BUILDERS

How Plantd identified business process inefficiencies as a competitive wedge in building materials | Nathan Silvernail

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
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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.
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How Axenya achieved cash flow positive before Series A by proving recontract capability | Mariano García-Valiño

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
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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
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Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How Turnstile positioned quote-to-cash for founders who don't know the category exists | Michael Babineau

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
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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.
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How Land Life evolved from selling technology to delivering A-to-Z restoration projects | Rebekah Braswell

Land Life is a technology-driven nature restoration company that restores landscapes degraded by wildfire, overfarming, and urbanization. The company combines proprietary remote sensing, machine learning algorithms, and hardware solutions to deliver end-to-end restoration projects spanning 40 years, monetized through voluntary and compliance carbon markets. With seven validated project design documents on Verra, Land Life has built a business model that requires customers to believe the company will exist for decades. In a recent episode of BUILDERS, we sat down with Rebekah Braswell, CEO of Land Life, to explore how the company navigated from global pilots in Saudi Arabia and the Galapagos to focused geographic operations, evolved its customer base from experimental tech buyers to conservative insurance companies, and repositioned its entire value proposition when climate dropped off corporate priority lists in 2024.
Topics Discussed:
Land Life's shift from selling technology components to customer-driven A-to-Z project delivery 
Remote sensing dashboard that assesses ecological, operational, and economic feasibility before land visits 
Securing environmental attributes while keeping land locally owned by landowners 
Machine learning algorithms for determining optimal tree species, placement, and timing 
Evolution from tech company early adopters to asset managers, financial institutions, and energy providers 
The 2024 market standstill: how tariffs and defense spending displaced climate on corporate agendas 
Strategic repositioning from "climate" to "resilience" language that connects to infrastructure and defense 
Targeting biogenic customers in timber and agriculture with supply shed restoration strategies
GTM Lessons For B2B Founders:
Let customer requirements redefine your product scope: Land Life initially sold discrete technology—cocoon hardware and software tools—to corporations. Buyers consistently responded: "great tech, but we sell shoes online for a living. I need a full project, A to Z." Rather than insisting on their original product definition, Rebekah agreed to plant trees and hire contractors despite "knowing very little at the time what it actually took." The company evolved from a technology vendor to a full-service restoration provider because that's what buyers would actually purchase. B2B founders should recognize when customer feedback reveals a larger market opportunity than their initial product scope, even if delivery capabilities don't yet exist.
Target buyers whose operational experience mirrors your delivery complexity: Land Life struggled with tech companies despite strong initial traction because these customers operated on "much shorter term economic cycles" incompatible with 40-year projects. The company found stronger fit with financial institutions, insurance companies, and energy providers—buyers Rebekah described as "familiar with asset management, familiar with physical operations" who could "identify with some of the cycles that we have to manage in terms of planting windows." She told her team: "you know you have a business when an insurance company starts buying your product. These are conservative buyers." B2B founders with long implementation cycles, physical operations, or asset-intensive models should prioritize buyers with analogous operational complexity rather than chasing early adopters who lack relevant mental models.
Build transparency infrastructure as core product, not marketing: For customers committing to 40-year relationships, Land Life addressed the fundamental trust problem through systematic monitoring and data sharing. Rebekah identified the specific perception barrier: "people have this image that people are just going out and planting trees and there's no accountability." The company's response wasn't better sales materials but "a data focused and transparent process" that continuously validates project performance. B2B founders selling long-term commitments should invest in measurement and reporting systems as primary credibility drivers, recognizing that transparency infrastructure is product, not overhead.
Adapt positioning to buyer priority shifts without abandoning core value: When climate investments "came to a standstill for six months" in 2024, Land Life didn't pivot its business model—it reframed its language. Climate "just dropped on the priority list" as corporations focused on "AI, defense and tariffs." The company shifted to "resilience" positioning that "doesn't use the word climate in it" but connects to infrastructure, defense, and supply chain concerns. Critically, this wasn't invented messaging—Land Life had internally called their engineers "resilience engineers" for years because "you can't bet one climate scenario." B2B founders facing external market shifts should mine existing internal frameworks for language that naturally aligns with new buyer priorities rather than forcing artificial repositions.
Expand value proposition beyond primary category benefit to operational impact: Land Life evolved from pure carbon sequestration sales to showing customers how restoration addresses their core operational risks. For biogenic customers—"people who work in timber, food and agriculture"—the pitch became: "if you're surrounded by a degraded ecosystem, it will eventually encroach" on your supply chain. Rebekah explained: "it's not just enough to have a robust supply chain like your field for example. Great that things are healthy there, but if you're surrounded by a degraded ecosystem, you know it will eventually encroach." This connected restoration directly to supply shed stability and de-risking rather than relying solely on carbon credit value. B2B founders should identify how their solution protects or enhances customers' existing operations, not just deliver category-specific benefits.
Pursue partnerships to reach scale thresholds faster than organic growth allows: Rebekah emphasized that achieving buyer-required scale through partnerships is now essential: "buyers are looking for scale and it is hard for us, who are in nature based solutions and physical assets, to achieve that overnight." She advocated for "constructive and innovative partnerships where you can bring that scale to buyers, whether it's organic or just through partnering" as the path to "play at a different level." The sector signal is clear: "they want bigger volumes, they want stronger suppliers, and that path goes a lot more quickly when you partner, as opposed to trying to do it alone." B2B founders in capital-intensive or operationally complex businesses should view partnerships as strategic accelerators to reach minimum viable scale, not just growth tactics.
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Don't Miss: New Podcast Series — How I Hire
Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

How PredictAP transitioned from founder-led sales to repeatable pipeline after hitting the network wall | David Stifter

David Stifter spent 20 years as head of technology at Colony Capital, managing systems for a $60 billion private equity real estate firm. When a longtime AP specialist retired, the company lost its institutional knowledge for coding complex invoices across thousands of entities and tenant relationships. After a year evaluating RPA, template-based approaches, and early OCR solutions, David recognized that structured historical data—invoices paired with their coding—could train AI models to capture implicit business rules. Five years ago, at 40 with young children, he left his executive role to build PredictAP. The company now processes tens of thousands of invoices monthly for firms including Bridge Investment Group, demonstrating how operational expertise combined with AI can solve problems that pure technology approaches miss.
Topics Discussed
Identifying AI use cases with structured annotated data and human feedback loops 
Moving from CTO buyer to vendor founder and discovering which networks actually convert 
Building repeatable sales motion after exhausting warm introductions 
Technology adoption barriers in real estate and the domain expertise requirement for vertical SaaS 
Hiring sales leadership to scale from founder-led to systematic pipeline generation 
Solving complete workflow integration challenges beyond isolated technical problems
GTM Lessons For B2B Founders
Match technical approach to problem structure, not trend: David identified three critical elements for his AI application: structured annotated data from historical invoice coding, recognizable patterns in implicit business rules, and human review as a feedback mechanism. He notes many founders "try to shove AI, the AI hammer to smash any nail, but they're not always the best use case." Six years ago, before modern LLMs, he used historical invoice-coding pairs as training data—solving the annotation problem that plagued early machine learning. Founders should evaluate whether their problem has the structural characteristics that make a given technology approach viable, rather than applying trending solutions to force market fit.
Network quality reveals itself when you need something: David contrasts two early investors: a former acquisitions executive who promised extensive connections but delivered "not a single callback" after leaving their role, versus an asset manager who generated "hundreds" of leads through genuine relationships. The acquisitions person experienced "an existential crisis" realizing "my network was based upon my ability to have a massive checkbook behind me." Founders should recognize that network strength isn't tested until you're asking rather than giving—those who built relationships through consistent helpfulness rather than transactional power will see different response rates when they launch.
Architect the founder-led to systematic sales transition: After two years of founder-led sales, David "hit that wall" and brought in Steve Farrell, prioritizing experience scaling from $3-5M to $20M ARR over industry-specific expertise. He notes warm intro calls are "very to the point" while cold outreach "starts hostile or skeptical"—requiring entirely different trust-building approaches. The shift required adding BDRs, AEs, and systematic content generation. Founders should hire sales leadership with specific stage experience before network depletion forces reactive hiring, and expect to rebuild positioning for skeptical buyers who lack pre-existing trust.
Integrate solutions into existing workflow infrastructure: David emphasizes the failure mode of optimized point solutions: "They have a perfect solution from the technical problem but it's not going to work for this firm because it's not going to fit into their workflow." He maps the complete experience including integration with existing systems, training requirements, user experience, consistency, and speed. Technical superiority in isolation leads to "problems with adoption and retention." Founders should map every system, process, and stakeholder their solution touches, designing for workflow integration rather than isolated problem-solving.
Sequence customer sophistication as you scale beyond innovators: David's initial customers were "leading edge folks" from his technology network who understood AI potential. As PredictAP matured, sales cycles became "much longer" with more conservative firms requiring higher proof thresholds. He learned that "initial sales have to be very successful and you have to have customers that advocate for you" because mainstream buyers need extensive social proof. Founders should recognize that early adopter ICP differs fundamentally from mainstream buyers—what closes innovators (technology potential) differs from what closes pragmatists (proven ROI and references), requiring distinct positioning and sales approaches for each segment.
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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.
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How Datawizz discovered the chasm between AI-mature companies and everyone else shaped their ICP | Iddo Gino

Datawizz is pioneering continuous reinforcement learning infrastructure for AI systems that need to evolve in production, not ossify after deployment. After building and exiting RapidAPI—which served 10 million developers and had at least one team at 75% of Fortune 500 companies using and paying for the platform—Founder and CEO Iddo Gino returned to building when he noticed a pattern: nearly every AI agent pitch he reviewed as an angel investor assumed models would simultaneously get orders of magnitude better and cheaper. In a recent episode of BUILDERS, we sat down with Iddo to explore why that dual assumption breaks most AI economics, how traditional ML training approaches fail in the LLM era, and why specialized models will capture 50-60% of AI inference by 2030.
Topics Discussed
Why running two distinct businesses under one roof—RapidAPI's developer marketplace and enterprise API hub—ultimately capped scale despite compelling synergy narratives
The "Big Short moment" reviewing AI pitches: every business model assumed simultaneous 1-2 order of magnitude improvements in accuracy and cost
Why companies spending 2-3 months on fine-tuning repeatedly saw frontier models (GPT-4, Claude 3) obsolete their custom work
The continuous learning flywheel: online evaluation → suspect inference queuing → human validation → daily/weekly RL batches → deployment
How human evaluation companies like Scale AI shift from offline batch labeling to real-time inference correction queues
Early GTM through LinkedIn DMs to founders running serious agent production volume, working backward through less mature adopters
ICP discovery: qualifying on whether 20% accuracy gains or 10x cost reductions would be transformational versus incremental
The integration layer approach: orchestrating the continuous learning loop across observability, evaluation, training, and inference tools
Why the first $10M is about selling to believers in continuous learning, not evangelizing the category
GTM Lessons For B2B Founders
Recognize when distribution narratives mask structural incompatibility: RapidAPI had 10 million developers and teams at 75% of Fortune 500 paying for the platform—massive distribution that theoretically fed enterprise sales. The problem: Iddo could always find anecdotes where POC teams had used RapidAPI, creating a compelling story about grassroots adoption. The critical question he should have asked earlier: "Is self-service really the driver for why we're winning deals, or is it a nice-to-have contributor?" When two businesses have fundamentally different product roadmaps, cultures, and buying journeys, distribution overlap doesn't create a sustainable single company. Stop asking if synergies exist—ask if they're causal.
Qualify on whether improvements cross phase-transition thresholds: Datawizz disqualifies prospects who acknowledge value but lack acute pain. The diagnostic questions: "If we improved model accuracy by 20%, how impactful is that?" and "If we cut your costs 10x, what does that mean?" Companies already automating human labor often respond that inference costs are rounding errors compared to savings. The ideal customers hit differently: "We need accuracy at X% to fully automate this process and remove humans from the loop. Until then, it's just AI-assisted. Getting over that line is a step-function change in how we deploy this agent." Qualify on whether your improvement crosses a threshold that changes what's possible, not just what's better.
Use discovery to map market structure, not just validate hypotheses: Iddo validated that the most mature companies run specialized, fine-tuned models in production. The surprise: "The chasm between them and everybody else was a lot wider than I thought." This insight reshaped their entire strategy—the tooling gap, approaches to model development, and timeline to maturity differed dramatically across segments. Most founders use discovery to confirm their assumptions. Better founders use it to understand where different cohorts sit on the maturity curve, what bridges or blocks their progression, and which segments can buy versus which need multi-year evangelism.
Target spend thresholds that indicate real commitment: Datawizz focuses on companies spending "at a minimum five to six figures a month on AI and specifically on LLM inference, using the APIs directly"—meaning they're building on top of OpenAI/Anthropic/etc., not just using ChatGPT. This filters for companies with skin in the game. Below that threshold, AI is an experiment. Above it, unit economics and quality bars matter operationally. For infrastructure plays, find the spend level that indicates your problem is a daily operational reality, not a future consideration.
Structure discovery to extract insight, not close deals: Iddo's framework: "If I could run [a call where] 29 of 30 minutes could be us just asking questions and learning, that would be the perfect call in my mind." He compared it to "the dentist with the probe trying to touch everything and see where it hurts." The most valuable calls weren't those that converted to POCs—they came from people who approached the problem differently or had conflicting considerations. In hot markets with abundant budgets, founders easily collect false positives by selling when they should be learning. The discipline: exhaust your question list before explaining what you build. If they don't eventually ask "What do you do?" you're not surfacing real pain.
Avoid the false-positive trap in well-funded categories: Iddo identified a specific risk in AI: "You can very easily run these calls, you think you're doing discovery, really you're doing sales, you end up getting a bunch of POCs and maybe some paying customers. So you get really good initial signs but you've never done any actual discovery. You have all the wrong indications—you're getting a lot of false positive feedback while building the completely wrong thing." When capital is abundant and your space is hot, early revenue can mask product-market misalignment. Good initial signs aren't validation if you skipped the work to understand why people bought.
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Sponsors:
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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.
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How GreenLite discovered architects were the wrong ICP after 6 months of customer interviews | James Gallagher

GreenLite delivers private construction plan review as an alternative to traditional city permitting processes. After spending six months testing both sides of the construction permitting transaction, the company identified owner-developers as their ICP and built a business model around Florida's privatization legislation—legislation that has now expanded to nine additional states including Texas, Tennessee, and California. In this episode of BUILDERS, we sat down with James Gallagher, CEO and Co-Founder of GreenLite, to explore how his fifth startup leveraged regulatory shifts, rejected workflow software in favor of outcomes, and scaled by targeting chief development officers at enterprise retailers struggling with permitting delays.
Topics Discussed:
How GreenLite discovered architects were heavy users but wrong customers due to two-part sales dynamics
Why owner-developers became the ICP after six months of customer discovery across applicants and agencies
The accidental discovery of private plan review through conversations with Fort Worth and Miami-Dade agencies
GreenLite's platform combining regulatory permissions, licensed AEC professionals, and AI-augmented software
How natural disasters and AEC talent shortages are accelerating privatization legislation nationwide
Cold email strategies that converted enterprise retailers by surfacing acute pain points
GTM Lessons For B2B Founders:
Map two-sided markets to find where purchasing authority and pain intersect: GreenLite pitched a CTO at a major architecture firm who responded positively but said "I just need to talk to my client, my customer." This revealed architects required approval from owner-developers despite being the heaviest product users. James pivoted to owner-developers who "carry the land, carry the construction loans" and feel revenue delays most acutely. The lesson: usage intensity doesn't equal buyer authority. In complex ecosystems, systematically test which party controls budget and feels enough pain to sign contracts independently.
Recognize when procurement cycles kill early-stage validation velocity: Cities explicitly told James their "crazy procurement cycles" made early partnership impractical despite genuine interest. State and local education and government sales require specialized expertise and extended timelines that prevent rapid iteration. James chose to prove the model with private sector customers first. For founders: government can be a lucrative eventual market, but unless you have sled sales expertise and 12+ month runway per deal, validate PMF elsewhere first.
Capitalize on regulatory tailwinds before markets realize they exist: Only Florida permitted private plan review when GreenLite launched in July 2022. By late 2024, nine states passed enabling legislation driven by natural disaster reconstruction needs and talent shortages in city building departments. James positioned GreenLite to ride this wave rather than selling transformation to resistant agencies. Founders should monitor legislative and regulatory changes in their verticals—new compliance requirements or permissions can suddenly open massive TAMs with minimal incumbent competition.
Enterprise cold email converts when you surface non-obvious acute pain: GreenLite cold emailed chief development officers at major retail chains and quick-service restaurants with "Are you missing your openings due to permitting?" The response rate validated that permitting delays—not site selection or construction costs—were a critical path blocker for store rollout velocity. James targeted CDOs rather than real estate or design teams because they own the full development timeline. For enterprise sales: identify the executive accountable for the metric your solution impacts, then lead with how you move that specific number.
Validate outcome-based models before building sophisticated workflow tools: GreenLite's customers rejected "another workflow product or system of record" that required API integrations with their ERPs and construction management systems. Instead, they wanted "faster, more predictable, more transparent permits." James built a viable business delivering finished permits through licensed professionals augmented by software, with the AI sophistication coming later. The business was "super viable well before the product was" by early 2023. For founders in industries resistant to software adoption: test whether buyers want tools to operate or outcomes to purchase—outcome-based pricing can achieve PMF faster and command premium willingness-to-pay.
// Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io
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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. 
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How Aurelius Systems proved Viability through nationwide field demonstrations in extreme conditions | Michael LaFramboise

Aurelius Systems is tackling one of defense's most critical challenges: cost-effective counter-drone warfare. The company builds lightweight, edge-deployed laser weapon systems with 10-million-x marginal cost advantages over traditional interceptors—shooting down drones for approximately 10 cents versus $2 million per Sea Sparrow missile. With systems priced in hundreds of thousands rather than tens of millions of dollars, Aurelius is proving that commercial manufacturing principles can revolutionize defense technology. In this episode of BUILDERS, I sat down with Michael LaFramboise, CEO and Co-Founder of Aurelius Systems, to unpack how his background spanning automotive manufacturing at Chrysler, R&D at Coherent (the largest U.S. laser manufacturer), and defense sales positioned him to build what he calls "the F150 of directed energy systems."
Topics Discussed:
Why Michael's unusual combination of heavy industrial manufacturing, high-power laser R&D, and directed energy sales made him one of "probably like five people under 70 in the country" positioned to build this company
Aurelius's contrarian R&D thesis: build everything from commercial off-the-shelf components first, only upgrading to bespoke when field tests fail
The tactical fundraising progression: first prototype to pre-seed, DIU grant in February 2025, Singapore Defense Force joint challenge, Army X-Tech competition wins
Government relations as infrastructure: why Aurelius retained a lobbyist six months post-pre-seed and how Congressional support addresses 1-3 year sales cycles
Navigating the DOD acquisitions reorg: 100+ technology acceleration organizations consolidating to 10-20 under new PAE structure, with goals of 90-day turnarounds replacing multi-year cycles
The demonstration strategy that changed everything: earning signed memorandums from high-ranking officers after shooting down drones in Hawaii and Austin under adversarial conditions (heavy rain, 99% humidity, heat warping, night operations)
Founder-led marketing ROI: why acquisitions officers, funders, and engineering talent all follow different channels (LinkedIn vs. X) and require different voices
The three-stakeholder sales complexity: when your end user (warfighter), purchaser (acquisitions), and budget authorizer (Congress) are separate entities who don't communicate
GTM Lessons For B2B Founders:
Follow proven playbooks in specialized markets, then execute obsessively: Michael explicitly followed Anduril's early-stage defense playbook, particularly around government relations: "I think it's like following the Anduril playbook for how you do an early stage defense company is probably a very appropriate thing to do." In highly specialized B2B markets (defense, healthcare, financial services), pattern-match to companies that have successfully navigated regulatory and procurement complexity rather than inventing process from scratch. The differentiation comes from execution and technology, not from reinventing go-to-market structure.
Treat specialized expertise as infrastructure, not overhead: Aurelius hired a lobbyist six months after their pre-seed—before significant revenue—because defense sales involve three disconnected stakeholders. Michael explained: "your purchaser, your end user, and your authorizer for funds are all separate people that don't know each other... whenever you have these different points, it doesn't expand linearly the difficulty or the complexity of the sales cycle. It expands exponentially." B2B founders should map stakeholder complexity early and staff accordingly. If your buyer doesn't control budget, your user doesn't make purchase decisions, or your champion needs internal air cover, these aren't edge cases—they're your sales model.
Demonstration beats documentation when overcoming category skepticism: After decades of directed energy failures, Aurelius spent 2024 conducting nationwide field demonstrations, culminating in adversarial drone shoot-downs in heavy rain, 99% humidity, and night conditions. Michael noted they needed to "clean up the mess that a lot of these other companies have created" with signed memorandums from high-ranking officers. When your category has a failure history, customer education isn't about better pitch decks—it's about systematic proof that eliminates objections through witnessed performance. Plan for demonstration costs and timeline in your first-year budget.
Build your R&D thesis around manufacturing reality, not engineering perfection: Aurelius's core principle: build everything from commercial off-the-shelf components, upgrading only when field tests fail. Michael's insight from automotive and laser manufacturing: "you can get 80-90% physics perfection on a system for 2% of the cost" versus traditional directed energy's approach of "400 ARL and AFRL PhDs all coming together to make the most super bespoke, hyper perfect thing ever." They use material processing lasers (identical output at 1/10th the cost of directed energy lasers) and commercial components from automotive supply chains. B2B founders should define their "good enough" threshold explicitly and build cost structure around it—perfection is often the enemy of scalability and margin.
Attack market dislocations where wrong-fit solutions reveal unmet needs: Aurelius doesn't compete with Sea Sparrow missiles for shooting down aircraft at 9 miles—they target the dislocation where $2M missiles designed for large ordinance are being misused against $500 drones with 30% effectiveness. Michael identified that "there isn't anything in the market that's been developed for counter drone at any significant distance." The opportunity isn't better missiles; it's purpose-built solutions for Group 1 and Group 2 drones (FPV quadcopters and small planes) where no appropriate system exists. Map where customers are forced to use expensive, inappropriate solutions—that's where new categories emerge.
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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
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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. 
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How Dexory turned early adopters into advocates by building continuous value delivery from day one | Andrei Danescu

Dexory builds data intelligence platforms for logistics, using autonomous robots to create digital twins of warehouse operations. With over $280 million raised through a recent preemptive Series C, the company has scaled from a bootstrapped startup to a full-stack robotics operation expanding across Europe and the US. In this episode of Category Visionaries, I sat down with Andrei Danescu, Founder and CEO of Dexory, to unpack how the company navigated early product-market misalignment, cracked the messaging for a category-creating technology, and maintained execution velocity as a capital-intensive business.
Topics Discussed:
Building in logistics after observing parts tracking failures in Formula One operations
The costly mistake: spending years on public space robots before committing to warehouse logistics
Why bootstrapping for five to six years forced product discipline before venture funding
Messaging shift from autonomous robot capabilities to inventory visibility pain points
Zero infrastructure change as a strategic product constraint for live warehouse deployments
Geographic expansion strategy using multinational customers for internal reference selling
How the convergence of AI adoption, sensor cost reduction, and industry data appetite created market timing
Maintaining commercial velocity as the primary metric for Series C readiness in full-stack businesses
GTM Lessons For B2B Founders:
Message to the problem, not the technology stack: When Dexory led with "world's tallest autonomous robots" and "scan 10,000+ pallets per hour," prospects responded with "what does it actually do?" The shift to leading with inventory visibility and stock control—a pain point customers immediately recognized—unlocked early traction. For category-creating products, customers need to map your solution to existing problems before they can appreciate technical differentiation. Andrei's insight: start with the problem customers know they have, then layer in technical superiority once you've established relevance.
Turn operational constraints into product requirements: Dexory designed around the reality that warehouses operate as "live businesses" that cannot pause for infrastructure overhauls. Zero infrastructure change became a core product spec, not a nice-to-have feature. This required autonomous navigation in complex, dynamic environments rather than controlled spaces. Founders building for established industries should identify non-negotiable operational constraints early and architect solutions that respect them rather than requiring customers to adapt their operations.
Build value expansion mechanisms before closing your first customer: Dexory established infrastructure for continuous product improvement from day one, treating early deployments as ongoing collaborations rather than transactions. Customers influenced roadmap priorities while Dexory delivered incremental value increases over time. This transformed buyers into advocates who took "point of pride" in the technology. The tactical approach: structure customer agreements and product architecture to support continuous delivery cycles that compound value rather than one-time implementations.
Use multinational customers as geographic expansion infrastructure: Instead of opening regional offices across territories, Dexory targeted global companies where a European deployment could generate US interest through internal reference calls. Andrei noted this creates "a lot stronger" references "because they're already part of the same company." The expansion velocity this enabled—UK to Europe to US without massive regional buildout—proved critical for a capital-intensive business. Founders should prioritize customers with multi-region operations who can accelerate geographic reach through internal advocacy networks.
Treat post-raise execution velocity as your next round metric: After Dexory's Series B, investors returned a month later to find the company "already ahead of plan." This consistent over-delivery on growth targets set up their preemptive Series C. For full-stack businesses where each dollar deployed takes longer to show returns, maintaining commercial momentum signals execution capability that justifies higher valuations. Andrei's warning: the temptation to slow down and "invest a bit more in product" after raising capital is exactly when founders need to double down on commercial traction as the North Star.
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How Sparrow achieved 14x revenue growth by targeting pain ownership, not pain awareness | Deborah Hanus

Sparrow automates employee leave management—a compliance nightmare that consumes thousands of HR hours annually at companies with distributed workforces. With $64 million in total funding through their recent Series B, Sparrow has achieved 14x revenue growth between their Series A and Series B by solving what became an "insurmountable problem" as states, counties, and cities each passed conflicting paid leave regulations over the past decade. In this episode of BUILDERS, Deborah Hanus shares how she scaled from $1.2 million in her first year while running everything part-time by discovering that the path to enterprise adoption wasn't solving employee frustration—it was quantifying the hidden costs of compliance risk, payroll errors, and retention that director-level HR leaders were desperately trying to contain.
Topics Discussed:
The regulatory explosion that made leave management unsolvable in-house: overlapping federal, state, county, and city requirements across distributed teams
How Sparrow pivoted from a $50-per-leave consumer product to enterprise software after discovering director-level buyers saw a fundamentally different problem than employees
Why Sparrow's biggest competitor is internal management rather than other vendors, and how this shaped their entire go-to-market strategy
The 4-10x ROI framework: how preventing paperwork errors that cost customers $1 million+ justifies $100K platform investments
Scaling from founder-led sales with zero sales background through systematic hiring processes—including reaching out to 100+ candidates for their first sales hire
Customer qualification strategy: vetting prospects not just for current pain, but for alignment with the product roadmap 2-3 years forward
 
GTM Lessons For B2B Founders:
Map pain perception across org levels to find economic buyers: Employees experienced leave management as "taking me a lot of time"—roughly 20 hours of taxes-level complicated paperwork. Director-level HR leaders, CFOs, and employment lawyers saw something entirely different: retention problems from employees leaving after bad leave experiences, litigation risk from compliance gaps across jurisdictions, thousands spent on employment lawyers for each leave event, and payroll calculation errors when state programs cover partial wages. Deborah's initial consumer product hypothesis failed because employees would only pay TurboTax pricing (~$50), requiring massive volume. The enterprise motion succeeded because strategic buyers owned the full cost stack. Map how pain manifests at each organizational level, then build your ICP around whoever owns the aggregate business impact rather than the tactical workflow friction.
Build ROI models around error prevention, not efficiency gains: Sparrow doesn't sell time savings—they sell payroll accuracy. Their typical customer sees 4-10x financial ROI because the platform prevents mistakes that cost significantly more than the subscription. When paperwork is filed incorrectly, employees miss 60-70% of pay for 12-20 weeks, and with 70% of Americans living paycheck-to-paycheck, employers often make up the difference to prevent attrition. A $100K Sparrow investment typically saves $1M+ in payroll corrections alone, before counting the thousands in hours HR spends with employment lawyers for each leave event. Calculate the true cost of the status quo—including error correction, compliance penalties, and retention impact—not just the labor hours your product eliminates.
Design qualification frameworks for roadmap fit, not just current pain: Deborah emphasizes that "everyone has this problem, but not everyone is going to be a fit for the product today and where it's going to be two years from now." Sparrow deliberately vets whether prospects will be excited about their product evolution 3-4 years forward, not just whether they have leave management pain today. This drives retention and customer advocacy as capabilities expand. Build qualification criteria that assess prospect-product alignment across the entire customer lifecycle—including future module adoption, integration depth, and use case expansion—rather than optimizing only for closing deals on current functionality.
Treat hiring as systematic sourcing, not urgent gap-filling: Despite being in "back-to-back calls all day" unable to "send order forms fast enough," Deborah took time to reach out to approximately 100 candidates to make their first sales hire. She emphasizes defining what each role should accomplish 5-10 years out, then building sourcing strategies to achieve 50% confidence in that long-term outcome. This intentional approach—coupled with her value of "scaling intentionally"—enabled efficient growth without typical scaling chaos. Resist the startup default of "just hire someone fast." Instead, invest upfront in role definition (including the 5-year trajectory), source systematically rather than opportunistically, and accept lower short-term velocity for higher long-term scaling efficiency.
Recognize emotional volatility as statistical artifact, not signal: Deborah reframes the classic startup "highs and lows" through a data science lens: with sparse early data, founders overfit to individual signals. One person saying "your product is stupid" triggers existential doubt; one saying "everyone should use it" creates irrational exuberance. As companies scale and data accumulates, the noise averages out—70% neutral-to-good outcomes with 30% fires becomes manageable rather than anxiety-inducing. She found scaling "much easier than that first year" because "you can sort of plot out your trend line and you can see where you're going." Build systems to accumulate data points faster (more customer conversations, more experiments, more leading indicators), recognize that early-stage emotional swings reflect sample size rather than reality, and make decisions based on trend lines rather than individual data points.
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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
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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