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Pivotal early lessons of today's best startups.
Welcome to the focal podcast where we go deep with some of today's best founders and operators on ONE crucial lessons from their early days.
This podcast is not the usual "highlight reel" startup podcast that goes one inch deep across 20+ topics. Rather, we ask the questions you’d ask if you were sitting across from them. No fluff, just the real, actionable insights you’d get if these founders were mentoring you 1on1.
We cover topics including:
- What worked and why.
- Costly mistakes and how they fixed them.
- Frameworks that truly made a difference.
- Tactics to move faster.
- What they wish they’d known sooner.
- And much more!
"Only a fool learns from their own mistakes. The wise learn from the mistakes of others."
Welcome to the focal podcast where we go deep with some of today's best founders and operators on ONE crucial lessons from their early days.
This podcast is not the usual "highlight reel" startup podcast that goes one inch deep across 20+ topics. Rather, we ask the questions you’d ask if you were sitting across from them. No fluff, just the real, actionable insights you’d get if these founders were mentoring you 1on1.
We cover topics including:
- What worked and why.
- Costly mistakes and how they fixed them.
- Frameworks that truly made a difference.
- Tactics to move faster.
- What they wish they’d known sooner.
- And much more!
"Only a fool learns from their own mistakes. The wise learn from the mistakes of others."
26 Episodes
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Clay pioneered GTM engineering and went from $1M to $100M in ARR in 2 years. I talked to the person who invented the role of GTM Engineer at Clay.Yash Tekriwal, Clay's first GTM engineer - back when the $3B company was still figuring out what that even meant.What started as one person drowning in too many jobs (RevOps + Sales + BDR + data analyst) has since become a new category that's now reshaping how startups think about go-to-market.You’ll learn:Why RevOps is "maintenance" but GTM engineering is a growth leverThe skills that define a great GTM engineer today (hint: it involves vibe coding)What "treating go-to-market like a product" actually looks like in practiceTwo org models for GTM engineering teams - and which to start with"Automate the manual, but don't automate the important"In Today's Episode We Discuss:01:23 - The origin story of GTM engineering at Clay and why the term is polarizing05:02 - GTM engineer vs RevOps: maintenance function versus growth lever07:31 - Treating go-to-market like a product team, not an individual sport10:42 - Three experiments every GTM team should run on inbound and outbound15:24 - The essential GTM tech stack: CRM, enrichment, sequencing, and what actually matters19:08 - Tools founders should consider when getting started—and the automation trap to avoid22:12 - Zero to $1M: be thrifty on tools and process information manually25:38 - What to look for in your first GTM engineering hire (hint: it's not technical skills)28:43 - Signals that you need to hire a GTM engineer for outbound vs inbound motions31:45 - Scaling past $10M: specialize fast and the hyperscaler dilemma36:01 - Two org models for GTM engineering: centralized hit team vs embedded engineers40:22 - The ideal GTM engineer profile: tinkerers, not traditional engineers43:33 - Why engineers are not the ideal candidates for GTM engineering roles45:19 - Can salespeople become great GTM engineers? The sales hacker archetype47:26 - Resources to learn GTM engineering: Clay University, substacks, YouTube channels, and agencies51:00 - Top three things founders must know about GTM engineering at any stage52:16 - The most creative GTM engineering builds: satellite imagery, hospital capacity, and custom memes56:24 - Personal lessons from scaling at Clay: ego death, pivoting, and balancing maintenance with big bets59:42 - The one thing Yash would change: stop oscillating and let problems become obvious
The Horizontal vs Vertical AI Debate: Why This Ex-Meta AI Researcher Is Betting Big on Horizontal Web AgentsShould you build narrow (vertical) or go broad (horizontal) in AI? This episode unpacks why one PhD researcher abandoned his working vertical product to chase a much riskier horizontal bet - and why VCs leaning heavily into vertical AI might be missing something.Abhishek Das is the co-founder and co-CEO of Yutori, which has raised over $15 million from Radical Ventures, Felicis, and prominent angels including Ali Gil, Sarah Guo, Scott Belsky, and Guillermo Rauch. Previously a research scientist at Meta's FAIR lab, Abhishek holds a PhD from Georgia Tech where he pioneered work on AI agents that can see, talk, and act starting in 2016.In Today's Episode We Discuss:00:53 - Why how we interact with the web hasn't changed in three decades and what will break that02:27 - The coming shift from manual browsing to AI assistants performing tasks in the background05:57 - What "agents" actually meant in ML research before the term became overloaded06:14 - Why 90% accuracy per step creates catastrophic failure rates over multi-step workflows08:46 - The behavior pattern humans nail intuitively that machines struggle with: backtracking from errors10:11 - The DoorDash experiment: building an end-to-end food ordering agent that never shipped12:58 - Why training on sinle websites leads to memorization instead of generalization13:03 - The dopamine problem: some tasks users don't want automated15:08 - Why capability-scoped beats website-scoped: the pivot to read-only horizontal agents18:05 - Three criteria that drove the horizontal decision: research, user value, and data strategy24:18 - Scouts API launch: why different channels have different risk appetites for web agents26:30 - Flying close to the sun: how Yutori competes with hyperscalers on horizontal AI30:32 - What VCs should actually test for in horizontal AI teams beyond founder horsepower32:10 - Why three-month roadmaps are the only reasonable planning horizon in AI today33:05 - The dogfooding ritual: every team member rotates through user feedback weekly34:50 - Why research and product can't be siloed and how ideas flow both directions36:03 - The uncomfortable truth: end users don't care about your research breakthroughs37:32 - The Nintendo Switch 2 problem: aggregating individual feedback into systemic fixes39:35 - Reframing web agents as "buyer's agents" that filter the internet on your behalf40:59 - The simulation bet: training agents on cloned websites for high-stakes irreversible actions43:05 - Why initial team skepticism about Scouts' value proposition was completely wrong45:01 - How scout reports contextualize results with reasoning and ingest feedback over time47:52 - The core insight test: where does your instinct lie across research, market, and domain?49:36 - The hiring trap: why preemptively hiring sales leadership to impress VCs backfires51:18 - The 12-year-old advice that still guides him: "Be a sponge when entering a new space"53:05 - Non-negotiables: walking the dog with podcasts and personally reading every user email54:49 - What founders actually need from VCs: direct and timely feedback, not just capital
Stop launching into the void and start creating campaigns that actually get attention.Sumeru Chatterjee reveals the exact 10-week playbook he's used to generate millions of impressions at four unicorns, including why most B2B launches fail and how to weaponize your investor network for maximum impact. You'll discover why emotion beats logic in B2B marketing and why treating existing features as "new launches" is the growth hack nobody talks about.Sumeru Chatterjee is Head of Growth at CoWorker AI, the first AI agent for complex work. Previously an early employee at four unicorns and founder of LaunchMob agency, Sumeru orchestrated CoWorker's launch that generated over 1 million impressions in a single day with 75 investors coordinated like a military operation.In Today's Episode We Discuss:03:45 - Mine 20 customer calls for launch gold using AI07:29 - Stop hiring humans: Why fear sells better than features10:23 - The 200 dream customers exercise founders skip14:50 - Find 50 influencers who already own your audience18:05 - Three distribution channels max or you'll fail everywhere20:40 - Everyone claims differentiation but nobody actually commits29:48 - The $20 book that made Hormozi $60 million35:36 - Competitive positioning vs contextual positioning changes everything38:28 - 46 creative concepts: From white papers to doormats44:16 - Product Hunt is dead for B2B launches54:05 - Coworker's investor spreadsheet that drove 1M impressions01:08:44 - Launch every two weeks or become irrelevant01:11:03 - OpenAI launches Slack integration like it's revolutionary01:14:37 - Your 10 employees are connected to 500,000 people01:15:37 - Different is better than better always wins01:18:04 - Master one funnel before attempting anything else
The forward deployed engineer model took Happy Robot from zero to millions in revenue in under 2 years.In this episode, Pablo Palafox reveals exactly how to implement Palantir's FDE motion at a startup - including when to use it, who to hire, and the costly mistakes to avoid. Learn why embedding engineers directly with customers beats traditional sales approaches for complex AI products.Pablo Palafox is the co-founder and CEO of Happy Robot, the AI-native operating system for supply chain and logistics. Prior to Happy Robot, Pablo completed his PhD in computer science and deep learning. Happy Robot has raised over $60M from investors including a16z, YC, and Base10, and serves enterprise customers like DHL.In Today's Episode We Discuss:02:01 - When the CEO realizes they're actually the company's first FDE05:13 - Why embedding with customers beats having a sales pitch09:01 - Stop trying to copy Palantir - build your own FDE playbook13:25 - The critical difference between FDEs and deployment strategists17:19 - How Discord servers led to billion-dollar freight broker clients21:33 - FDEs must become industry insiders, not just tech experts25:46 - When NOT to use the forward deployed engineer model30:55 - The FDE hiring secret: Look for "nerds who can sell"36:35 - Why FDEs need 1-2% equity vs 0.1-0.5% for regular engineers41:49 - An FDE's day: 80% building, 20% with customers onsite47:00 - The $30K to $3M expansion playbook for FDE accounts52:10 - Building FDE "pods" for vertical specialization56:27 - Why waiting to verticalize FDEs was their biggest mistake59:19 - The 10X deployment accelerator most startups forget62:00 - Why FDEs will soon build entire vertical products autonomously64:58 - When to transition from "things that don't scale" to scale67:11 - The one place every vertical AI founder must go immediately
Why saying "no" is the secret to growing faster as a startup founderMost founders think raising $100M means spending aggressively. Adit Abraham raised $108M and spent only $1M - while landing Fortune 10 contracts very early on and having experienced zero enterprise churn to date.In this episode, he reveals the counterintuitive focus strategies that helped Reducto turn documents into data better than anyone else, including why they fired a $5K contract, limited engineers to one priority per week, and spent months recruiting a single PhD instead of scaling the team quickly.Adit Abraham is the co-founder and CEO of Reducto, an AI company that transforms documents into structured data for language models. He previously worked at Google and attempted other startups before Reducto, where he learned the hard lessons about focus that now drive his company's success. Reducto has raised over $100M from A16Z, Benchmark, First Round Capital, and Y Combinator.In Today's Episode We Discuss:02:04 - Pivoting from a viral product before Y Combinator even began05:48 - How free computer vision consulting revealed real product-market fit07:29 - The exact moment founders know they've found product-market fit08:03 - Why going one layer deep on ideas is the most dangerous founder trap11:10 - Choosing two PDF features over 35 file types competitors supported14:54 - Turning down construction document contracts worth millions in revenue17:10 - Past startup failures that became the blueprint for saying no successfully22:25 - Cutting engineer to-do lists from 10 items to 1 weekly priority27:45 - The doctor-patient framework that makes rejecting customers feel collaborative31:35 - Maintaining velocity while scaling from 4 to 20 high-agency employees36:08 - Prioritization without spreadsheets: qualitative judgment over point systems38:50 - Spending $1 million after raising $108 million from top-tier VCs40:52 - Why their first research hire is one of 10 best in world for document AI46:35 - The fitness trainer analogy every founder misunderstands about company building49:14 - When "stay lean" advice becomes the wrong strategy for your stage50:16 - Why full-time commitment creates space for different experiments than side projects52:04 - The VC conversation that made sharing bad news feel safe instead of scary
Every bottom-up PLG company faces this tension:PLG gets you in. Enterprise funds the future. They need vastly different products - how do you prioritize?If you try to please both motions at once, you starve both.How to balance PLG with enterprise is what I discuss with Feross Aboukhadijeh, the CEO and co-founder of Socket ($65M raised from a16z, Abstract, Dylan Field, Aaron Levie, and other).Socket, a developer-first security platform protecting code from vulnerable and malicious dependencies. Before Socket, Feross was an open source maintainer and developer who built widely-used libraries.In Today's Episode We Discuss:01:43 - How developer background dictated Socket's PLG-first strategy over enterprise04:50 - Building a GitHub app in 48 hours to avoid launching with zero user capture07:56 - The counterintuitive rule: launch with intentionally missing enterprise features10:53 - Why Socket deliberately ignored vulnerabilities despite every competitor offering it11:20 - The dirty secret of startup pricing pages most founders won't admit15:37 - How Socket mistakenly modeled pricing after GitHub's public/private repository strategy16:08 - Why cryptocurrency companies exposed a fatal flaw in Socket's pricing model18:19 - Going straight to enterprise sales to defend against fast-following competitors19:37 - Why product quality loses to inferior products with superior go-to-market21:36 - Socket's first enterprise deal was $500 and they kept doubling until pushback24:27 - When PLG and enterprise roadmaps become zero-sum resource battles26:27 - The strategic mistake of abandoning PLG motion after enterprise traction28:54 - How developer awareness creates unfair advantages in security tool evaluations29:23 - Enterprise handholding versus self-serve product design create opposing company muscles33:01 - Figma's playbook: how connecting free-to-enterprise destroys customer acquisition costs36:12 - The biggest regret: not building the PLG funnel before enterprise distraction hit40:57 - Getting SOC 2 on day one would have parallelized six months of enterprise delays41:00 - The monstrosity trap: second-time founders who hire VPs before product-market fit40:13 - Why the popular advice to limit cap table size is fundamentally wrong41:05 - Why Feross regrets turning away a $10K angel investment over ego43:24 - The technical founder's fatal mistake: choosing to code over customer conversations45:04 - Why selling before building feels wrong but saves months of wasted development45:13 - The Mom Test: the book that teaches founders how to extract honest customer feedback
Most startup founders discover they have a culture problem when things are already breakingToday, we discuss how to build the right culture before the wrong one costs you millions.Every founder thinks about culture, but almost none do it right. Abhi Sharma, a second-time founder / now the founder and CEO of Relyance AI, learned this the hard way after reaching several million in ARR. Things were breaking and he couldn’t pinpoint exactly why. Now he shares the exact framework he uses to build culture that actually scales - from defining your company's "invariant" to implementing tactical excellence across every department.Abhi Sharma is the co-founder and CEO of Relyance AI, a company building super intelligence for data security. To date, Relyance has raised over $60 million from top-tier investors including Menlo Ventures, Unusual Ventures, and Microsoft's M12 Venture Fund.In Today's Episode We Discuss:00:01:41 - Why culture always feels like an afterthought until systems break and you can't explain why00:03:35 - The exponential dissipation problem: how founder control over culture disappears faster than you think00:05:09 - Three catastrophic ways poor culture manifested at Relyance: hiring mistakes, product strategy disconnects, and enablement failures00:09:59 - Why shouting culture values from the rooftops fails: the unreasonable hospitality pivot that actually worked00:12:14 - The $X million ARR wake-up call: when Abhi realized he was getting hires wrong and had to define operating principles00:15:25 - From weekend reflection to company DNA: the exact process of distilling culture down to actionable principles00:17:11 - The one piece most founders iterate on after writing culture docs (and why examples matter more than principles)00:20:21 - Your company's invariant: why every startup is ultimately about one core idea that never changes00:23:56 - Stripe's GDP example: how the best companies anchor to fundamental human behaviors, not features00:25:14 - The Hedgehog Concept decoded: three components that create your competitive moat (straight from Jim Collins)00:28:06 - Data journeys as superpower: why Relyance's unique differentiator became their core product feature00:30:08 - Economic driver vs. pricing: why most founders confuse the two and how it kills scalability00:32:54 - Dominance friction: how misalignment between business model and customer value creates disruption vulnerability00:33:28 - Costco's profit-per-square-foot model: the counterintuitive pricing strategy that drives more volume00:37:30 - Why it took three years to figure out Relyance's economic driver (and why that's perfectly okay)00:38:50 - Culture is actions, not words: why cultural values without operating blueprints are worthless00:40:57 - The trust operating principle: Stockdale Paradox, job vs. responsibility, and good news fast vs. bad news faster00:45:20 - How job versus responsibility transforms employees into owners (and why most companies fail at this)00:47:23 - Why "you don't get credit for 80% to the moon" is the ultimate accountability framework00:49:16 - Making escalation a good word: rewiring team psychology around bad news and urgency00:51:41 - The belief system cherry on top: three statements that tie everything together and fit on a sticker00:55:19 - Tactical excellence: why Control-C, Control-V matters more than inspiration (and how to operationalize culture daily)00:58:20 - The monthly new hire ritual Abhi still does himself: why culture onboarding can never be delegated00:59:49 - Founder mode vs. micromanagement: Brian Chesky was right, but where's the line?01:01:22 - The X vs. X+Y million ARR question: why every growth gap traces back to cultural problems01:03:26 - Popular bad advice: why "hire executives and step away" is wrong and when founder instinct trumps expertise01:05:06 - The brutal honesty test: if you're not all-in, don't start a company (and why vanity startups fail 100% of the time)01:06:16 - Reflection time as competitive advantage: how America's polymaths and founding fathers made progress through going inward01:06:48 - The first five deals rule: why Abhi banned VC introductions for Relyance's initial customers (and why it was magical advice)01:09:36 - Product-market fit vs. AI hype: are you hacking your way to ARR or truly iterating toward customer pain?
The software industry's 30-year business model is becoming obsolete - this founder is betting his company on what comes next.Why listen: Jacob Beckerman reveals why the cost of code approaching zero means every software company needs to rethink everything - from margins to moats to hiring. He's open-sourcing his entire codebase, hiring poets alongside engineers, and building for a world where brand matters more than features.Jacob Beckerman is the founder and CEO of Macro, an AI workspace startup that has raised over $32 million from Andreessen Horowitz and Box Group. He previously conducted AI research at Penn and worked at Bridgewater Associates.In Today's Episode We Discuss:00:00 - Why everything you learned about building software companies is now obsolete01:47 - The three radical changes coming as software development costs hit zero05:47 - Why 93% gross margins are dead and cursor operates at 20%08:28 - The new rulebook: ambition, openness, and brand over features11:06 - Why being "principled" and narrow will kill your startup13:11 - From seven-figure PDF reader to replacing Slack, Notion, and Linear simultaneously17:19 - Open-sourcing your entire codebase as competitive advantage20:50 - Why you're selling integrations and intelligence, not software22:26 - Hiring poets and MFAs instead of MIT engineers27:50 - Software brands becoming like fashion: Salesforce as Kirkland30:34 - Traditional moats are dead—what actually matters now32:32 - "Would you rather wrap a database or superintelligence?"35:00 - Infinite demand for intelligence vs finite meeting summaries40:00 - Why zombie unicorns have their heads in the sand about AGI42:26 - Battle scars matter more than startup advice47:22 - "Get the hell out of the way and let me go on my journey"
Pump.co is one of the fastest growing YC companies. They got there partially by building an incredible sales team, stacked with talent that was overlooked by many.In this episode, Paul Russo, a sales leader at Pump unpacks a sales-hiring system built for aggressive, early-stage growth. You’ll hear how to source elite junior talent, pressure-test them with mock cold calls, and ramp them into technical AEs who still outbound hard. He also shares promotion gates, call quotas, and the culture required to chase incredibly ambitious goals.Our guest Paul Russo is employee #1 and a sales leader at Pump.co, the company that helps startups save up to 60% on cloud costs - for free.In Today’s Episode We Discuss:05:09 - The “weird” target formula forcing 20% month-over-month revenue growth.07:48 - Do individual-sport athletes outperform team players in enterprise sales?09:10 - Outbound-first: hire technical AEs over “been-there enterprise” veterans.11:22 - Why we prefer scientists over business majors for AWS selling.11:43 - Recruit “future founders” and frame the role as founder school.13:24 - Scale with hungry rookies led by seasoned pod leaders.15:24 - YC Bookface + Top-20 schools: an elite sales-athlete pipeline.20:02 - Cold-call candidates with traction—sell the unicorn vision first.23:10 - COO screen routes talent; extroverts go sales, introverts to ops.26:01 - Mock cold calls, no context: test grit, tone, coachability fast.29:09 - Demand real conflict stories—“I never fight” is a red flag.29:52 - Assess disciplined routines: 4:30am calls require athlete-like habits.31:10 - Explain FinOps simply: reserved instances are leases, not compute.35:39 - Cultural bar: 12–16-hour days, aiming for a 2028 IPO.37:48 - Onboarding: Pump University, daily mocks, Nooks-powered 750-call days.40:36 - Two-month ramp; PIPs are coaching tools, not pre-firing.43:04 - Promotion ladders with hard gates; AEs still dial 250/day.47:08 - Friendly pod rivalry + “rebuttal ball” spreads best practices.53:41 - First sales hire playbook: top-school hunter, athlete, founder-aspiring—equity-heavy.
Most founders wait too long to invest in marketing—and by the time they realize their mistake, they've already lost the race. That’s why Paul Veugen challenges the conventional wisdom that marketing should wait until product-market fit, arguing that building your growth engine from day one is the only way to achieve predictable, scalable growth.Paul Veugen is a serial entrepreneur and investor currently building Detail, a video creation platform that enables everyone to share their story faster. He previously founded and led Human to an acquisition by Mapbox, and Usabilla which sold to SurveyMonkey for $100 million in 2019. He also led product and go-to-market at Color, which has raised close to $500 million from top-tier investors.In Today's Episode We Discuss:02:01 - Why "don't invest in marketing until product-market fit" is terrible advice for founders03:37 - How marketing experiments are actually customer discovery in disguise07:26 - Why cold outbound is dead and founders need to build momentum before reaching out13:27 - The brutal math: You need 20% month-over-month growth to hit $1M ARR in 12 months19:05 - How to brute force your way to finding winning marketing channels26:05 - Why marketing channels take 90+ days to show results (and most founders give up too soon)34:13 - Overcoming the fear of looking stupid in public when building in public40:58 - How positioning drives product decisions, not the other way around47:44 - Why AI features are attention grabbers, not value drivers49:18 - The messy middle: Why channels feel broken before they explode55:05 - How being an investor makes you a better founder (and vice versa)57:58 - The problem with MVPs and why testing individual ingredients is useless01:02:23 - Why building a startup is an endless expedition, not a sprint
If you don’t enforce the bar, you lower it.This episode tackles the uncomfortable line between being humane and looking out for employees while also being a high-performing organization - and what a real culture reset looks like when you’ve let it slip.Our guest is Cat Noone who went through such a major reset herself with the company she co-founded, Stark - which is trusted by over 50,000+ companies and >$10M raised from Uncork and us at focal.In Today's Episode We Discuss:01:46 - How being hell-bent on mission while avoiding "bro culture" backfired03:54 - The early warning signs that performance was drifting at Stark04:14 - Why I stopped doing reference checks and paid the price08:38 - How the lowest performer sets your company's bar, not the best09:17 - When busy work replaces real productivity in remote teams12:32 - You can't have shitty input AND shitty output - pick one15:01 - Why founder insecurity about being "employee friendly" kills companies18:28 - The brutal emotional cost of firing people you've worked with from day one25:00 - How to communicate layoffs to survivors and rebuild momentum29:39 - Why urgency beats speed for maintaining quality standards33:38 - Demo Thursdays as quality control checkpoints, not show and tell37:06 - The four-day work week experiment and why Fridays aren't free40:01 - Why most startup principles are worthless wallpaper44:12 - If you're going to cut deep, cut deeper - don't play it safe45:58 - Move fast and break things is an excuse to ship shit48:34 - Get an executive coach before you think you need one
Stop pitching the end state. Sell the smallest step that proves you can provide value.This episode dives in on how to decouple a north‑star company vision from a scrappy, testable product pitch that customers can adopt today. You’ll learn how to use positioning as your lever - choose sharper category language, cut scope to true table stakes, and listen for unsolicited buy signals- to move from zero traction to real pull. On top, you’ll learn what the slowest, costliest way to validate an idea is; how to identify table stakes; and the signals that tell you when to broaden your ICP. In Today’s Episode We Discuss:01:35 - From “Stripe for Support” to reality: what we missed03:48 - API‑first exposes every seam; validation speed plummets07:59 - The worst enterprise pitch: “engineers, please write more code”11:23 - Name your category—or wear Zendesk/Intercom’s handcuffs16:06 - Set true table stakes; timebox the MVP ruthlessly21:02 - Buy‑now signals: users volunteer payment without a hard sell23:49 - Ethical pre‑selling: describe the future, then sprint to it25:12 - Turn case studies into copy—speak customers’ exact language27:38 - Vertical → use case → market: DevTools → Technical Support → B2B30:54 - Outrun feature spreadsheets with a customer collaboration thesis40:41 - What collaboration means: Slack escalations, issue trackers, shared context47:15 - Map features to FRT, CSAT, retention—not “shiny UI” claims50:34 - Homepage discipline: kill vanity metrics and shortcut bragging52:21 - 70/30 rule: discovery + founder conviction against higher‑order shifts
You have to be so much better than the incumbent if you want to have even the slightest change.This episode is a tactical masterclass on early-stage B2B sales. You’ll learn how to nail the first meeting, architect modular demos, multi‑thread like a pro, and turn proposals into “Champion Empowerment” decks that actually close. We also cover ROI modeling, executive sponsorship, outbound strategy, and the exact behaviors that separate A‑players from everyone else.Our guest is Greg Costigan leads the sales team at Performica and has built and led GTM organizations at Box, Zuora, Zenefits, LearnUp, Hone, and MindGym. He’s closed complex enterprise deals, championed award‑winning programs (e.g., Pinterest’s Brandon Hall–recognized L&D initiative), and specializes in taking startups from founder‑led sales to scalable processes.In Today’s Episode We Discuss:01:33 - Sales process is a science—ditch gut feel for repeatable rigor.04:51 - Stop skipping steps—credibility beats the ‘one‑call close’ myth.07:01 - First meeting playbook: GGGA, pre-read, ruthless prep.10:57 - Lead with a hypothesis—change the buyer’s frame (Challenger).13:32 - First-call exceptionalism: come in hot and create momentum.14:51 - Yes, demo on call one—and land a clean close.19:44 - Multi-thread fast: champion texting, exec sponsors, rule of threes.22:19 - Demo excellence: send agenda early, close BANT/MEDDICC gaps.23:59 - Modular demos: tailor admin, user, integrations to stakeholders.27:51 - End every demo with a scoping or proposal—never ambiguity.34:14 - Turn proposals into a Champion Empowerment deck that sells itself.36:54 - No exec sponsor? You’re at risk—fix it before forecasting.38:20 - Build a simple ROI model—finance will ask, be ready.54:49 - Outbound isn’t dead—SDRs matter more than ever.
Moving upmarket, the right wayWhen should a startup go from SMB to enterprise - and when should you not?I break this down with a former revenue leader at Box, SurveyMonkey, Asana, etc - Matt Harmon (ex‑Box, Asana, SurveyMonkey). We discuss the real signals for enterprise readiness, why security/compliance readiness matters, and why “we’ll build it if you buy it” kills confidence. We also compare playbooks for existing vs. new categories, the land→expand reality, and how to balance self‑serve revenue with enterprise ambitions.In Today's Episode We Discuss:1:42 Why the “go upmarket” conversation starts early4:53 Company readiness: security, compliance, SEs, forecasting shifts10:57 Signals it’s curiosity-only vs. a real enterprise opportunity16:45 “Is it someone’s KPI?” and the need for true pain/need18:36 Existing category = one path to buy (ripping/replacing)22:52 New category upmarket: shared services & proving uniqueness28:28 Land→expand and product-led reality33:08 Don’t force a model—map the customer journey first37:57 Positioning and intellectual honesty at ~$1M ARR40:00 Category creation vs. innovating in an existing one45:07 Why not to fear SMB/self-serve revenue47:15 Don’t over-index on “sell to pain” for new categories50:15 Founder advice: embrace ambiguity and EQ52:25 What great VCs do: back leaders who can hire leaders
Bootstrapping to $10M ARR was easier than raising the first $20M.This episode is a masterclass in founder decision-making: choosing (and parting with) co-founders, bootstrapping to real revenue, then raising at scale - without losing the plot. Expect frank takes on titles, burn, investor selection, and the moral weight of taking other people’s money.Duncan Weatherston is the co-founder and CEO of Smile Digital Health, a leading healthcare data platform company. He and his team bootstrapped to ~$10M ARR before raising a $20M Series A, and are now well past $50M in ARR.01:40 - Why start with co-founders vs going solo in healthcare SaaS06:27 - How to vet co-founders: proof of execution over chemistry06:58 - The #1 mistake: trusting claims without validating capability09:39 - Early-stage stars rarely scale—how roles must evolve12:25 - Title inflation trap: why early VP labels backfire later12:47 - Be mercenary with misfits: fairness to the team > feelings16:56 - Create IC ladders: don’t “promote” top engineers into management18:27 - Founder vesting: avoid dead equity with 5–6 year schedules19:46 - Why they bootstrapped first: expertise, low burn, paying customers22:40 - Would he raise earlier today? Services-led product tradeoffs25:47 - The $20M decision: buyouts, tailwinds, and scaling delivery34:04 - Taking VC creates a moral obligation—here’s what that means36:56 - 2021 mistake: “spend aggressively” and adapting too slowly45:59 - The do-over: fix org design, roles, and accountability sooner46:25 - Popular advice he rejects: don’t contort your playbook to fads48:41 - PMF obsession: identify your repeatable sales unit before scaling51:03 - Best investor advice: hire actual A-players, not just roles
When every YC batchmate wanted their product and investors threw money at them, Arc made the unthinkable decision - abandon the business. Learn the framework for identifying false product-market fit that saved Arc from the fate of their now-struggling competitors.Basile Senesi is the Chief Revenue Officer at Arc, the financial operating system for growth companies. He's built multiple YC companies including Phonebox (raised $500M+), is a prolific angel investor, and owns Chateau Pavo winery in Sonoma.In Today's Episode We Discuss:02:17 - How Arc originated $100M in loans then killed the product07:25 - The warning signs that made them abandon massive revenue growth10:49 - Why unit economics matter more than investor expectations14:16 - How to convince investors to kill your fastest-growing product16:38 - Pivoting from lending to cash management during market chaos19:05 - Why do the hard thing first in fintech22:14 - Everything is a funnel: validating ideas without building27:34 - Building operating models before you have revenue34:50 - Why startups need pessimistic salespeople37:00 - How to know when you're building the wrong business40:14 - Not all revenue is created equal in venture43:11 - Hire for the long haul, not the next milestone46:54 - Tactics equal strategy in early-stage startups50:49 - Learning what not to do is your competitive advantage
Don Muir turned down his dream job at Apollo to build the AI-powered bank Arc.This episode goes through the exact playbook the former BCG consultant and private equity investor used to de-risk his leap into entrepreneurship - including his 3-point checklist that allowed him to say no to Apollo. Don shares hard-won lessons about finding product-market fit, recruiting world-class talent, and why it took 190 rejections to get to his first 10 customers.Don Muir is the co-founder and CEO of Arc, a zero-asset commercial bank powered by AI that offers intelligent capital management and private credit to ambitious businesses. To date, Arc has raised over $180M in debt and equity.In Today's Episode We Discuss:01:30 - Why I chose debt over equity and existing markets over new ones04:10 - The bottoms-up approach to finding your unique right to win08:44 - From crowdfunding communities to non-dilutive capital: 4 pivots to product-market fit11:42 - Execution over innovation: Why first-time founders shouldn't reinvent the wheel14:14 - The 3-point checklist before rejecting Apollo's offer16:26 - Getting 10 CEO signatures with just a Stanford email address21:49 - 190 rejections, then 10 straight wins: The LOI breakthrough moment23:29 - Finding fast-moving waters: When to pivot vs. persevere25:28 - The Stanford.edu email hack that opened CEO doors32:25 - Why technical co-founder pedigree is overrated (but VCs disagree)38:07 - How one $100k check turned hundreds of "no's" into "yes's"42:32 - The sleepless nights that forced the Apollo phone call45:59 - When your biggest rejection becomes your largest partner49:41 - Why the "safe path" is actually the riskiest choice52:55 - The venture capital myth: Why most startups don't need VC money
In this episode, we dive deep into startup sales hiring with Anis Bennaceur, a masterful talent scout who's cracked the code on building exceptional early-stage teams. You'll discover why most founders hire wrong, how to spot founder-DNA in candidates, and the brutal interview techniques that filter out B-players before they contaminate your culture.Anis Bennaceur is the co-founder and CEO of Attention, a startup building AI agents that revolutionize sales conversations. A second-time founder, Attention has raised close to $20 million from Eniac, 645 Ventures, Liquid2 Ventures, and Alvin.In Today's Episode We Discuss:01:25 - The Triangle of Talent: Why 80% of your employees are useless04:26 - Level 5 superstars can't be trained - they're born that way05:43 - Your first hires must think like founders or you'll fail10:25 - Why Anis only hires people obsessed with Paul Graham essays15:58 - The $100K hiring mistake that saved Attention's culture18:35 - Two sales candidates talked each other out of joining - here's why21:40 - Always hire salespeople in pairs to create internal competition25:34 - The midnight email test that reveals true A-players27:56 - One interview question that exposes scrappy hackers instantly31:23 - Using ChatGPT to detect hiring red flags you missed35:02 - Three biggest life failures: The therapist interview technique41:42 - Why Brian Chesky's anti-selling method filters out mercenaries54:54 - The Saturday night Slack test that predicted employee turnover56:52 - How political extremism kills startup culture58:25 - "If you had the contract, why wouldn't you sign?"1:05:15 - Rejecting candidates who negotiate reveals commitment issues1:12:13 - Stop listening to customers - they'll build you a faster horse
Most founders get sales rep productivity wrong - and it kills their growth.If you’re thinking about hiring your first sellers - or wondering why the ones you hired are struggling to hit their numbers - this one is for you!In this week’s focal podcast, I unpack in detail how to build a repeatable sales playbook that actually works with Russ Thau who drops the sales productivity formula he used to scale multiple companies past $50M in revenue, including taking Box, Intercom, Envoy, SuccessFactor, Airtable, and Launch Darkly. In Today's Episode We Discuss:02:09 - Why time is the one thing you can't fabricate in sales03:43 - How many calls can someone realistically take per day?03:53 - The control experiment: Why founders should do calls first06:22 - First calls vs. follow-ups: How to benchmark properly07:46 - Why reps need 30 minutes prep time per call09:39 - The critical 5-minute buffer between calls09:49 - How call complexity changes everything (Intercom vs. SuccessFactors)11:55 - Why follow-ups must happen within hours, not days12:07 - The context switch problem with outbound prospecting14:24 - How long founders need to keep selling alongside reps14:56 - Why hire two AEs at once, not just one17:22 - The 90-day signal that reveals rep quality19:04 - When to hire your first sales leader (3-4 AEs)21:26 - The biggest mistake: Forgetting reps are human beings22:31 - Why 10% conversion rate is your absolute minimum24:46 - The velocity math: 100 calls to close 10 deals26:02 - How conversion rates reveal your true ideal customer28:20 - The $10-30K deal size "no man's land"33:00 - Why companies set $36K minimum deal sizes (the math revealed)37:19 - How to escape no man's land and sell bigger deals43:07 - Enterprise vs. velocity rep skills: What's the difference?45:04 - Understanding "the real deal" and your sales methodology48:55 - Why sales productivity is simpler than you think
What got you here won't get you there - the brutal truth about scaling from $1M to $50M in revenue.If you keep doing what you were doing to get to $1M ARR, you won’t get to $3M ARR. What got you to $3M won’t get you to $10M, what got you to $10M won’t get you to $20M, and so on. The hard truth about rocket ship startup growth is that you have to reinvent yourself at every major revenue milestone you reach. But unfortunately, most founders can't do it. They cling to what worked, scale what's broken, and wonder why growth stalls.In this episode, I sit down with Russ Thau, a former founder and seasoned revenue leader specializing in scaling companies from $1M to $50M in revenue, to discuss what you have to do when on the Sales side to reach $50M+ in revenue as fast as possible.Russ has has scaled revenue from single digit millions to $150M+ and two IPOs at companies such as Intercom, Box, and Envoy, and he's also advised companies like Airtable and LaunchDarkly since they were sub-$1M in revenue.In Today's Episode We Discuss:02:02 - Why being a good salesperson is actually bad for getting to $1M revenue04:31 - The counterintuitive shift from "do everything" to "go extremely narrow" at $1M07:34 - How to identify role model customers that create herd momentum11:16 - The dangerous TAM trap: why you DON'T need a billion-dollar market early on16:48 - When to stop narrowing and start widening your ICP at $3M+20:33 - The "premature scaling" mistake that kills momentum at $3M27:54 - Why the bowling pin strategy beats boiling the ocean from $3M to $10M32:01 - When "good chaos" signals it's time to implement real processes38:22 - The 5 critical metrics every revenue leader needs at $10M44:08 - How Box bet the entire company on enterprise at $20M (and won)50:52 - The 3 types of startup employees - and why nobody spans all three54:08 - Where to find entrepreneurial salespeople (hint: failed startups)1:01:08 - When to start "sprinkling in" process-oriented people vs entrepreneurs1:04:59 - The founder-to-sales-leader handoff: optimal timing and structure1:11:30 - Why agility beats everything else in startup revenue growth
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