BUILDERS

Front Lines Media

Welcome to BUILDERS — the show about how founders get new technology adopted. Each episode features a founder on the front lines of bringing new tech to market, sharing how they broke into their industry, earned early believers, built credibility, and unlocked real technology adoption. BUILDERS is part of a network of 20 industry-specific shows with a library of 1,200+ founder interviews conducted over the past three years. For the full network, visit FrontLines.io. Brought to you by:  www.FrontLines.io/FounderLedGrowth — Founder-led Growth as a Service. Launch your own podcast that drives thought leadership, demand, and most importantly, revenue.

  1. How Ridepanda landed Amazon and Google by repositioning within existing commuter benefit budgets | Chinmay Malaviya

    7 GIỜ TRƯỚC

    How Ridepanda landed Amazon and Google by repositioning within existing commuter benefit budgets | Chinmay Malaviya

    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

    19 phút
  2. How Palla Financial navigates selling to banks with no standard buyer: from remittance teams to CEOs | Enrique Perezalonso

    8 GIỜ TRƯỚC

    How Palla Financial navigates selling to banks with no standard buyer: from remittance teams to CEOs | Enrique Perezalonso

    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

    23 phút
  3. How Telo Trucks avoided the failure pattern that killed 60+ automotive startups in the last 40 years | Jason Marks

    4 NGÀY TRƯỚC

    How Telo Trucks avoided the failure pattern that killed 60+ automotive startups in the last 40 years | Jason Marks

    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

    25 phút
  4. How Lula pivoted from B2C to B2B after discovering landlords were 80%+ of users | Bo Lais

    4 NGÀY TRƯỚC

    How Lula pivoted from B2C to B2B after discovering landlords were 80%+ of users | Bo Lais

    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

    20 phút
  5. How CoreStory seeded "Spec-Driven Development" across the market without analyst relations | Anand Kulkarni

    4 NGÀY TRƯỚC

    How CoreStory seeded "Spec-Driven Development" across the market without analyst relations | Anand Kulkarni

    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

    23 phút
  6. How theion's CEO approaches pre-GTM deep tech strategy | Dr. Ulrich Ehmes"

    4 NGÀY TRƯỚC

    How theion's CEO approaches pre-GTM deep tech strategy | Dr. Ulrich Ehmes"

    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

    18 phút
  7. How Positron AI is driving sales ahead of product | Mitesh Agrawal

    4 NGÀY TRƯỚC

    How Positron AI is driving sales ahead of product | Mitesh Agrawal

    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

    27 phút
  8. How Qualytics Knew it had found product-market fit | Gorkem Sevinc

    5 NGÀY TRƯỚC

    How Qualytics Knew it had found product-market fit | Gorkem Sevinc

    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

    25 phút

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Welcome to BUILDERS — the show about how founders get new technology adopted. Each episode features a founder on the front lines of bringing new tech to market, sharing how they broke into their industry, earned early believers, built credibility, and unlocked real technology adoption. BUILDERS is part of a network of 20 industry-specific shows with a library of 1,200+ founder interviews conducted over the past three years. For the full network, visit FrontLines.io. Brought to you by:  www.FrontLines.io/FounderLedGrowth — Founder-led Growth as a Service. Launch your own podcast that drives thought leadership, demand, and most importantly, revenue.