managing reactive data quality firefights - Qualytics emerged from a clear practitioner pain point: writing endless custom rules to catch data issues after they'd already broken dashboards and KPIs. The company raised pre-seed and seed rounds while building with beta customers, then closed a Series A as repeatability patterns emerged in their POC process. Now, as enterprises scramble to operationalize AI initiatives, Qualytics is experiencing explosive inbound demand from organizations realizing their data foundations aren't ready for democratized data access. Topics Discussed The practitioner insight that sparked Qualytics: reactive rule-writing doesn't scale Leveraging existing CTO/CDO networks and PE portfolio connections for beta customers The evolution from free POCs to paid POCs as a mutual commitment mechanism Identifying repeatability through week-by-week POC conversion patterns Building practitioner credibility into the sales motion while hiring for enterprise sales grit The decision to hire sales and marketing leadership simultaneously post-Series A Tracking in-product engagement metrics (DQ operations frequency, anomaly detection, rule editing) as churn prevention Positioning data quality as vertical-specific business problems (premium leakage, regulatory compliance) The timing advantage: AI adoption forcing enterprises to treat data governance as mandatory infrastructure GTM Lessons For B2B Founders Talk to 100 prospects before writing code—even with deep domain expertise: After burning 18 months building a radiology second opinion product that patients didn't want (they didn't even know radiologists were doctors), Gorkem adopted a hard rule: validate with 100 conversations before building. His advantage as a former CTO who lived the data quality problem created false confidence. Practitioners often assume their pain is universal, but buyer awareness and willingness to pay are separate questions. Start with NSF I-Corps-style problem validation: show rough sketches, probe what happened when they hit the pain point, understand how it hurt them financially or operationally. Repeatability appears in micro-conversions during trials, not just closed-won rates: Gorkem didn't declare product-market fit when deals closed—he declared it when he could predict POC behavior by week. "Week two, I'm expecting this. Week three, I'm expecting this." That predictability enabled ROI calculators and internal champion enablement materials. For technical founders, this means instrumenting your trial or POC to track leading indicators: specific features activated, data volumes processed, number of team members engaged, frequency of logins. When those patterns stabilize across prospects, you have a repeatable motion. Use paid POCs as a procurement front-loading mechanism, not a revenue play: Qualytics charges nominal amounts for some POCs—not for the revenue, but to get the MSA signed and force both parties through legal/security review upfront. This eliminates the pattern where free POCs succeed technically but die in procurement. Large enterprises often refuse to pay for POCs, which Gorkem accepts—but only if they commit equivalent effort (executive time, cross-functional teams). The paid POC is a qualification tool: if they won't commit anything, they're not a real opportunity. Hire sales and marketing leadership in parallel and hold them to unified GTM metrics: Gorkem regrets hiring early sales reps before leadership and delaying marketing investment. Post-Series A, he hired both leaders simultaneously and holds them jointly accountable to pipeline generation and velocity—not siloed MQL counts or quota attainment. This structural decision forces collaboration on messaging, ICP definition, and campaign strategy from day one. For technical founders who "figured out" founder-led sales, resist the urge to replicate your motion with more SDRs. Bring in strategic leadership that can build a scalable system. Instrument product engagement as your earliest churn signal—then intervene immediately: Beyond quarterly NPS and executive QBRs, Gorkem tracks granular product usage: how many data quality operations users run, how many anomalies they discover, how actively they're editing rules. When engagement drops, he doesn't wait—he jumps into the customer's existing weekly meetings to diagnose and course-correct. For B2B founders building complex products with long time-to-value, passive health scores aren't enough. You need active usage telemetry and a low-latency intervention process. Translate technical capabilities into vertical-specific business outcomes: Gorkem doesn't pitch "data quality for data engineers." He talks about premium leakage with insurance companies and OCC/SEC data controls with banks. This reframing works because buyers recognize their problem, not a vendor category. The shift requires research: understand each vertical's regulatory environment, operational pain points, and the business metrics executives care about. When you walk in speaking their language about their P&L impact, you're not another vendor—you're someone who gets it. Time your market entry to when "nice-to-have" becomes "must-have": When Qualytics launched, some enterprises called data quality a "nice-to-have." AI adoption changed that calculus overnight. Organizations planning to let 20,000 employees interrogate data through AI interfaces suddenly realized they need robust data governance, quality controls, and cataloging first. Gorkem's timing wasn't luck—he built during the "nice-to-have" phase so he'd be ready when AI budgets made it mandatory. Technical founders should identify the external forcing function (regulation, technology shift, economic change) that will transform their solution from vitamin to painkiller. // 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

Trener Robotics is solving a fundamental problem in industrial automation: the 5 million robotic arms deployed globally operate without intelligence, relying on 60-year-old procedural programming methods. With $38 Million in total funding—including a just-closed $32 Million Series A—the company compressed an 18-month journey from pre-seed to Series A by focusing ruthlessly on CNC machine tending. In this episode of Category Visionaries, I sat down with Asad Tirmizi, Founder of Trener Robotics, to unpack how 14 years of research in robotics and AI converged with market timing to create what judges recognized as this year's biggest innovation in machining—despite the founding team having zero machining expertise. Topics Discussed: Why Trener Robotics chose CNC machine tending over higher-visibility applications like airplane cleaning The capital efficiency trade-offs between sales cycle length, development complexity, and runway Partnering with three of the five largest robot OEMs controlling 4.3 million of 5 million deployed units Expanding to six countries (Norway, Denmark, Sweden, Portugal, Spain, US) through integrator networks Converting technical curiosity into closed deals in a risk-averse industry with 60-year-old workflows Building training materials in Portuguese for markets the founding team has never visited GTM Lessons For B2B Founders: Sales cycle length determines survival, not TAM size: Trener Robotics rejected compelling applications with massive TAM like airplane cleaning because sales cycles would burn through runway before reaching scale. Asad was explicit: "If your sales cycle is too long, your funding is too less and your development time is too much, that's it, you're out of business." They chose CNC machine tending specifically because manufacturers already budget for robots, understand ROI calculations, and have existing vendor relationships. Calculate your actual time-to-close from first meeting to signed contract, multiply by customer acquisition cost, and build your runway model around that reality—not the TAM slide in your deck. Niche dominance beats horizontal expansion every time: Despite having technology capable of 100+ applications, Trener Robotics committed to machine tending exclusively. Asad's framework: "Making 100 skills is easy. Distributing 100 skills, maintaining 100 skills, marketing hundred skills—that's where most startups break when scaling, not when incubating." The constraint forced them to become the definitive solution for one workflow, enabling repeatable sales motions and concentrated marketing spend. Most founders intellectually agree with focus but fail operationally—they take revenue from adjacent use cases "just this once." Don't. Pick your beachhead, win it completely, then use that cash cow to fund expansion. Industry awards are underutilized credibility hacks: Trener Robotics won the Machine Tool Innovation Award—the machining industry's most prestigious recognition—despite being roboticists with no machining background. This wasn't luck. They studied what innovations historically won, trained their models on data that would produce award-worthy results, and positioned the submission around industry pain points. The award opened OEM partnership conversations that would have taken years otherwise. Identify the 2-3 awards that matter in your category, reverse-engineer what wins, and build your product roadmap accordingly. Third-party validation converts skeptical enterprise buyers faster than any sales deck. Channel partner economics need structural win-win design: Trener Robotics secured partnerships with three of the five largest robot OEMs (controlling 86% of deployed units globally) by solving a specific problem: OEMs sell hardware but lose recurring revenue to system integrators who program robots. Trener Robotics' AI models let OEMs capture software subscription revenue while reducing integrator programming costs. Asad acknowledged they're still learning: "I would not by any stretch of imagination say we have proven how good we are in managing channel partners. It's a journey we are on." But the structural economics work because both sides make more money. When designing channel programs, don't just offer margin points—restructure the value chain so partners access new revenue pools they couldn't capture before. Interest signals are worthless without conversion timeline mapping: Asad's painful admission: "Interest does not mean sales. Pilots do not mean sales. Even letter of interest or contracts to test your equipment does not mean sales." As a technical founder, he initially conflated technical validation with buying intent. The fix: obsessively measure time between interest signal and closed deal, then segment by customer type, deal size, and decision-maker level. Only after mapping this could they accurately forecast and avoid the "too much time in the gray area of interest turning to sales" trap. Build a conversion funnel that tracks days-in-stage, not just stage progression percentages. // 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

Brian Whorley, Founder and CEO of Paytient, is rebuilding healthcare's broken payment infrastructure. Paytient enables employers and insurers to front healthcare costs for members who repay over time, interest-free. The company now serves 6,000 employers and powers payment solutions for nearly half of America's 50 million Medicare seniors. In this episode of BUILDERS, Brian reveals his counterintuitive GTM pivot from employers to insurers, why he testified before Congress on healthcare affordability, and how to build in highly regulated markets without fighting the system. Topics Discussed: Why healthcare lacks functional buyer-seller dynamics and transparent pricing The World War II tax quirk that prevents employers from giving healthcare dollars directly to employees Cash market case studies: Why LASIK prices decreased in real terms since 1998 while maintaining quality improvements Paytient's unexpected discovery that insurers were better strategic partners than employers Congressional testimony before the House Committee of Oversight and Government Reform on December 10th The company's evolution from founder-led employer sales to insurance-first distribution strategy Launching self-serve for sub-200 employee companies while closing Fortune 100 accounts How Medicare regulations requiring prescription payment flexibility created a 50-million-person market GTM Lessons For B2B Founders: Test enterprise distribution earlier than your assumptions suggest: Brian assumed Paytient needed a million users before insurers would engage. Instead, one of the nation's largest insurers partnered early because they recognized out-of-pocket costs as a critical experience gap they couldn't solve internally. The insurer's product team understood the problem but lacked control over member finances. When building in complex ecosystems, large strategic partners may engage earlier than expected if you solve a problem outside their core capabilities. Prioritize partners with longer planning horizons: Brian discovered insurers planning 2027-2029 health plans in early 2025, while employers focused on last month's challenges. This planning horizon difference fundamentally changed Paytient's GTM strategy. Insurers became the majority of their business because they could "invest and reshape for the long term" as part of broader strategy. When choosing between customer segments, prioritize buyers who think strategically over those managing tactical, short-term needs—they'll invest in solutions before acute pain points emerge. Regulatory tailwinds can create massive distribution overnight: A law passed four years after Paytient launched required all Medicare insurers to offer exactly what Paytient provides—prescription cost flexibility with insurer-fronted payments. This regulation instantly created a 50-million-person addressable market. Brian now powers this for "almost half the country." When building in regulated industries, track pending legislation that could mandate your solution category, creating instant distribution through compliance requirements. Build different GTM engines for concentrated vs. fragmented markets: Healthcare is "a very concentrated industry" at the top 40 insurers, where Paytient focuses enterprise efforts. For the fragmented small business market (under 200 employees), they launched a self-serve platform at patient.com this month, immediately gaining traction with venture-backed employers seeking simple subscriptions. The dual-motion approach—high-touch for concentrated markets, self-serve for long-tail—maximizes coverage without burning capital on inefficient sales motions. In trust-based sales, delivery quality drives expansion velocity: When Paytient launches with a Fortune 100, "tens of thousands of people have access to patient now." The benefits stack is "sacred and sacrosanct"—a trust-based, relationship-driven sale. Brian emphasizes the product must work "exactly how you said, even better" because performance creates referrals through benefit brokers and consultants. In high-stakes enterprise deployments, your product quality directly determines sales velocity through partner and customer networks. Navigate regulatory constraints as creative boundaries, not barriers: Brian's core advice for healthcare founders: "You have to work with the system as it is." Many founders approach healthcare "as antagonist" with solutions "too foreign or too different" that threaten the status quo. Instead, innovate within existing regulatory and operational frameworks. There are "plenty of space" and "data requirements for how healthcare can work today" to build billion-dollar businesses while respecting industry structure. Fighting the system guarantees slow adoption; working within it enables scale. // 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

Autonomize AI is transforming healthcare infrastructure by eliminating administrative waste and reimagining how health enterprises operate. Covering 150 million of the 330 million lives in the United States and powering three of the five largest health enterprises, Autonomize AI has found traction by solving healthcare's hardest problems first. In this episode of BUILDERS, we sat down with Ganesh Padmanabhan, Founder & CEO of Autonomize AI, to explore how he built an AI platform from the ground up for healthcare—not by retrofitting existing technology, but by immersing himself in the industry's unique challenges and building solutions that address the fundamental inefficiencies plaguing the system. Topics Discussed: The origin story of launching during COVID with conviction around unstructured data Landing the first enterprise customer with a PowerPoint and prototype before writing production code The evolution from clinical trial patient matching to powering major health enterprises Why solving the hardest problems first created faster traction than targeting easy wins Building credibility as an outsider by leveraging past successes and being honest about failures The distinction between building AI for healthcare versus building AI from within healthcare Scaling from a $10,000 pilot to multi-million dollar ARR with deep customer immersion Why healthcare is fundamentally a trust equation, not a technology problem The future vision of an AI-native health enterprise operating system GTM Lessons For B2B Founders: Don't write code until you have a signed deal: Ganesh didn't write production code until securing his first enterprise customer. He used a compelling pitch deck and an expensive prototype stitched together from cloud solutions to demonstrate feasibility. Once the deal was signed at $150,000 annually, they built the sustainable version while delivering value with the prototype. This approach validated real demand before significant investment. Solve the hardest problem, not the easiest one: Counterintuitively, Autonomize AI found faster traction by tackling the most difficult challenges in healthcare. Ganesh explains, "The simplest way to actually get traction, solve the hardest problem that's out there. If you do that and you can actually solve it...if the problem is big enough for them to move, they will." Hard problems often have fewer competitors and more desperate buyers. Wait for pattern recognition before scaling: Ganesh knew he had a business when the second and third customers requested exactly what the first customer bought. He waited for this repeatable pattern before raising a seed round, ensuring he wasn't just solving one customer's unique problem but addressing a genuine market need. Immerse deeply in one customer before broad expansion: Autonomize AI spent 12 months becoming better experts on their first major enterprise customer's systems than the customer's own internal teams. This deep penetration transformed a $10,000 pilot into millions in ARR and provided invaluable learning that shaped their entire platform approach. The investment in one relationship paid exponential dividends. Build from the industry, not for the industry: Ganesh's advice is clear: "Don't build AI and bring it into healthcare. Come into healthcare and build the AI." Most companies fail by retrofitting technology into healthcare's nuanced environment. Success comes from immersing yourself in the specific industry, understanding its unique constraints and trust requirements, then building solutions from that foundation. Leverage past credibility through specific storytelling: As an industry outsider, Ganesh built trust by sharing concrete past successes: growing Dell's convergent infrastructure business from zero to $1.3 billion in five years, working with major healthcare clients in previous roles. He also shared failures openly, creating authentic credibility. He notes, "People learn more from their successes than from their failures...you learn what to do then what not to do." // 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

Woody Klemetson scaled sales from 100 people at Divi to 350 at Bill.com post-acquisition, then walked away to build something harder: infrastructure for hybrid AI-human revenue teams. At AskElephant, he's tackling the problem that every revenue leader faces but few can articulate—how to actually implement AI in revenue operations when your systems weren't built for it. With zero marketing spend, AskElephant hit 400% growth through pure referral motion and converts 85% of pilots to production (versus single digits industry-wide). Woody breaks down why most "AI-ready" companies aren't, how to structure pilots that actually ship, and what it takes to hire sellers who orchestrate agents instead of relying on armies of support staff. Topics Discussed: Post-acquisition culture collision: the cost of moving too fast versus too slow Why "AI readiness" is usually one person at a company, not the organization  The 27-agent CRM system that delivers 5% forecast accuracy without human input  Revenue outcome systems as category evolution: solving for predictability across disconnected tools  Pilot-first GTM that converts at 85% by starting with one-minute-per-day wins  Partner-led distribution through consultants evolving from slideware to implementation  Hiring ops-minded sellers who code: over half of non-engineers using Cursor daily  The PLG expansion coming in 2025 and why traditional demand gen is getting tested alongside door-to-door GTM Lessons For B2B Founders: Culture integration requires explicit deceleration early: Woody's team assumed Bill.com wanted their aggressive startup velocity immediately post-acquisition. They didn't slow down to map cultural differences, causing "whiplash" across 350 people. The specific mistake: not creating space to understand Bill's processes before challenging them. Even when acquired for your approach, the first 90 days should be listening and mapping, not executing. Only after understanding their system can you effectively challenge and merge cultures. This applies whether you're acquiring or being acquired—the cultural work is non-negotiable and front-loaded. Diagnose AI readiness by system documentation, not enthusiasm: Most companies think they're AI-ready because leadership wants AI. Reality check: if your teams haven't documented their systems and processes, AI has nothing to learn from. AskElephant starts some customers with basic dictation—not because it's revolutionary, but because it's the prerequisite to anything meaningful. The diagnostic question: "Walk us through your current customer journey." If the answer is "we have sales stages," you're not ready for automation. You need documented systems before AI can execute them. Start by having AI observe and document before it acts. Build agents incrementally to compound context: AskElephant runs 27 different CRM agents that collectively deliver 5% forecast accuracy. This wasn't built in one sprint—it took 40 hours of training and context-building. Each agent handles a specific job: contact creation, data enrichment, ICP scoring, churn monitoring, stage updates. The misconception founders have: AI should work perfectly from the first prompt. The reality: you build agents brick by brick, each one learning from the previous context layer. This is why their forecasting works—because 27 agents watching different signals together create accuracy that one "smart" agent can't. Pilot conversion at scale requires deliberately small scope: Single-digit pilot-to-production rates happen because teams scope too big. AskElephant's 85% conversion comes from "dream big, implement small." First pilot: automated CRM notes. Then: notes humans wish they'd written. Then: automated field updates. Each step saves minutes, builds trust, proves value. Woody's framework: if you're not saving one minute per person per day in your first pilot, you've scoped wrong. The goal isn't to wow with ambition—it's to ship something that works perfectly, then expand from proven trust. Their customers average 27 hours saved per week per person, but none started there. Revenue outcome systems emerge from tool sprawl failure: Every revenue leader uses 15-20 disconnected tools trying to make revenue predictable. The category insight isn't "operating systems"—it's that companies care about outcomes, not operations. AskElephant's positioning: we focus on the outcome (predictable revenue), not just the operating infrastructure. This distinction matters because it shifts the conversation from technical plumbing to business results. When creating categories, find the frame that makes the buyer's problem visceral and your solution inevitable, even if you're solving similar problems as others in the space. Partner-led GTM turns consultants into distribution: AskElephant's entire growth came through partners: Salesforce/HubSpot consultants becoming AI strategists, sales coaches extending from training to implementation. The unlock: these partners needed a way to deliver lasting value beyond slideware. Previously, a coach would train your team and leave. Now they implement AI systems that hold teams accountable to the training, creating longer engagements and better outcomes. For founders: identify services providers whose business model gets dramatically better by incorporating your product. They become your sales force because you make them more valuable to their clients. Hire for orchestration capability, not pure sales skill: Over half of AskElephant's non-engineering team uses Cursor daily. Woody hires "ops-minded" and "tech-minded" sellers who can manage AI agents alongside human work. The old model: silver-tongued seller + solutions engineer + 27 support people. The new model: one seller orchestrating 27 AI agents. These reps don't build lists, don't create SOWs, don't write product scopes, don't need SEs for demos. But they still need human connection skills—listening, curiosity, presence. The hiring filter: can this person think in systems and implement technical solutions while maintaining high-touch relationships? If they can't code enough to orchestrate agents, they can't scale in this environment. // 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

Identity fraud spiked 148% in 2025 as AI democratized identity fabrication. Financial institutions now face a fundamental question: Are you dealing with a real human? Heka Global is addressing this with web intelligence—analyzing digital footprints like connected applications rather than traditional signals. In this episode of BUILDERS, I sat down with Idan Bar Dov, Co-Founder & CEO of Heka Global, to explore how his company created a fourth layer in the anti-fraud stack and why legacy identity verification systems are becoming liabilities rather than assets. Topics Discussed:  The emergence of "fraud as a service" and why consumer-facing attacks replaced traditional enterprise breaches  How web intelligence works: validating identity through connected applications and digital footprints  The anti-fraud tech stack: credit bureaus, biometrics, transaction analytics, and web intelligence as distinct layers  Why heads of fraud expand budgets rather than replace vendors, and what causes solutions to get kicked out  The partnership sales model: navigating vendor management complexity and red tape in financial institutions  Why 10-person dinners and fraud simulations outperform traditional enterprise marketing  How Barclays and Cornerback backing solved the chicken-and-egg problem for a data product  Why specific fraud prevention messaging (account takeover, synthetic identities) beat investor credibility GTM Lessons For B2B Founders: Target ICP based on liability exposure, not just industry fit: Heka narrowed beyond "financial institutions" to lenders who bear immediate losses from fraud—companies like LendingPoint, Avant, and Upstart. These buyers feel the pain acutely versus institutions with reimbursement terms who can deflect liability. Idan's insight: "We need the client to feel the pain just as much as we see it. That means we want them to see the liability." Map your ICP not just by vertical or size, but by who internalizes the economic impact of the problem you solve. Frame your product as a new stack layer, not a competitive replacement: Heka positioned web intelligence as the fourth distinct layer after credit bureaus, biometrics, and transaction analytics. This became their second pitch deck slide, showing logos of each category. The result: buyers stopped comparing Heka to existing vendors and started evaluating complementary value. When entering mature markets, resist the urge to claim you're "better than X"—instead, define where you fit in the existing architecture and why that layer didn't exist before. Abandon spray-and-pray for sub-1,000 TAM markets: Heka tested Lemlist flows with targeted LLM personalization and saw zero pipeline from it. Idan's take: "When you're selling to maybe a thousand financial institutions, that's it. You can be super specific when you target them." For enterprise plays with small addressable markets, allocate zero budget to automated outbound. Focus entirely on warm introductions, relationship nurturing, and becoming known to every relevant buyer through content and community. Leverage investor networks to break data product cold-starts: Data products face a critical barrier—you need customer data to prove value, but need proven value to get customers. Heka solved this by bringing on Barclays and Cornerback as investors who vouched for the team's capability to "do magic and create a new layer." Their backing convinced risk-averse financial institutions to pilot. If building a product requiring customer data for training or validation, prioritize strategic investors who can credibly de-risk early adoption for target buyers. Build trust through teaching, not pitching: Heka hosts dinners and fraud incident simulations with ~10 heads of fraud per session. Critical detail: they never pitch Heka in these forums. Idan explained the approach focuses on "building a community around Heka and how people engage with your product and you being a thought leader while listening." In high-trust categories, educational forums where you facilitate peer learning without selling create stronger pipeline than direct pitching. Structure partnerships with active enablement and incentive alignment: Idan's key lesson: "Partnerships are not synonymous to distribution channels." Heka requires partner sales teams to join early customer conversations to learn the pitch, provides detailed API and output training, and ensures partners get extra compensation for selling non-core products. Without this, partners lack motivation to prioritize your solution. Structure partnerships as true collaborations requiring ongoing enablement investment, not passive referral channels. A/B test credibility signals versus technical specificity: Idan assumed messaging around Barclays backing would crush, while specific fraud prevention content (account takeover, synthetic identity detection) was an afterthought. The data showed 10x better response to technical specificity. The lesson: sophisticated buyers in technical categories respond to precise problem-solving over brand credibility. Test whether your audience values "who backs us" or "exactly what we do" before defaulting to investor logos and validation. //  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

Portnox is an enterprise access control platform that eliminates passwords and enforces zero trust security. The company was bootstrapped for over a decade, plateauing at a few million in ARR before investors brought in Denny LeCompte as CEO four years ago. Since then, Portnox has grown 8x. But this episode isn't about that growth story. Denny, a former cognitive scientist and professor who taught psychometrics, uses his scientific background to systematically dismantle Net Promoter Score—explaining why it's methodologically flawed, how it misleads organizations, and which metrics actually correlate with business performance. This is a contrarian take grounded in measurement science, not marketing opinion. Topics Discussed: The fundamental psychometric flaws in NPS: why single-item questionnaires are unreliable and why throwing out 7s and 8s violates basic statistical principles How NPS scores fluctuate based on survey UI presentation independent of actual customer sentiment Why NPS creates incentive structures that encourage gaming rather than improving customer outcomes The case for gross revenue retention and net revenue retention as the only ungameable metrics that matter How measuring human behavior changes that behavior (the Heisenberg principle applied to business metrics) Why investors care about retention rates above 90% but don't ask about NPS scores GTM Lessons For B2B Founders: Single-item questionnaires violate measurement principles: Denny's background in psychometrics immediately flagged NPS as unreliable. One-item measures lack the redundancy needed for reliability, and the methodology of throwing out middle responses (7s and 8s) then subtracting detractors from promoters is statistically nonsensical. At a previous company with thousands of data points, he observed NPS scores drop and rise based solely on how the survey rendered on the page—no business changes, just UI differences. When presentation affects your metric independent of the underlying construct, your instrument is broken. Founders with technical backgrounds should trust their instincts when measurement methodology feels scientifically unsound. Compensation drives behavior more than metric accuracy: Portnox structures customer success compensation as 50% gross revenue retention and 50% net revenue retention. These are determined by finance and can't be manipulated. Denny had to rein in his CS team when they became overly focused on time-to-value because any number you give a team becomes their obsession. With NPS, teams game survey timing, cherry-pick recipients, and optimize for score rather than outcome. This is the Heisenberg principle applied to business: measuring changes the behavior. Choose metrics where gaming the number aligns with improving actual business outcomes. Investors evaluate retention rates, not satisfaction surveys: When Denny presents gross retention above 90%, investors don't ask about NPS. Renewal behavior reveals actual satisfaction—customers voting with budget rather than survey responses. The test for any metric: "What are we doing differently if this number is up versus down?" If it doesn't drive distinct actions or reveal information not already visible in financials, eliminate it. NPS often becomes a number that exists because "we've always measured it," inherited from previous leadership without questioning its utility. Question inherited practices ruthlessly: NPS gained adoption through Harvard Business Review credibility in 2003 and consulting firms building practices around it. The promise of "one number you need" appeals to executives wanting simple solutions. But herd behavior—"everyone else measures it"—perpetuates bad methodology. Denny's advice to founders stuck with NPS: give your team something else to focus on (gross retention is straightforward: don't let customers churn), then stop doing it. Sometimes you need to point to external validation to break internal momentum. The question isn't whether NPS correlates somewhat with growth—it's whether better alternatives exist that can't be gamed. // 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/53yCHlPLSMFimtv0riPyM

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

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

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

Civ Robotics is automating construction layout—the process of translating blueprints into physical markers on job sites—using autonomous ground robots instead of traditional surveying crews. Founded by civil engineer Tom Yeshurun after he spent $2 million on a four-person surveying team for a single project, Civ has scaled from initial concept to deploying robots across the United States, Australia, Europe, and the Middle East, with 12 robots currently operating in Saudi Arabia alone. In this episode, Tom breaks down his tactical approach to product-market fit, why he pivoted from aerial drones to ground vehicles based on customer feedback, and how he's building sales teams by recruiting construction professionals rather than traditional sales reps. Topics Discussed: How Tom identified the construction layout automation opportunity while managing $120-500 million infrastructure projects The two-year pivot from aerial drones to ground robots after target customers cited safety concerns Market differences between Israel and the US: subcontracted surveying firms versus in-house EPC operations Converting tier-one contractors like Bechtel and Primoris through persistence and geographic proof points The product development framework: one request = document, two requests = build, three requests = should be done Transitioning from paid digital ads to SEO/AIO optimization with measurable improvements in inbound quality Using AI workflows to audit website metadata and align content with buyer personas instead of investor messaging Sales hiring strategy: grooming construction engineers into customer success and sales roles versus hiring pure sales talent International expansion through remote deployment and a LinkedIn-driven sale that generated 12 robots in Saudi Arabia Product roadmap from layout automation to machine guidance and full construction equipment autonomy GTM Lessons For B2B Founders: Interview customers in your actual target geography, not just accessible markets: Tom built his initial prototype after interviewing Israeli and European companies, but the US market operates fundamentally differently—EPCs like Bechtel and Primoris handle surveying in-house due to volume, while Israeli EPCs subcontract to surveying firms. This changed the buyer persona, sales motion, and value proposition entirely. When he finally interviewed US companies, the feedback was immediate and actionable. Don't optimize for interview convenience—validate where you plan to sell. Let technical decisions be customer-driven, not engineering-driven: Tom's team spent two years developing an aerial drone solution because it was technically more complex and exciting for engineers. Three early adopters said they liked the concept but feared the drone—if it was ground-based, they'd reconsider. Tom scrapped two years of development and rebuilt for ground vehicles. His takeaway: bring both options to target customers before committing development resources. Engineering preferences create technical risk; customer preferences create market risk. Use the "one-two-three rule" for product prioritization: Tom's framework eliminates guesswork in product roadmaps: one customer requests a feature, document it; two customers request it, begin development; three customers request it, it should already be shipped. This prevents building "cool features" that product managers or engineers want but customers don't need, and ensures development resources map directly to revenue opportunities. Deploy proof before the pitch to collapse enterprise sales cycles: When a major contractor asked if Civ's robot could handle Texas mud, Tom responded that they already had a robot deployed "literally a mile away" on an adjacent project. That proximity proof turned a Wednesday discovery call into a Monday deployment, followed by a one-month trial and conversion to a customer now running 15 robots. For hardware or complex B2B sales, having operational deployments near prospects eliminates the biggest objection: "will this actually work in our environment?" Position yourself as a peer, not a vendor: Tom doesn't introduce himself as CEO or founder in sales conversations—he leads with his background as a civil engineer and field engineer who managed the same types of projects his buyers manage. This reframes the conversation from vendor-buyer to peer-to-peer, making it easier to discuss pain points candidly. In technical industries, domain credibility matters more than sales technique. If you lack it personally, your customer-facing team must have it. Audit your website metadata as a conversion optimization lever: Tom discovered his road robot product page was showing solar farm videos in link previews because metadata wasn't optimized per product line. His team systematically reviewed every page's metadata, primary content, and video assets to ensure alignment with the specific buyer viewing that page. This granular optimization improved inbound quality measurably. Most B2B companies ignore metadata entirely—it's a high-leverage, low-effort fix. Hire from industry for sales, hire generalists for marketing: Tom's board challenged him to "duplicate himself" as the company's best seller. His answer: recruit former construction project managers and field engineers who already communicate effectively and understand buyer pain points, then train them on sales process. For marketing, the talent pool with construction automation experience is too small, so he hired a generalist. This isn't about industry knowledge being unimportant—it's about recognizing where domain expertise is essential (customer-facing) versus learnable (content creation). Create reciprocal value loops with influential customers: One customer produces professional-quality content about Civ's robots because showcasing innovation differentiates him with his own clients. Tom reciprocates by cutting the subscription price by 50%, explicitly framing it as "you're a great influencer and helping us spread the word." This relationship generated Civ's Saudi Arabia opportunity—12 robots sold—when the customer's LinkedIn post drew a comment from a prospect. Identify which customers benefit from being seen as early adopters, then structure commercial terms that reward amplification. // 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 Meta Description: Tom Yeshurun, Co-Founder & CEO at Civ Robotics, shares his framework for product-market fit, hiring construction pros into sales roles, and scaling robotics deployments internationally on BUILDERS.

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

Dug Song and Jon Oberheide are the co-founders of Duo Security.If you've never heard of Duo, it might be one of the most underrated software stories of all-time.Starting in 2010, they burned only $14 million to hit $100m in ARR, were acquired by Cisco for $2.35 billion in 2018, and now rumored to be doing over $1 billion in ARR inside Cisco 16 years later.We talk about how they built one of the most capital efficient SaaS companies ever from Ann Arbor, Michigan, and how their focus on the customer and company culture helped them win in a crowded cybersecurity market.We talk growing up in the early hacking culture of the 90s, why most security tools are painful to use, sizing their market, solving for non-consumption of a product, and how Duo flipped the model by designing for end users instead of security teams.We talk about staying in Michigan instead of moving to Silicon Valley, and why staying out of the tech bubble helped them execute.We break down the mechanics of scaling from zero to $100 million in ARR, everything they learned integrating with Cisco, and why more founders should build outside of San Francisco. A quick thank you ex-Duo employees Zack Urlocker, Ash Devata, and Katie Kilroy for their help brainstorming topics for the conversation.Try Numeral, the end-to-end platform for sales tax and compliance: [https://www.numeral.com](https://www.numeral.com/)Sign-up for Flex Elite with code TURNER, get $1,000: https://form.typeform.com/to/Rx9rTjFzTimestamps:(4:49) Meeting from Dug's Wi-Fi honeypot(7:33) 90's hacking culture and cybersecurity's wild west(14:49) How the internet was born in Ann Arbor(18:58) Staying in Michigan instead of moving to Silicon Valley(31:20) Philosophy on leadership and team building(39:48) What makes a good engineering leader(44:01) Starting Duo to make security easier(45:22) Why most security products suck(48:36) How fixing account takeover became a $1B ARR company(59:10) TAM, competition, fixing the non-consumption of security(1:04:04) Being a radical advocate for the customer(1:08:35) Duo's pizza sales play(1:12:45) Branding lessons from Anthropic, Tesla, Cliff Bar(1:17:47) When to say no to customers(1:21:27) Importance of culture when scaling(1:27:56) Duo's role in uncovering the SolarWinds breach(1:31:29) Scaling to $100M ARR on $14M burned(1:39:30) Inside the $2.35B Cisco acquisition(1:44:02) What big companies get wrong about customers(1:51:53) Building Michigan's startup ecosystemReferencedDuo Security: [https://duo.com](https://duo.com/)Cisco: [https://www.cisco.com](https://www.cisco.com/)University of Michigan: [https://umich.edu](https://umich.edu/)Follow DugTwitter: https://x.com/dugsongLinkedIn: https://www.linkedin.com/in/dugsongFollow JonTwitter: https://x.com/jonoberheideLinkedIn: https://www.linkedin.com/in/jonoFollow TurnerTwitter: https://twitter.com/TurnerNovakLinkedIn: https://www.linkedin.com/in/turnernovakSubscribe to my newsletter to get every episode + the transcript in your inbox every week: https://www.thespl.it/

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

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

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

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

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

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

In this episode, we're joined by Roeland Delrue, Co-founder of Aikido Security, the fast-growing application security platform that just became a unicorn in under 4 years.  Roeland shares what it really takes to scale a company at breakneck speed, from going 5× year-over-year, to balancing startups and enterprise in one GTM motion, to raising a Series B with a single goal: becoming “unignorable.” We unpack how Aikido uses product-led growth, brutal revenue focus, and buyer-first sales mentality to win in one of the most competitive markets in SaaS. We spoke with Roeland about building for continuous wins, why revenue clarity beats buzzwords, and how Aikido joins the buyer's journey instead of forcing rigid sales methodologies. Here are some of the key questions we address: How did Aikido grow from $5M to $20M+ ARR in one year? What does it mean to build an unignorable company? Why brutal focus on revenue simplifies product, hiring, and prioritization decisions Why joining the buyer's journey beats forcing MEDDICC-style sales processes How product-led trials reduce churn and increase win rates What it takes to scale from unicorn to decacorn (and why $100M ARR is the next real milestone)

Confirm uses organizational network analysis to surface hidden high performers and toxic actors that traditional performance reviews miss - identifying the quiet contributors everyone relies on and the problematic employees who manage up effectively. In this episode of BUILDERS, I sat down with David Murray, Cofounder & CEO of Confirm, to dissect their most painful go-to-market lessons. David shares why leading with methodology superiority torpedoed their early sales, the specific discovery framework that flipped their win rate, and how they segment the four distinct HR buying motions that require completely different sales approaches. Topics Discussed: Why traditional performance reviews are 60% manager bias according to research by Maynard Goff How organizational network analysis identifies introverted high performers and manages-up toxic actors The catastrophic early GTM mistake: positioning against existing processes Discovery frameworks for conservative buyers in compliance-heavy functions Talk ratio targets and silence techniques from clinical psychology applied to enterprise sales Channel testing methodology that identified LinkedIn ads as their primary acquisition driver The four-quadrant framework for HR sales: CHRO vs line manager, company-wide vs HR-only tools Messaging strategies that balance shock factor with substantive education GTM Lessons For B2B Founders: Discovery trumps differentiation in category creation: Confirm's design partner had promoted toxic employees and lost quiet high performers in the same cycle—a perfect case study for their ONA methodology. But when they pitched other HR leaders with "here's why your approach is broken," they hit walls. The shift: stop selling methodology, start diagnosing pain. Reference what you've observed at similar companies—"Some folks at your size tell us they struggle with X, is that true for you?"—then let prospects surface their version of the problem. Only after they've articulated their pain do you map your differentiated approach to their specific context. Target buyer timing, not just buyer titles: Confirm identified a specific trigger: HR leaders in their first 1-2 months at a new company. These leaders are hired to make change and need early wins. The outreach question: "How are you looking to make your mark?" This surfaces whether they're hungry for innovation or managing political capital. A newly hired CHRO has different motivations than a 5-year veteran protecting their process choices. Map your outreach to career timing, not just seniority. Enforce 50/30/20 talk ratios in discovery: David's target: prospects speak 60-80% of discovery calls, with 50% being acceptable. If you're talking more than half the time, you're pitching, not discovering. The clinical psychology technique: positive encouragers ("yeah," "huh") plus deliberate silence after open-ended questions. Prospects will fill silence with the real issues—budget constraints, political dynamics, past vendor failures. This intel is gold for multi-threading and objection handling later. Test channel-message fit with minimal spend: Confirm's approach: "do everything a little bit and see what sticks." They found LinkedIn ads with precise targeting (title, company size, recent job changes) delivered qualified pipeline cost-effectively, while other channels didn't. The framework: allocate 10-15% of budget across 5-6 channels for 60 days, measure cost-per-qualified-meeting, then concentrate spend. Plan for 3-6 month creative refresh cycles as audiences develop ad fatigue—this isn't set-and-forget. Map your product to the HR buying matrix: David identifies four distinct quadrants: (1) CHRO buyer, company-wide deployment = traditional enterprise sale, 6-18 month cycles, heavy multi-threading required; (2) CHRO buyer, HR-only tool = shorter cycles but still executive selling; (3) Line manager buyer, company-wide = requires bottom-up adoption mechanics; (4) Line manager buyer, HR-only = SMB-style transactional sale. Confirm operates in quadrant 1—the longest, most complex sale. Most founders don't explicitly map which quadrant they're in, leading to mismatched sales motions and blown forecasts. Use provocative messaging with technical substance: "One-click performance reviews" generated meetings because it triggered both excitement (managers hate writing reviews) and concern (is AI replacing human judgment?). The key: the shock factor gets the meeting, but you need depth on the call. Confirm's explanation: the AI aggregates data from Asana, Jira, OKRs, peer feedback, and self-reflections to reduce recency bias, then generates a draft managers edit. The dystopian concern becomes a feature when you explain the data anchoring. Surface-level shock without technical credibility burns trust. Adjust for organizational risk tolerance by function: HR and healthcare share conservative buying cultures due to compliance, documentation, and legal requirements. David contrasts this with selling to CTOs or engineers who "kick tires and want to break things." This affects everything: longer evaluation cycles, more stakeholders in legal/compliance, emphasis on security and data handling, reference checks weighted heavily. If you're selling to risk-averse functions, adjust your content (white papers, compliance documentation), your timeline expectations, and your change management positioning. Reframe education as extraction, not instruction: David's mental model shift: "I need to learn from them" replaced "I need to educate them." In practice: "I've heard from others that calibration meetings consume 10+ hours per cycle with unclear outcomes. They tried approaches like forced ranking or manager-only decisions. Have you experimented with either?" This positions you as a pattern-matcher across their peer group, not a lecturer. They become receptive to alternatives because you've demonstrated you understand their world through other customers' experiences. // 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

CalmWave is tackling ICU alarm fatigue—a problem where patients generate up to 1,600 alarms per day because clinicians lack data-driven guidance on setting vital sign thresholds. The company processes 32 million data points daily from a single 14-hospital system by fusing high-frequency vital signs from Philips InteliBridge with EMR data from Epic in real time. This represents 10 billion data points annually at current run rate. Ophir Ronen, a sixth-time founder who previously sold to PagerDuty, built CalmWave by applying enterprise IT operations patterns to healthcare infrastructure. The company secured its first comprehensive system-wide agreement within months of launch and now holds 51 patents with 20 more pending as medical device manufacturers pursue distribution partnerships. Topics Discussed Why middleware interoperability is a prerequisite for clinical safety, not a feature  The technical challenge of fusing 10x more data from vitals systems than EMR systems  Building trust through transparent AI that exposes mathematical reasoning to clinicians  Scaling from 7 million to 32 million daily data points across hospital rollout phases  How CalmWave's common signal format enables data scientists to work with clean datasets  Positioning alarm fatigue as a beachhead into broader hospital operations platforms  The innovation investment arm validation pathway for startup enterprise sales  Extending the signals-incidents-events pattern to energy, defense, and manufacturing GTM Lessons For B2B Founders Interoperability becomes your moat when it's a safety prerequisite: CalmWave couldn't provide safe alarm recommendations using only vital signs data without knowing which medications had been administered that could affect those vitals. This forced them to build bidirectional integration with both Philips InteliBridge (high-frequency vitals) and Epic EMR before addressing the clinical problem. The integration layer itself—which normalizes, enriches, and structures data into their common signal format—became defensible IP. Ophir noted that high-frequency vitals data is "erased on a rolling 30-day basis" at most hospitals, making CalmWave's fused dataset genuinely novel. Founders in healthcare or other regulated industries should identify whether data fusion across siloed systems is required for safety or efficacy, then build that integration capability as core infrastructure rather than expecting customers to solve it. Transparent AI sells better than black box AI in clinical environments: When presenting to 30 senior leaders including a notoriously difficult CMO, CalmWave walked through the mathematical basis of their algorithms—demonstrating exactly how they calculate safe alarm threshold adjustments. The CMO stood up mid-presentation and said, "You guys shouldn't even call yourselves AI. This is math and statistics. I understand exactly what you're doing. Well done. This is truly innovative." This validation from clinical leadership came from showing the work, not from accuracy metrics alone. Founders selling AI into risk-averse environments should build explainability into their core product architecture, enabling clinicians to understand why each recommendation is generated rather than treating interpretability as a post-hoc feature. Innovation investment arms provide validation pathways that bypass procurement: CalmWave's breakthrough came when an innovation investment arm from a major health system reached out after three months of due diligence, then placed them in front of clinicians. Two weeks before signing a comprehensive system-wide agreement, they presented to the C-suite. This pathway avoided traditional vendor procurement cycles. The innovation arm acted as internal champion, pre-validating the startup's approach before exposing them to decision-makers. Founders targeting large healthcare systems should identify which organizations have dedicated innovation or venture arms, recognizing these groups are measured on finding novel solutions rather than minimizing vendor risk. Beachhead problems in enterprise must be urgent enough to overcome startup friction: Ophir explicitly chose alarm fatigue because health systems with IT budgets in the hundreds of millions needed "something compelling enough to make them engage" with a startup. ICU alarm fatigue has regulatory scrutiny, patient safety implications, and nursing burnout consequences that create executive-level urgency. The problem was important enough that clinical leadership would tolerate the integration complexity and vendor risk of working with an early-stage company. Founders should evaluate beachhead opportunities not just by market size but by whether the pain point has organizational consequences severe enough to justify betting on an unproven vendor. Adjacent domain pattern recognition creates non-obvious competitive advantages: CalmWave's team came from building large-scale operations platforms at PagerDuty, where they developed expertise in processing massive streaming data, correlating events, and reducing alert noise. They recognized that ICU alarm fatigue followed the same structural pattern as IT operations alarm fatigue—too many alerts without context. This allowed them to apply a proven architectural approach (signals → alarms → incidents → events) to a new vertical where healthcare incumbents lacked that specific systems thinking. One hospital generates 7 million data points daily; their platform now handles 32 million across multiple facilities. Founders with deep operational expertise in one domain should actively map their architectural patterns to adjacent verticals where incumbents haven't solved analogous problems at scale. // 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

Amplio operates a two-sided marketplace that helps manufacturers monetize surplus inventory and decommissioned industrial equipment rather than writing off assets or paying for disposal. The company has won contracts with GM and SpaceX despite competing against liquidators with 30-year local relationships. In a recent episode of BUILDERS, we sat down with Trey Closson, Co-Founder and CEO of Amplio, to unpack how the company executed a complete business model pivot from supply chain risk software to marketplace, discovered that enterprise deals close faster than SMB despite conventional wisdom, and built repeatable GTM motions in a fragmented $100B+ market previously dominated by local operators. Topics Discussed: Executing Amplio's pivot from supply chain risk software to surplus inventory marketplace Moving four truckloads of inventory through a WeWork to prove the business model Closing GM and SpaceX inbound from Google Ads as the PMF validation signal Displacing 30-year incumbent relationships through corporate + local dual threading Why enterprise contracts closed faster than SMB deals in Amplio's specific context Scaling beyond founder-led sales to repeatable AE motions Operating a two-sided marketplace: supply acquisition strategy vs. demand conversion GTM Lessons For B2B Founders: Manual heroics prove economics before automation: When a customer offered Amplio $25 million in surplus inventory, Trey had no warehouse, no logistics infrastructure, and no playbook. What was supposed to be four pallets became four full truckloads delivered to their WeWork. Trey and one employee physically moved inventory boxes off pallets into their office space, then figured out how to sell it while the WeWork management threatened eviction. The core insight: "the first time solving a problem, it doesn't need to be an automated, efficient process, it just needs to be okay. A customer has a problem, we need to figure out a way to solve that problem." Only after proving they could profitably solve the problem multiple times did they invest in automation and efficiency. For founders, the implication is clear—delay infrastructure investment until you've manually proven unit economics and repeatability, even if execution requires unsustainable effort. True PMF signals come from zero-relationship wins: Trey leveraged 15 years of supply chain relationships to secure initial customers and build product infrastructure. But he identifies the precise PMF inflection point: "middle of last year, we had both GM and SpaceX respond to a Google Ad." These companies had zero connection to Trey or his co-founder, found Amplio through SEM, and chose them over traditional liquidators they'd worked with for years. This is the distinction between "my network will buy from me" and "the market will buy from us." Founders should use their Rolodex to achieve velocity and prove the concept, but recognize that true product-market fit only exists when customers with no founder relationship choose your solution over established alternatives. Enterprise velocity depends on payment direction and urgency profile: Amplio deliberately focused on enterprise after being told by multiple founders to avoid "hunting whales." They discovered enterprise closed faster than SMB for three structural reasons. First, SMBs had unrealistic recovery expectations—wanting $900K back on $1M inventory when market reality is cents on the dollar, creating unresolvable expectation gaps. Second, enterprises had the problem across 100+ facilities with no dedicated owner and urgent mandates from finance or supply chain leadership. Third, because Amplio pays customers rather than charging them, legal review velocity increased dramatically. As Trey explains: "the lawyers thankfully determine, because we're not getting paid by them, that there's low risk for them in terms of signing a contract with us." Founders should map their specific deal structure and customer urgency profile rather than defaulting to SMB-first based on generic advice. Displace entrenched relationships through dual-threading: The surplus liquidation market is hyper-fragmented with hundreds of thousands of local liquidators, many holding 30-year plant-level relationships. Amplio's breakthrough: "partnering together with that person at the corporate level we can indicate not only can we solve the problem locally, but we can also do it across the entire enterprise." They pair the local plant manager with corporate procurement or finance leadership, demonstrating local problem-solving plus enterprise-wide scalability that local liquidators cannot match. This dual-threading strategy neutralizes the incumbent's relationship advantage while showcasing the efficiency and consistency that corporate leadership values. For founders entering relationship-driven markets, identify the corporate stakeholder whose enterprise-wide objectives trump individual facility loyalty. Accelerate trust through predictable execution in low-NPS markets: Industrial liquidation is a "really low NPS industry—nobody loves working with their liquidator." In markets with poor customer satisfaction and commoditized offerings, trust accelerates when you focus on "say-do ratio"—if you commit to something, execute it. Amplio often solves adjacent problems outside their core offering and frequently removes inventory from warehouses faster than economically optimal to make customers "look like an absolute hero." This over-delivery in low-satisfaction markets creates disproportionate differentiation. The tactical implementation: understand what problems the organization is trying to solve beyond your core product, find ways to solve those problems even if not monetizable, and prioritize making your champion successful over optimizing every transaction. // 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

i6 Group is connecting the fragmented aviation fuel ecosystem-airlines, fuel suppliers, and service providers-through a real-time digital platform that eliminates paper-based processes at over 260 airports worldwide. After launching with British Airways at Heathrow in 2015 and recently closing their Series B with German PE firm Itrium, i6 is proving that even heavily regulated, risk-averse industries can achieve step-function operational improvements through software. In this episode of BUILDERS, Alex Mattos, CEO and Managing Director of i6 Group, breaks down how they navigated decade-long enterprise sales cycles, leveraged strategic customers as Series A investors, and are now building toward profitability to maximize exit optionality. Topics Discussed: The surprising analog nature of aviation fuel operations despite advanced aircraft technology i6's pivot from defense fuel system testing to commercial aviation digitization The multi-party fuel ecosystem: airlines, suppliers, service providers, and logistics chains Strategic approach to landing British Airways and Virgin Atlantic as launch customers Fundamental differences between European fuel optimization vs. US supply chain management models Multi-stakeholder enterprise sales involving fuel teams, flight ops, pilot unions, and CFOs Strategic Series A with customer-investors: British Airways, JetBlue, Shell, and World Fuel Services Series B transition from strategic to PE backing focused on scaling operations and go-to-market Network effects driving compounding value as airport coverage expands Path to self-sustainability and exit strategy considerations GTM Lessons For B2B Founders: Target brand DNA, not just budget, for early enterprise customers: i6 deliberately approached Virgin Atlantic because of Richard Branson's reputation for "being entrepreneurial, taking a risk, doing something different." This wasn't naive brand worship—it was strategic targeting based on organizational risk tolerance. When selling complex infrastructure to enterprises pre-product-market fit, a prospect's innovation track record matters more than their budget size. Map your early pipeline based on cultural willingness to partner with startups, not just technical fit. Invest in non-paying reference customers as currency for tier-one deals: Virgin Atlantic became i6's first operational deployment without payment. This wasn't charity—it was strategic capital allocation. The working reference at Virgin directly unlocked British Airways: "we turned up, demonstrated what we were doing...we've done this trial with Virgin and here's the results, and it went really well." For founders selling to conservative enterprises, one live deployment at a credible brand is worth more than a dozen pitch decks. Budget 6-12 months of runway for strategic pilots that generate proof points, not revenue. Create forcing functions with specific follow-up commitments: When British Airways said "if you're still here in six months, come back," most founders would hear soft rejection. Alex heard a calendar commitment and returned "to the day" with results. This precision signaling—we take your requirements seriously enough to track them to the day—separates serious vendors from tire-kickers. When enterprises set conditional bars, treat them as binding contracts and demonstrate execution discipline through exact follow-through. Position for market disruption by maintaining warm enterprise relationships: i6 benefited when an incumbent competitor liquidated, creating urgent procurement needs at British Airways. But luck favors the prepared—they had already established credibility through their Virgin deployment. Maintain enterprise relationships even when deals seem stalled. In concentrated B2B markets, competitive exits, budget releases, and trigger events happen regularly. Your position in the consideration set when disruption hits determines whether you capture the opportunity. Engineer word-of-mouth in concentrated industries through excellence, not marketing: Four months after Heathrow deployment, Dubai airport approached i6 unsolicited: "we've heard great things." In the aviation fuel community—which Alex describes as "surprisingly small"—exceptional execution travels faster than any outbound motion. This changes GTM strategy: in concentrated industries, over-invest in customer success and operational excellence at early deployments rather than spreading thin across many accounts. Your first customers are your sales team. Segment GTM by operational model, not just geography or company size: i6 discovered European airlines optimize for fuel efficiency and real-time decisions, while US airlines (controlling their own supply networks since the late 1980s) prioritize supply chain visibility: "how much fuel did we put in the plane, how much have we had delivered, how much have we got left." These aren't feature preferences—they're fundamentally different jobs-to-be-done driven by market structure. Don't assume global enterprises have unified needs. Segment by operational model and regulatory environment, then customize messaging and roadmap accordingly. Stage investor expertise to match company evolution, not just valuation milestones: Series A brought strategic investors who were actual users (British Airways, JetBlue, Shell, World Fuel Services) for product validation and network access. Series B brought PE firm Itrium for "scaling the business...building and growing our sales and revenue teams." This wasn't opportunistic—it was deliberate staging of capital sources to match capability gaps. Don't optimize fundraising purely on valuation or dilution. Map your next 18-month bottleneck (product validation vs. operational scaling vs. market expansion) and raise from investors who've solved that specific problem. Build for profitability to control your exit timing and terms: Alex's goal is avoiding Series C entirely: "we build and establish a fully self-sustaining business...the business becomes fully sustainable in the next couple of years." This isn't conservatism—it's strategic optionality. Reaching profitability eliminates the forced march toward subsequent rounds, letting you choose between IPO or M&A based on market conditions rather than cash position. For infrastructure plays with long implementation cycles, factor sustainability into your growth model early, even if it moderates topline growth rates. // 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

Supersede manufactures structural building products from recycled industrial and agricultural plastic waste, creating drop-in replacements for plywood and OSB. What makes their approach notable isn't the environmental mission - it's the deliberate market sequencing strategy that let them reach the top 10 boat builders globally within months of launch. CEO and Co-Founder Sean Petterson, whose father died on a construction job and who previously built and sold a construction safety equipment company, knew the construction market's reputation for slow adoption would kill them before they could prove their product. So instead of pitching the $12B+ annual US construction market directly, they started with marine applications where regulatory pressure, product toxicity issues, and performance failures created urgent buying windows. In this episode, Sean breaks down how they used trade show metrics to validate product-market fit, why they're absorbing shipping costs to prove regional demand before building plants, and the operational art of scaling manufacturing capacity against pipeline conversion timing. Topics Discussed: Strategic market entry: why marine and RV serve as proving grounds and revenue generators before construction How material properties (waterproof, high density, VOC-free) dictated target application selection The regulatory catalyst: California's formaldehyde ban creating electrolysis problems in boat transoms Trade show execution at IBEX Tampa: converting sustainability pavilion traffic into top 10 builder partnerships Multi-plant expansion strategy: Phoenix for marine, Indiana for RV proximity to Elkhart manufacturing hub The timing challenge: balancing capex on new production lines against uncertain customer adoption curves Using shipping cost absorption as market validation before committing to regional manufacturing Product thickness decisions and the constraint of running 24/7 production on single SKUs Long-term infrastructure goal: lights-out factories in every state to hit 10% US market share GTM Lessons For B2B Founders: Map product attributes to urgent pain points, not general market needs: Sean's framework was ruthlessly specific—Supersede's material is waterproof, twice as dense as wood, VOC-free, and has superior fastener retention. Rather than positioning these as generic benefits, they mapped each attribute to acute pain: marine grade plywood costs 3-4x more, leaches formaldehyde and CCAs into water, and California's new regulations were causing electrolysis that corrodes aluminum transoms. This isn't marketing positioning—it's matching physics to procurement urgency. Founders should inventory their product's fundamental characteristics and find markets where each one solves an active crisis. Use expensive distribution as a validation tool before infrastructure investment: Supersede services Florida boat builders from their Phoenix plant despite shipping costs destroying margins. This is intentional—they're paying for market intelligence. Only after customers move from single units to full product lines do they commit manufacturing capex to that region. Sean's calculus: "As long as we have enough comfort in the unit economics to manage shipping costs, we can explore how markets look before sinking too much in." Most founders optimize for margin too early. Supersede optimizes for learning, treating distribution costs as cheaper than building the wrong plant in the wrong location. Create credibility through extreme durability testing, then cascade down: Sean describes pontoon boats with twin 300hp motors hitting 60mph over waves as their "value proposition crucible." This isn't about marine market success—it's about creating an unarguable proof point for every downstream market. When they enter construction, they won't debate whether their product can handle a roof load; they'll show years of data from conditions that make construction look gentle. The insight: win in the most punishing environment first, then every easier application becomes a layup. Most founders do the opposite—start easy, then struggle with credibility when moving upmarket. Sequence markets by sales motion similarity, not revenue size: The marine-to-RV-to-construction path isn't about market size—it's about operational leverage. Sean notes RV has "the same exact process, except they move a little quicker" as marine. Both are concentrated geographies (marine in Florida, RV in Elkhart), both have OEM buyers making high-volume decisions, both value durability and water resistance. This lets them reuse sales playbooks while building revenue. Construction, despite being 10x larger, requires completely different distribution (retail + wholesale), longer approval cycles (two years for major projects), and more diverse buyer personas (contractors, architects, developers, retailers). The sequencing strategy funds the capability build they'll need for construction without the distraction of learning three different GTM motions simultaneously. Treat trade shows as validation metrics, not lead generation: Supersede tracked specific conference-provided data at IBEX: highest searched booth, highest saved, most traffic despite being in the "sustainability pavilion" that attendees typically skip. They didn't just collect business cards—they validated that their value proposition resonated at scale before committing to a multi-plant buildout. Sean converted this signal into partnerships with all top 10 builders by volume within the show cycle. The lesson: use trade shows as market research tools with quantifiable success metrics, not as top-of-funnel activities. If you can't win a trade show in your target segment, you're not ready to scale. Balance production constraints against customer optionality to force prioritization: Supersede faces a counterintuitive challenge—they have demand for multiple product thicknesses but can only run 24/7 production on one thickness per line to maintain efficiency. This forces brutal customer prioritization decisions. As Sean puts it: "Which customer we like better." Rather than viewing this as a problem, recognize it as a focusing mechanism. Resource constraints force you to choose customers who value your core offering most rather than customizing yourself into complexity. Most founders try to serve everyone before proving they can serve anyone exceptionally. // 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

Introducing Revenue Meta—a new series by The Edge Podcast spotlighting DeFi protocols that actually generate cashflows and return value to tokenholders.There aren't many protocols that can answer the simple question: How does your business make money? We're starting with Maple Finance, where CoFounder & CEO Sid Powell breaks down their revenue model, treasury management, and path from $30M to $100M ARR.In this episode:+ How Maple generates revenue through over-collateralized lending+ Revenue allocation: treasury management, buybacks, and building strategic reserves+ The roadmap to $100M ARR and how they grow their loan book* Why Maple is a pure token play, no hidden equity, all value flows to SYRUP holders------

Parable is building an end-to-end intelligence platform that quantifies how organizations spend their collective time—the foundation for measuring real AI impact. With a thousand data connectors ingesting activity and log data across the enterprise software stack, Parable constructs proprietary knowledge graphs that size opportunities and measure outcomes in hard dollars, not adoption metrics. In this episode of BUILDERS, I sat down with Adam Schwartz, Co-Founder & CEO of Parable, to explore why 95% of CFOs see no AI ROI, how his decade running profitable businesses under resource constraints shaped his focus on inputs over outcomes, and why 2026 requires moving AI from CapEx experimentation to measured OpEx. Topics Discussed: Why the 95% CFO stat on AI ROI matters as an arbiter of truth, despite backlash Building knowledge graphs from activity data to quantify collective time allocation across hundreds of people The fundamental problem: enterprises lack quantitative frameworks for operational efficiency pre-AI Running parallel ICP experiments to achieve sales-market fit before product-market fit Why Parable has never lost a POC once leaders see quantitative baselines Market dynamics creating false signals—unprecedented curiosity without buying intent The demarcation between companies treating AI as product work versus those waiting for vendor solutions Why AI transformation demands century-old management structures to be questioned GTM Lessons For B2B Founders: Engineer disqualification in momentum markets: Market-wide AI enthusiasm creates pipeline illusion. Prospects will engage indefinitely for education without purchase intent. Adam's framework: "How do we get people to say no to us and not drag us along... They want to keep talking because they want to learn and they want to know what's going on and they are genuinely interested." In enterprise sales during category shifts, build explicit qualification gates that force prospects to reveal resource commitment or disqualify. Extended evaluation cycles feel like traction but destroy unit economics. Use go-to-market as ICP discovery mechanism: Adam intentionally pursued multiple customer segments simultaneously—different company sizes and AI maturity stages—to let data reveal fit rather than rely on hypothesis. His memo to the team: "We're going to go after these three, you know, many different sizes of companies in order for us to decide like, who we like best." The key insight: get to problem-market fit and sales-market fit validation before optimizing product-market fit. This inverts conventional wisdom but works when TAM is massive and the bottleneck is identifying who feels pain acutely enough to buy now. Qualify on organizational structure, not verbal commitment: Every enterprise claims AI is strategic. Adam's hard filter: "Who in the organization is responsible for AI transformation? And if you don't have a one person answer to that question, you're not serious." Serious buyers have a named owner reporting to C-suite with dedicated budget and team. Buying Gemini, Glean, or other point solutions isn't a seriousness KPI—it's often passive consumption of AI as a byproduct of existing software relationships. Look for companies doing five-year work-backs on industry transformation and cascading effects on their operating model. Target post-experimentation, pre-scale buyers: Adam discovered the sweet spot isn't companies beginning their AI journey—it's those who've deployed initial programs and now need to prove value. "The market of people that have started to build AI into their operating model or into their strategy in like a coherent way, there's a team, there's an owner, there's budget... those are the people that we really want to be talking to." These buyers understand the problem viscerally because they're living it. They do product work daily—talking to stakeholders, generating use cases, building briefs, triaging roadmaps. They need your solution to professionalize what they're already attempting manually. Build measurement into your category narrative: The AI tooling market has over-indexed on soft efficiency claims that won't survive renewal cycles. Adam's warning: "There is too much hand waving around soft efficiency gains... you're going to have to renew and you need NRR and I don't think it's going to be that usage of the tool internally by employees and adoption is going to be enough." The last decade over-rotated to "everything drives revenue" due to VC pressure. This decade requires precision: does your product save time, reduce headcount needs, or accelerate revenue? Quantify it. Partner with measurement platforms if needed. Adam's insight on Calendly is instructive—it clearly saves time, but most buyers can't quantify how much, which weakens renewal economics. // 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

Chef Robotics has produced 80 million meals—more than all other food robotics companies combined. The company has cracked what dozens of well-funded startups couldn't: profitable deployment of AI-enabled robots in food manufacturing. In this episode of BUILDERS, Rajat Bhageria, Founder and CEO of Chef Robotics, reveals why he focused on manufacturing before restaurants, how a single contract term change accelerated his sales cycle, and why the food assembly problem requires intelligence that traditional automation can't provide. This is category creation in real-time, with expansion to Germany and the UK planned for 2026. Topics Discussed: Why 60-70% of commercial food labor is in assembly, not cooking or prep The systematic failures of B2C robotics companies (Zume) versus B2B approaches (Miso Robotics) Chef's manufacturing-first strategy to build training data and field operations scale Why six-axis robots with vision outperform gravity-fed dispensers for food variability Reframing contract structure from "site acceptance test" to "trial" for faster closes Trade show strategy: multiple robots across partner booths, not just your own The economics of robotics-as-a-service in traditionally capex-driven industries GTM Lessons For B2B Founders: Validate unit economics before building in hardware: Rajat secured early contracts before engineering anything. This wasn't just customer validation—it was economic validation. He identified that robotics companies fail when "they're trying to charge a human salary, but they're not able to provide the full set of tasks that a human is able to do in an eight hour shift." By selling first, Chef confirmed customers would pay for assembly automation specifically, not a general-purpose kitchen robot. For hard tech founders: pre-selling de-risks both product-market fit AND your business model assumptions. Target the labor concentration point, not the obvious automation opportunity: While competitors automated cooking (low labor intensity), Chef mapped the entire food production workflow and discovered assembly consumed 60-70% of labor hours. Rajat's insight: "One person can cook for 100 people or a thousand people. So even though the cooking process can take a while, you're amortizing it over a lot of people." This workflow analysis revealed where ROI actually existed. Founders should map labor distribution across their customer's entire operation, not just automate the most visible or technically interesting task. Build your moat through training data and field operations density: Chef's manufacturing focus isn't just about easier sales—it's strategic infrastructure. Rajat explained: "Today, Chef has done 80 million meals...If we can be really good at food manipulation, we have the biggest data set of training data...as we build more robots, our bill of material gets lower...We have people all over the country servicing these robots, which obviously those same people can service robots in restaurants." For AI-enabled hardware, your moat compounds through deployment volume, not just product features. Reframe risk through contract structure, not just pricing: Chef's breakthrough wasn't discounting—it was renaming their "site acceptance test" to a "trial." Rajat described the impact: "Literally exactly the same thing. It's kind of like you go to your Google Doc and you replace all SAT into trial. That has an immense impact on the sales velocity." The cognitive reframing transformed how buyers perceived commitment risk. For founders selling novel technology: audit your contract language for terms that trigger buyer risk aversion, even when the underlying mechanics protect them. Trade show ROI multiplies through partner booth placement: Rather than maximizing their own booth presence, Chef places robots in partner booths across the trade show floor. Rajat noted this approach yields more deal closures because "the champions saw the thing at the trade show." This isn't about lead volume—it's about removing skepticism. Manufacturing buyers don't believe flexible automation exists until they see it operating. For hard tech companies: distribute proof points across the physical spaces where your skeptical buyers already congregate. Customer success IS your market education strategy: In a nascent category with a "graveyard" of failed predecessors, Chef's market education relies entirely on reference customers. Cafe Spice scaled from 4 to 16 robots and now hosts prospective customer visits. Rajat's approach: give exceptional pricing to customers willing to become advocates. The conversion rate from a skeptical prospect visiting a working deployment far exceeds any other marketing channel. For category creators: your unit economics on early lighthouse customers should account for their sales force value, not just their revenue. // 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

F2 is the AI platform for private markets investors, automating due diligence and portfolio monitoring workflows with agentic AI. After building ARK into a digital banking platform that scaled from tens of millions to tens of billions in loan volume, Donald Muir developed AI technology to automate debt placement on ARK's marketplace. When upmarket institutional lenders requested access to the AI for their entire deal flow—not just ARK's marketplace deals—Donald recognized the technology's standalone value. In this episode of BUILDERS, Donald shares how he's commercializing enterprise-grade AI for an industry where he personally spent years in the private equity bullpen, and how F2 is addressing the reliability and trust barriers that prevent AI adoption in high-stakes financial decision-making. Topics Discussed How F2 emerged from ARK's internal need to automate debt marketplace screening memos The technical approach to eliminating hallucination in Excel-based financial analysis Replicating private equity's "super day" interview format to prove AI capability with live deal data Sales team composition: hiring ex-finance professionals instead of traditional sales reps AI's role in evolving private equity analysts from menial tasks to system operators Product roadmap from due diligence to portfolio monitoring to deal syndication platform Maintaining operational independence while preserving strategic alignment with ARK GTM Lessons For B2B Founders Solve your own hardest problem first, then productize: Donald built F2's core technology to scale ARK's debt marketplace, focusing on the most difficult engineering challenge—reliable financial analysis of unstructured Excel data—because the marketplace required it. This resulted in technology that foundation models still haven't replicated over a year later. The aha moment came when institutional lenders wanted the AI for all their deal flow, not just marketplace transactions. Organic internal development created category-leading capabilities and validated product-market fit before commercialization. B2B founders should identify which internal operational challenges, if solved, could become standalone products serving the broader market. Design sales processes that mirror how your ICP evaluates talent: Donald replicated private equity's "super day" format where analyst candidates receive a data room, laptop without internet access, and three hours to produce an LBO model and investment thesis. F2 runs identical timed tests—customers send live deal data rooms under NDA, F2 generates investment committee memos using their templates, and presents same-day results. This proves the AI can perform at the standard funds use to evaluate human analysts they hire 18 months before start dates. B2B founders selling into industries with rigorous talent evaluation processes should reverse-engineer those frameworks into product demonstrations that speak to buyer expectations. Prioritize credibility over sales experience in technical markets: Donald's entire sales team consists of ex-finance professionals who lived in the seat—no traditional salespeople. These reps can screen-share investment memos created that morning and discuss them authentically with MDs and principals using industry-specific language. After 4.5 years running go-to-market at ARK, Donald teaches sales methodology to domain experts rather than teaching domain expertise to salespeople. For deals averaging half a billion dollars flowing through the platform, buyer credibility outweighs sales polish. B2B founders in specialized verticals should evaluate whether domain fluency or sales pedigree matters more for their specific buyer personas and deal complexity. Engineer for auditability before optimizing for speed: F2 focused on eliminating hallucination and achieving mathematical accuracy—solving what Donald calls the "reliability and trust" gap—before addressing workflow efficiency. The company name references the F2 keystroke used to audit Excel calculations at 3 AM in the PE bullpen. This positioning directly addresses the barrier preventing AI adoption for investment decisions: LLMs hallucinate, can't do math, and lack auditability. Only after proving the AI produces auditable, trustworthy output did F2 layer on speed benefits. B2B founders building for high-stakes decision environments should identify the fundamental trust barrier and make it the core technical focus before feature expansion. Leverage institutional knowledge as competitive differentiation: Beyond automating existing workflows, F2 enables firms to pipe in decades of institutional knowledge via API—instantly benchmarking new deals against thousands of historical transactions by vertical, revenue size, leverage levels, and management quality. This transforms screening memos from isolated analyses into context-rich evaluations informed by complete firm history. The AI doesn't just work faster; it has comprehensive context that individual analysts manually searching SharePoint folders could never access. B2B founders should identify where accumulated institutional data creates compounding value beyond point-in-time automation. // 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

Hubble Network is redefining what's possible in satellite connectivity by connecting standard Bluetooth chips to satellites over 500 kilometers away using advanced antenna arrays and digital beamforming. Founded in 2021 by Alex Haro (co-founder of Life360, which IPO'd in 2019 and grew to 80+ million monthly active users) and Ben Longmier (whose previous company's protocol became Amazon Sidewalk after acquisition), Hubble has launched seven operational satellites via SpaceX and is serving enterprise customers across intermodal logistics, off-grid construction, and outdoor recreation. In a recent episode of BUILDERS, I sat down with Alex to explore how Hubble is building the infrastructure layer for global IoT—positioning as the "T-Mobile of space" rather than competing in device markets. Topics Discussed: The technical architecture behind connecting Bluetooth to satellites: lowering bit rates, optimizing modulation, and deploying hundreds of antennas for digital beamforming SpaceX's rideshare program mechanics and what it actually takes to book satellite launches as a startup Why Hubble deliberately chose to be network infrastructure rather than building hardware for specific verticals The psychology barrier of overcoming Bluetooth's short-range association—even among experienced RF engineers from Google, Amazon, and Starlink Strategic focus decisions when facing unlimited market opportunity across construction, agriculture, mining, logistics, and defense Transparent pricing as a developer-first GTM strategy versus traditional enterprise carrier sales models The transition from Life360's consumer hardware exploration to founding a satellite networking company GTM Lessons For B2B Founders: Choose your competitive layer strategically—infrastructure scales differently than applications: Hubble explicitly positioned as network infrastructure, not a device manufacturer. Alex stated: "We're not focused on building the hardware or devices. We very much view ourselves as a networking company." This allows enterprise customers to integrate Hubble connectivity into their existing devices with just a software change to the Bluetooth chip. The result: each B2B customer can deploy hundreds or thousands of devices to their end users, creating exponential reach. For founders building horizontal technology, consider whether competing at the infrastructure layer—even if less immediately tangible—creates superior unit economics and market leverage versus building full-stack solutions. Developer-first positioning requires operational commitment, not just marketing: Hubble's pricing transparency wasn't a marketing tactic—Alex described it as "hardcore to our ethos" because their goal is connecting billions of devices. They explicitly modeled after Twilio and Stripe rather than Verizon or AT&T, making it possible for engineers to validate unit economics independently and start free trials without sales conversations. This wasn't debated internally because both co-founders and the early team aligned on this approach. For infrastructure companies targeting massive scale, half-measures on developer experience will fail—the entire go-to-market motion must support self-service validation and transparent economics. Constraint forces clarity—unlimited TAM demands disciplined ICP filtering: Despite viable use cases across construction, oil and gas, mining, agriculture, supply chain, and defense, Alex emphasized: "In the early stages, focus is the most important thing. Every hour matters and being able to focus matters quite a bit and defocusing yourself can really hurt." Hubble's "sexy hook of Bluetooth to space" generates inbound interest across industries, creating constant pressure to expand. Their active debate centers on which industry leaders are "solving important use cases" with existing customer bases of "hundreds, if not thousands of customers." For founders with horizontal technology, resist opportunistic deals—filter aggressively for partners who provide concentrated distribution rather than one-off deployments. Physical demonstration collapses credibility timelines for counterintuitive technology: Hubble faced skepticism even from sophisticated RF engineers because of hardwired associations between Bluetooth and short range. Alex noted: "Some of the investors that joined our A or B, they passed on our seed and A because they thought, well, I believe in Alex, but is this really physically possible?" Post-launch with working satellites, the conversation shifted from "is this possible?" to commercial terms. The lesson isn't just "show don't tell"—it's that for technically improbable innovations, rushing to demonstrable proof compresses months of explanation into minutes of validation. Founders should potentially sacrifice feature breadth to reach a single, undeniable proof point faster. Operational domain expertise reveals infrastructure gaps others can't see: Alex spent years as CTO of Life360 attempting to build connected hardware for families—smart pet collars, GPS watches for kids, fall detectors—but existing networks had "super short battery life, very bulky, no global coverage, way too expensive." He invested in Ben's previous mesh network company and became a close advisor before co-founding Hubble. The insight wasn't theoretical—it came from failing repeatedly to solve the problem with existing infrastructure. Founders should treat operational frustrations in previous roles as proprietary market intelligence: you've already paid the learning cost that competitors will need years to acquire. // 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

In this episode, we sit down with Carl Mattsson, VP & GM EMEA at Kong, to discuss one of the most remarkable scaling journeys in the industry. Carl joined Kong when it was at just $1M ARR in the EMEA market and has since spearheaded its growth to nearly $100M ARR. We explore the unique sales principles that shaped the organization, the "heart surrounded by science" culture, and how Carl navigated the transition from a single-product company to a dominant AI-governance platform. Carl also shares the incredible story of a founder's personal commitment that kept him at the company during a critical turning point.

Axenya is rebuilding healthcare around chronic disease prevention through AI-powered continuous monitoring. Covering 100,000 lives in Brazil and processing 95 million clinical inferences monthly, the company pivoted from clinical technology provider to healthcare broker - achieving cash flow positive status before their Series A. In this episode of BUILDERS, I sat down with Mariano García-Valiño, CEO and Founder of Axenya, to learn how they spent $3 million building the "perfect product" before discovering no one would pay for it, why they acquired a small broker to unlock their revenue model, and their regulatory-constrained approach to geographic expansion. Topics Discussed: Axenya's shift from infectious disease to chronic disease management through wearables and AI The 12-month zero-revenue period after spending $3 million on product development Why doctors, patients, and health plans all failed as buyers despite clinical validation The broker acquisition that unlocked their business model Performance-based pricing: zero fees upfront, revenue from cost savings only Regulatory barriers determining expansion (Mexico viable, Argentina impossible, Europe requires model redesign) Field-force-driven GTM with 30+ salespeople for complex, high-ACV enterprise deals Path to cash flow positive before Series A and scaling playbook for 2026 // 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

Plantd is reinventing engineered lumber by replacing trees with rapidly renewable biomass, scaling manufacturing technology that costs 100x less than traditional OSB production. With customers including DR Horton and growing demand across furniture, RV, and international markets, Plantd has attracted partnerships throughout the building materials industry. In this episode of BUILDERS, I sat down with Nathan Silvernail, Co-Founder & CEO at Plantd, to explore how his decade at SpaceX shaped his approach to building a capital-intensive hardware company that could transform the $65 billion engineered lumber market.   Topics Discussed Building continuous OSB production systems versus $500M batch presses used by incumbents Securing DR Horton, furniture manufacturers, and building material companies as early customers Managing the bifurcation between OPEX-intensive manual processes and CAPEX transitions to AI robotic vision systems Designing machines for 400,000 panels/year output with sub-one-year payback at scale Navigating opinion-based building inspection processes where "no two blocks in this entire country build a house the same way" The strategic calculus of positioning away from climate tech to avoid green premium assumptions Scaling from pilot production to deploying 25-30 machines to meet current demand pipeline Achieving 70-layer panel construction versus 6-8 layers in timber-based OSB //   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

Turnstile is reimagining quote-to-cash for the modern B2B world, where negotiated agreements create operational chaos that standard pricing never does. After selling Second Measure to Bloomberg, co-founders Michael Babineau and Lillian Chou experienced the irony firsthand: running a data analytics company while managing their own revenue operations through spreadsheets and manual processes. That incongruence became the catalyst for Turnstile, a self-serve revenue platform designed to support sales-led B2B companies from their first negotiated deal through tens of millions in ARR. In this conversation, Michael shares how they're solving the structured data problem that plagues B2B revenue operations, why eliminating custom development forced genuine platform flexibility, and how they're collapsing a traditionally 3-6 month implementation into a self-serve onboarding that takes minutes. Topics Discussed: Why negotiated B2B agreements create the structured data problem that breaks revenue operations Turnstile's compound startup approach spanning quote-to-cash to revenue recognition The internal ban on custom development that forced true configurability into the platform How supporting non-standard contracts from day one enables earlier market entry than traditional CPQ Revenue leakage and "truth drift" between contract terms and actual customer relationships The rippling-style GTM strategy: start with startups, grow into enterprise with your customers Positioning challenges when your category exists but your ICP doesn't know it yet Building for human operators and AI agents simultaneously on the same platform primitives Agentic dunning and the roadmap toward AI-automated revenue operations // 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

My interview with Ali Ansari the founder of micro1.ai, an AI startup that has grown revenue from $8M to $150M+ this year and is on track for a multi-billion dollar valuation. They are working with most of the AI labs and largest tech companies in the world (including Microsoft) to hire human experts to train AI. We've been investing in Ali for years now and it's been epic to see his insane growth and recent traction. Ali and micro1 are at the forefront of the AI revolution.Ali Ansari Founder of micro1.ai on X: https://x.com/aliniikkmicro1 website: https://www.micro1.ai/0:00 Forbes Article, $2.5B Valuation?1:35 Micro1: The AI Platform For Human Intelligence7:18 Micro1's Insane Growth ($8M to $100M ARR in one year)9:54 Are We In An AI Bubble?16:16 Micro1's Long Term Vision20:25 Micro1 Training Tesla Optimus25:20 Why Did You Found Micro1?29:10 The Early Days Ebay Flipping33:08 $15B Market Growing 100%+34:35 Human Demonstration Business (Teaching Robots)37:00 Micro1's Next Funding RoundMy X:   / gfilche  HyperChange Patreon :)   / hyperchange   Disclaimer: I'm an investor in micro1 personally and through my VC firm HyperGuap. This is not financial advice.

Sam Liang worked on the team that built the "blue dot" for Google Maps and now he's transforming how we think about meetings with Otter.ai. Fresh off crossing $100M in ARR with a lean team of less than 200, Sam joins us to discuss how Otter evolved from passive transcription to active AI agents that participate in your meetings. Learn practical strategies for building reliable voice AI, implementing enterprise knowledge bases, and deploying AI agents that actually deliver ROI.Resources mentioned:• Otter.ai $100M ARR announcement: https://otter.ai/blog/otter-ai-breaks-100m-arr-barrier• HIPAA compliance: https://otter.ai/blog/otter-ai-achieves-hipaa-complianceSubscribe to The Neuron newsletter: https://theneuron.ai

Episode 407 of The VentureFizz Podcast features Seth Rosen, Founder & CEO of CustomMade. A common theme that you'll hear throughout this interview is the importance of resiliency. Sure - the media loves the story of the latest company that has achieved $100M ARR in a month (I'm obviously kidding), but the overwhelming majority of businesses are a grind. It's about taking a bunch of punches, getting back up and figuring it all out. It's not all rainbows and butterflies, which is why I was excited to interview Seth. The story of CustomMade has lots of twists and turns… from rapid growth… to later salvaging the company by structuring a deal with Wayfair to acqui-hire their employee base… to the insanely successful reboot! Today, CustomMade is a leading online custom jeweler that specializes in creating personalized, one-of-a-kind jewelry pieces, such as engagement rings, wedding bands, and more. The platform simplifies the entire custom process, helping buyers create their vision and working with master jewelers to bring it to life. Chapters: 00:00 Intro 00:11 Importance of Resiliency 01:20 The Right Business Model: Subscription vs Marketplace 02:52 Seth's Background 06:24 Meeting Mike Salguero While Working in Real Estate 12:51 Background Story of CustomMade 20:55 Raising Venture Capital for CustomMade 24:58 Building & Running an Online Marketplace 27:30 The Challenges of Running an Online Marketplace 29:24 Making a Deal with Wayfair 31:33 CustomMade Reboot 36:38 CustomMade Today - The World's Largest Online Custom Jeweler 40:10 What are Lab Grown Diamonds 44:24 SEO & GEO 49:20 Seth's Other Initiatives in the Gem Industry 50:46 Seth's Role as a Venture Partner at WTI

This Week In Startups is made possible by:Sentry - http://sentry.io/twistLinkedIn Ads - http://linkedin.com/thisweekinstartupsPipedrive - pipedrive.com/twistToday's show:Netflix wants to gobble up Warner Bros. Do they just want to own Batman and Harry Potter, or is this secretly about destroying movie theaters?Sure, this is usually a startup show, but news THIS BIG warrants attention! So Lon stops by to tell Jason and Alex about the big Netflix acquisition news, why so many theatrical movie fans are terrified for the future, and why this might face particular regulatory scrutiny both at home and abroad.PLUS… are Googlers gaming Polymarket? This is one scenario in which prediction markets are NOT exactly like stocks.THEN we're looking at some of our favorite startups from the Fall ‘25 Y Combinator cohort (and asking Producer Claude for his picks)… Considering why Perplexity keeps getting sued and how they can stop it… and doing a victory lap for Jason's early investment in breakout AI training project Micro1.Timestamps:(02:05) Netflix buying Warner Bros! Jason, Lon and Alex react.(05:04) Jaytrade Update: J kind of missed the boat on this one(05:36) What does this mean for theatrical cinema?(08:42) Sentry - New users get 3 months free of the Business plan (covers 150k errors). Go to http://sentry.io/twist and use code TWIST(09:52) Jason's pitch to Disney CEO Bob Iger (please send this to him!)(19:36) LinkedIn Ads: Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to http://linkedin.com/thisweekinstartups to claim your credit.(23:29) Is this deal going to get approval, at home and abroad?(25:52) Are Googlers gaming Polymarket?(28:02) Can you do “insider trading” on a prediction market?(29:23) Pipedrive - Bring your entire sales process into one elegant space. Get started with a 30 day free trial at pipedrive.com/twist(37:00) How accelerators like Y Combinator serve as “finishing schools” for startups(37:52) A Quick Look at some of our fav companies from YC's Fall '25 cohort(39:01) Why startups need to “skate to where the puck is going”(40:08) Why sometimes old ideas (like solar-powered aircraft) are often worth revisiting(45:29) Jason's advice for founders (and investors) in the “feel good” or activist space(50:48) Why Lon, Alex, and Claude ALL thought Hyperspell sounds like a hot startup(52:58) Perplexity getting sued again! Why can't they make friends!(57:51) Meanwhile, Meta's signing AI deals with news publications.(59:21) Micro1, which Jason helped to fund, has hit $100M ARR! Why do AI companies need so many experts?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(8:42) Sentry - New users get 3 months free of the Business plan (covers 150k errors). Go to http://sentry.io/twist and use code TWIST(19:36) LinkedIn Ads: Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to http://linkedin.com/thisweekinstartups to claim your credit.(29:23) Pipedrive - Bring your entire sales process into one elegant space. Get started with a 30 day free trial at pipedrive.com/twist

AGENDA: 04:06 Anthropic's $30BN Investment from Microsoft and NVIDIA 07:01 Google vs. OpenAI: Sam Altman's "War Mode" Memo 15:27 NVIDIA's Customer Concentration: Bull or Bear 22:12 Is "War Mode" BS: Does Hyper-Aggressive Ever Work? 36:12 Sierra Hits $100M ARR: Justify $10BN Price? 46:14 Implementation is the Biggest Barrier to Enterprise AI Growth 01:04:04 Is LLM Search Optimisation (GEO) Selling Snake Oil? What AI is a Fraud vs Real? 01:14:27 Figma Market Cap: Is the IPO Market F****** for 2026