1st10 Podcast

What happens when three PhD students accidentally build the infrastructure that every major AI lab depends on? OR What if the AI benchmarks everyone trusts are measuring the wrong thing entirely?On this episode of the *1st10 Podcast*, host Boris Epstein sits down with Anastasios Angelopoulos, co-founder and CEO of LMArena, to unpack LMArena went from a Berkeley side project built with free pizza and zero revenue to a $100M company with 42 employees and tens of millions of users in under two years.Tune in to hear them talk about:- How Academic AI benchmarks measure the wrong things and real-world user feedback is - fundamentally changing how models compete- Why $100M wasn't crazy for a "seed" round - especially when a company has already proven product-market fit- The diversification play in AI, or why dozens of winners will emerge, not just one dominant player- Why Personalized AI i.e., individual leaderboards that route you to the best model is the obvious next step.- The uncomfortable automation truth - Rote jobs WILL disappear, period.- What happens when academic rigor meets commercial speed. (HINT: An unfair advantage in AI evaluation!)Specifically, don't miss Anastasios' surprisingly pragmatic advice on what AI's acceleration means for jobs, companies, and individuals and why being early to the AI revolution means you still have 20 years to position yourself.Chapters00:00 Introductions and ice-breakers05:41 The Academic Path That Accidentally Led to AI's Center08:36 A Side Project That Refused to Stay Small12:04 When Academics Realize They Built a Company15:50 The Bradley-Terry Model: Turning Preferences Into Ranked Data19:22 Your Personal AI Leaderboard Is Coming23:48 "We're 20 Years Ahead of the Pack"26:17 Why a $100M Seed Round Was the Rational Move29:58 Who Makes Up LMArena? And Why?34:47 The LMArena Hiring Philosophy36:56 The Jobs AI Will Definitely Kill40:12 Surf the Wave or Get Pulled UnderQuotes:"We're at Berkeley we're eating pizza, free pizza, making no money but Sam Altman cares what we're doing!" - Anastasios Angelopoulos (10:49)"We're academics by nature. We don't care about aggrandizing or enriching ourselves." - Anastasios Angelopoulos (12:28)"Who cares how well it does on a Math Olympiad? I do mathematics in my work, and even I don't care about it!" - Anastasios Angelopoulos (14:36)"We're very, very early... There's trillions of dollars of economic value that are waiting to be created." - Anastasios Angelopoulos (23:59)"If you're somebody who's proofreading text for grammatical mistakes [...] yeah, you should expect that that job is not going to be there in, like, 20 years!" - Anastasios Angelopoulos (38:19)"The right thing to do is probably to lean in, to try to use the technology, become an expert in it, and be at the forefront of modernizing your field. Because if you do that, then you can be carried with the wave. The problem is if you don't surf the wave, you might get caught in the pullback!" - Anastasios Angelopoulos (40:29)Follow:Spotify: https://podcasters.spotify.com/pod/show/1st10podcast Amazon: https://music.amazon.com/podcasts/7e8ec9af-f38c-4cd9-8c68-1c1dd4516b 27/1st10-podcastApple: https://podcasts.apple.com/us/podcast/1st10-podcast/id1760411207 Podcast: https://www.1st10.com/podcast RSS: https://anchor.fm/s/f951319c/podcast/rss YouTube: https://www.youtube.com/@1st10podcast Links:Music by Roman Senyk from PixabayProducer: Shrikant Joshi

Sreerama Tripuramallu, a repeat founder with a tech pedigree from NVIDIA, dives into the complexities of tax management in the digital age. He contrasts the shortcomings of general AI in tax calculations—where accuracy is paramount—against the backdrop of a looming CPA shortage. Sree discusses his journey from NVIDIA to founding Mirage, and now, a new stealth project aimed at revolutionizing tax forecasting. He advocates for a user-centric approach, emphasizing the need for precise tools that can truly assist consumers in their financial planning.

What kind of founder decides to build a full radiology practice, an AI research lab, and a software company - all at once?On this episode of the 1st10 Podcast, Boris Epstein sits down with Rustin Rassoli, founder of Epsilon Labs to talk about why solving the U.S. radiology crisis requires breaking the rules of traditional healthcare tech. Rustin recounts his early entrepreneurial experiments, the lessons learned at Atomic VC, and the childhood experiences that exposed him to the failures and bottlenecks inside medical imaging. He details how Epsilon manages a daily throughput of 500+ patients, why existing AI models fail at medical imaging, and what it really takes to build a hybrid org where radiologists, ML researchers, and world-class engineers operate as one unit. Rustin’s unconventional path led him from drop-shipping at age 10, to cold-DMing his way into venture studios, to tackling one of healthcare's most critical problems. And he’s now betting that his integrated 3-in-1 approach might be the only viable path to solving a medical crisis accelerating toward disaster.Inside you’ll find answers to some fascinating questions, such as:Why a "normal" AI startup approach simply cannot solve one of healthcare's fastest-accelerating failures. How a childhood insight inside an imaging center quietly shaped a multi-layered startup strategy years later. What happens when engineers and radiologists attempt to collaborate without speaking the same language. Which single overlooked bottleneck has the potential to determine whether AI can meaningfully affect patient outcomes at scale. Why Rustin believes a tectonic shift is coming for AI startups - and why most won't survive it. Specifically, don’t miss the part where Rustin shares candid views on the current AI bubble. Spoiler alert, he isn’t very happy with Silicon Valley and its ‘throw-cash-at-everything’ VC culture!Chapters00:00 Introductions02:16 An Unexpected Origin Story05:18 Learning the Hard Way in Zero-to-One Land08:31 "Getting the First Job" Might Be the Wrong Goal12:15 The Radiology Crisis Is Impossible to Ignore17:14 What Happens When Demand Explodes and Supply Collapses20:41 Solving This Problem Requires Building a 3-in-123:07 The Strange Dance Between Radiologists and AI Engineers27:52 "Just Make the Model Better" Isn't How AI Works31:46 Medical AI Accuracy & Hidden Technical Battles35:56 Building a Team for an "Impossible" Mission38:47 A Brutal Reality of the AI Talent War41:53 Predictions for 2026 (HINT: The Bubble Must Burst!)Quotes:"I want my tombstone to say, 'This guy solved the radiology shortage and did some other kind of impactful things with medical imaging.'" (16:43) "I think engineers don't fully appreciate how nuanced radiology is and the fact that it's not binary. And a Radiologist A can be very kind of differently opinionated on something than Radiologist B." (28:08) "99% of what's being created today is not very valuable to the world." (39:25) Follow:Spotify: https://podcasters.spotify.com/pod/show/1st10podcast Amazon: https://music.amazon.com/podcasts/7e8ec9af-f38c-4cd9-8c68-1c1dd4516b 27/1st10-podcastApple: https://podcasts.apple.com/us/podcast/1st10-podcast/id1760411207 Podcast: https://www.1st10.com/podcast YouTube: https://www.youtube.com/@1st10podcast Links:Music by Roman Senyk from PixabayProducer: Shrikant Joshi

56% more job openings, 3x more applications, but 8 MORE days to fill roles! CEO of Gem.ai shares data that explains why most recruiting careers are about to hit a wall…In this eye-opening conversation, Boris Epstein sits down with Steven Bartel, CEO of Gem.ai, to explore the shocking transformation happening in recruiting right now. From North Korean actors infiltrating hiring processes to AI-generated deepfake interviews, the recruiting landscape has become a battlefield. Steve reveals how recruiters are drowning under 3x more applications while handling 56% more open roles, yet companies refuse to expand recruiting teams. Steve shares exclusive data on how AI is saving companies up to 90% of their application review time and how Gem is embedding AI deeply into recruiting workflows - from sourcing agents to fraud detection - to help recruiters work smarter, not just harder. Tune in to hear them talk about:The Application Apocalypse: Recruiters are experiencing a 3x increase in applications while handling 56% more open roles.The Fraud Arms Race: Fraud in hiring is escalating, with cases of North Korean actors, deepfake interviews, and AI-generated resumes.The Efficiency Revolution: AI is cutting application review time by up to 90% for leading companies.The Human-AI Partnership: Recruiters who embrace AI will outperform those who resist it; AI augments human judgment.The Data-Context Challenge: The future of recruiting AI is about having complete relationship histories and touchpoint data to enable hyper-personalized outreach.Specifically, don't miss Steve's bold prediction on how he expects AI to reshape recruiting over the next few years!Chapters00:00 Highlights from the episode03:45 When Your Interview Is With AI09:08 North Korea's Recruiting Infiltration12:06 The Deepfake Interview Dilemma19:13 Why Recruiters Are Burning Out23:18 Will AI Kill the Recruiting Industry?27:24 FAANG Engineers vs AI Natives - a Recap33:24 The Recruiter's New Role in an AI-First Future41:40 A Bold Prediction About What Comes Next46:29 Solving The Source of Truth ProblemQuotes:"Each recruiter, on average, is dealing with three times the inbound applicants across our customer base. And more than 20% of our customers are getting thousands of applicants for a single role." - Steve Bartel (02:18)"I think some of these folks are using deepfake videos, which are getting surprisingly sophisticated. I've heard this recommendation where companies are going as far as to say 'Hey, can you put your hand in front of your face?'" - Steve Bartel (12:25)"If you talk to most recruiters in the industry, they are working a lot harder than ever before." - Steve Bartel (25:34)"AI is not going to replace recruiters, but recruiters who embrace AI are going to replace the recruiters who don't." - Steve Bartel (43:50)"The hardest part of AI is no longer like the underlying algorithm. [...] The hard part about AI is what data does the AI have actually access to and what kind of context does it have access to..." - Steve Bartel (46:01)Follow:Spotify: https://podcasters.spotify.com/pod/show/1st10podcast Amazon: https://music.amazon.com/podcasts/7e8ec9af-f38c-4cd9-8c68-1c1dd4516b 27/1st10-podcastApple: https://podcasts.apple.com/us/podcast/1st10-podcast/id1760411207 Podcast: https://www.1st10.com/podcast RSS: https://anchor.fm/s/f951319c/podcast/rss YouTube: https://www.youtube.com/@1st10podcast Links:Gem: https://www.gem.comSteve Bartel on LinkedIn: https://www.linkedin.com/in/steve-bartel/Gem’s Benchmarks Report 2025: https://www.gem.com/resource/recruiting-benchmarksMusic by Roman Senyk from PixabayProducer: Shrikant Joshi

On this episode of the 1st10 Podcast, Boris Epstein, founder of 1st10 and former FAANG-level recruiter, reveals a shocking reality behind AI startup hiring practices and why the most talented engineers in tech might be getting left behind. Drawing from his decade of experience recruiting for top tech firms like Robinhood, Instacart, and Stripe, Boris explores why AI founders are wary of FAANG talent, what biases drive this perception, and how engineers can adapt to stay relevant. He contrasts grind culture with lifestyle gigs, zero-to-one building with scale, and passion projects with polished résumés. The episode is a wake-up call for FAANG engineers as well as a cautionary tale for startups dismissing valuable talent too quickly.Tune in to hear Boris explain:The Great Talent Paradox: AI startups systematically avoiding FAANG engineers seems to be creating a disconnect between supply and demand in the hiring market.The Hurdles of Work Culture: The 9-to-5 easy-going lifestyle preferred by FAANG engineers versus the 60-70 hour weeks demanded by AI startups is presenting a major hiring barrier.The HP-Internet Moment: Engineers face a stark choice: be part of the AI future or risk obsolescence if they don't adapt quickly.The Zero-to-One Test: Building something from scratch is the ultimate litmus test for AI startup hiring. Specifically, don't miss the part where Boris reveals how the bias shown by AI startups against FAANG talent could backfire and what FAANG engineers need to do, if (when?) that happens.Chapters00:00 Highlights From The Episode01:23 3 Deadly Biases05:18 A Grand Canyon-Sized Gap12:13 The Power of Passion Projects15:03 HP in 1994, FAANG in 2025?22:05 The Case for FAANG Talent28:21 How to Break Into AI33:27 Startups Don’t Wait, Why Should You?37:52 A Market on Collision Course43:31 Why Both Worlds Must Evolve46:33 Do You Want to Be Part of the Future?Quotes:"The reason [AI Startups] are working very hard is because AI is believed to be by these startups (to be) a completely transformational technology, completely transformational opportunity." - Boris Epstein (07:25)"Get off the FAANG bus, get into the AI startup bus!" - Boris Epstein (17:40)"If I had a dollar and I could only put it into one of the two startups, I’d probably bet on the FAANG startup." - Boris Epstein (23:32)"Your resume isn't showing anybody what you could do for them. Your resume is showing the world what you did in the past." - Boris Epstein (30:53)Spotify: https://podcasters.spotify.com/pod/show/1st10podcast Amazon: https://music.amazon.com/podcasts/7e8ec9af-f38c-4cd9-8c68-1c1dd4516b 27/1st10-podcastApple: https://podcasts.apple.com/us/podcast/1st10-podcast/id1760411207 Podcast: https://www.1st10.com/podcast RSS: https://anchor.fm/s/f951319c/podcast/rss YouTube: https://www.youtube.com/@1st10podcast Connect with usWebsite: www.1st10.comPodcast: www.1st10.com/podcast Twitter www.x.com/1st10engineersLinkedIn: www.linkedin.com/company/1st10/YouTube: www.youtube.com/@1st10podcast Links:FAANG companies (Facebook/Meta, Amazon, Apple, Netflix, Google) - https://en.wikipedia.org/wiki/Big_TechLangChain (open-source AI framework) - https://www.langchain.com/Music by Roman Senyk from PixabayProducer: Shrikant Joshi

Sara Ali, Senior Director of Corporate Development & Strategy at Yahoo, shares insights from over 12 years in M&A with giants like Google and Microsoft. She discusses the current AI M&A landscape, explaining how 'scarcity multiples' are driving talent acquisitions while traditional revenue measures fade. Sara reveals creative deal structures that bypass regulatory scrutiny and how acquired talent can earn vastly more than their traditionally-hired counterparts. Plus, her bold prediction that GPUs will become a valuable deal currency. This is a must-listen for anyone navigating the tech industry!

On this episode of the 1st10 Podcast, Boris Epstein sits down with Daniel Rock - economist, professor at Wharton, and co-founder of Workhelix - to decode the messy reality of AI's impact on jobs, productivity, and enterprise transformation. Daniel brings a unique perspective as both an academic economist studying digital technologies and an entrepreneur building AI solutions for enterprises. The conversation explores why AI adoption might take longer than tech enthusiasts expect, how companies can strategically deploy AI tools, and why the "entry-level jobs apocalypse" might not happen as predicted. Daniel also shares his insights on teaching in the AI era, the challenges of building an AI startup, and his measured predictions for the technology's future impact.Daniel is refreshingly clear-eyed about where we actually are and where we're likely going. Below are some of the standout lessons I took away from our conversation.An entry-level job-pocalypse? Well, no. AI could just as likely augment junior talent as replace it, and in some cases, even increase demand for skilled oversight.A job isn't a task. It's a bundle of interdependent skills, roles, and context - making full automation much harder than people think.Generative AI = the new Excel. Used poorly, it's lazy. Used well, it supercharges creativity, productivity, and learning - especially among students.An Educational Revolution Is Underway. AI is quietly transforming classroom dynamics and assessment criteria in ways that mirror future workplace changes.Real transformation takes time. Like electricity and the internet, AI as a general-purpose tech will only reshape enterprise when paired with new systems, workflows, and retraining.AI Has A Real Risk No One's Talking About. It’s not superintelligence - it's bad actors with superpowers. And it matters a lot more in the near term than you think.Chapters00:00 Key Ideas From the Episode05:32 Confessions of a Multi-Disciplinary Economist08:31 How Students Actually Use AI11:24 Redefining Originality in the GPT Era16:21 A Startup That's Betting Against the Wait-and-See Crowd19:30 Inside the Enterprise AI Mess24:22 Jobs Are Systems, Not Widgets28:12 Reviewers, Not Doers: The Software Engineering Shift32:00 Workhelix: Building in the Eye of the Storm38:42 Predictions from the Pragmatist45:26 Careers @ WorkhelixQuotes"I tend to make everyone a little bit upset when I talk about Artificial Intelligence." - Daniel Rock (02:28)"I'm a little skeptical that the entry-level jobs apocalypse is even going to happen. A job is not, like, an easy thing to just take out." - Daniel Rock (00:00)"My friends, Gene Kim and Steve Yegge, call that 'The Potential Closet of Eldritch Horrors.' I do not envy the talent wars that Meta and OpenAI and Anthropic have to fight in." - Daniel Rock (00:00)"You don't get an A if you're correct anymore! You have to be correct AND original! You'll get a B if you're correct." - Daniel Rock (11:56)"AI will pay off your credit card debt on the technical debt side. So if you start racking up a lot of technical debt, that can be okay because AI will wipe it out to some extent later on!" - Daniel Rock (35:06)Follow:Spotify: https://open.spotify.com/show/13UwWOSV1KrJBJgIdt8bJ7Amazon: https://music.amazon.com/podcasts/7e8ec9af-f38c-4cd9-8c68-1c1dd4516b 27/1st10-podcastApple: https://podcasts.apple.com/us/podcast/1st10-podcast/id1760411207 Podcast: https://www.1st10.com/podcast YouTube: https://www.youtube.com/@1st10podcast Links:Daniel Rock’s website: https://www.danielianrock.com Daniel Rock (Operations, Information and Decisions Department, Wharton School, UPenn): https://oid.wharton.upenn.edu/profile/rockdi/Daniel’s startup, Workhelix: https://www.workhelix.com/ Music by Roman Senyk from PixabayProducer: Shrikant Joshi

Mark Zuckerberg dropping $100 million each on SIXTEEN engineers (and counting) might be a wild strategy that could hand Meta the AI crown.On this episode of the 1st10 Podcast, host Boris Epstein dives into Meta's jaw-dropping AI talent acquisition spree that's sending shockwaves through Silicon Valley. From $100 million sign-on bonuses to billion-dollar offers, Meta is rewriting the rules of tech recruiting. From the $14B Scale AI buy to $100M+ offers for individual engineers, Boris unpacks the strategic genius - and controversy - behind Zuckerberg's pivot to building a "Superintelligence Lab." He explains why this isn't reckless spending but a calculated blend of corporate development and recruiting tactics, designed to leapfrog competition in the AI arms race. Along the way, he dissects the ripple effects across compensation norms, startup hiring, and the tech industry's status quo.Tune in to hear Boris explain how (and why):Meta isn't "just hiring" - it's merging a long-standing "corporate development" strategy with individual recruiting.Zuck's pivot pattern is clear. Mobile-first, Metaverse, and now AI - with "lockdown" focus and willingness to spend massively to catch up or lead.The hires weren't just motivated by massive paychecks. Mark Zuckerberg's compelling vision of "superintelligence for every human in the world" was a solid hook.Meta has forced an industry-wide compensation reset. Meta's strategy is forcing competitors like OpenAI and Anthropic to dramatically increase their own compensation packages to retain talent. Ripple effects will be seen beyond 'Big AI labs' - every competitor is now rethinking pay, retention, and how to raid rivals' best people.Discover why Meta is betting billions on superintelligence, how they're rewriting the rules of recruiting, and what this means for startups, engineers, and the future of AI.Chapters00:00 Key Ideas From The Episode01:19 Why Meta is Dropping $100M Like Pocket Change03:19 When Acquisitions Hit a Wall07:49 Zuck's Lockdown 2.0 Was Worth $14 Billion?13:20 The Math That Makes "Insane" Offers Make Sense17:04 The Hiring Model That Breaks ALL Industry Rules!21:10 Speed Was the Point, Not the Problem.26:53 What Kind of a Smart Guy Rejects a $1B Offer?!32:25 Will The Riches Trickle Down To... You?37:26 AI for Everyone - Or a Dystopian Nightmare?Quotes:"What Meta did in this case - which is, in my opinion, brilliant and landscape-changing - is they brought in individual people after their initial acquisition but for the same acquisition-level proceeds!" - Boris Epstein (16:44)"If Meta is willing to offer $100+ million, they’re equally allowed to ask for any timeline they want." - Boris Epstein (23:28)"I do believe that we'll see quite a meaningful trickle effect... Every single company CEO is taking notice. Every single company Corp Dev group, every single engineer, is taking notice." - Boris Epstein (32:25)Follow:Spotify: https://podcasters.spotify.com/pod/show/1st10podcast Amazon: https://music.amazon.com/podcasts/7e8ec9af-f38c-4cd9-8c68-1c1dd4516b 27/1st10-podcastApple: https://podcasts.apple.com/us/podcast/1st10-podcast/id1760411207 Podcast: https://www.1st10.com/podcast YouTube: https://www.youtube.com/@1st10podcast Connect with usWebsite: www.1st10.comPodcast: www.1st10.com/podcast Twitter www.x.com/1st10engineersLinkedIn: www.linkedin.com/company/1st10/YouTube: www.youtube.com/@1st10podcast Links:“Blink”, by Malcolm Gladwell - https://www.gladwell.com/blink/Open AI’s Head of Recruiting posts about Meta’s “exploding” offers: https://x.com/jquinonero/status/1940926946705395943The Developer Who Got A $1B+ Offer: https://www.business-standard.com/world-news/mark-zuckerberg-mira-murati-meta-thinking-machines-lab-andrew-tulloch-offer-125080601247_1.htmlMusic by Roman Senyk from PixabayProducer: Shrikant Joshi

What if the AI revolution doesn't take all jobs but *just* enough to crash society?On this first episode of the latest season of the 1st10 Podcast, host Boris Epstein is joined by ex-Microsoft, ex-Meta, and ex-OpenAI engineer and founder of the AI-powered podcast app Superphonic, Philip Su for a conversation about AI, jobs, and the future of humanity. Philip lays out why he's building small while the rest of the world races toward scale. He opens up about career pivots, the myth of vibecoding, and the sobering risks that even a 5% disruption from AI could cause. From building Facebook Video Calling to solo-coding his dream podcast app, this is a rare look at tech from someone who's seen every stage of the game but is now sounding the alarm…Tune in to hear them talk about a variety of topics, such as:*Career Pivots Require Self-Awareness: Philip's leap from Microsoft to Facebook (when it was still risky) underscores the importance of recognizing when your skills need reinvention.*Small Teams, Big Impact: With AI tools, a solo developer can now build what once required a team!*Shipping is the real grind: The hardest part of software? Not coding. It's the “business of software”—App Store approvals, signing certs, compliance, etc.Podcasts Are Ripe for Disruption: Superphonic's innovations (like topic-based subscriptions) reveal how overlooked niches can be goldmines for builders.AI is beating us at being human: It does art, music, and writing better than the average person!*The "Faster Faster" Problem: AI's self-improving nature means societal disruptions could happen at an accelerating pace.Specifically, don't miss the part where Philip explains how specialization won't necessarily save you from losing your job to AI but something else will. Listen to the episode to know what that might be!Chapters00:00 Introduction05:23 A Risky Leap: From Microsoft to Facebook13:47 Building a Podcast Player (in 2025!)19:36 Coding Now vs Then (Spoiler: It's Wild!)23:02 Can A Solo Dev Compete With The Big Guys?30:11 Vibe Coding - It's What You've Been Waiting For!32:46 Inside OpenAI: A Glimpse Behind the Curtain38:09 AI Is Not Like Social Media; It's MUCH Bigger!43:30 Why This Time Might Actually Be Different46:02 Winter is Coming -- For ALL White-Collar Workers!Quotes:"Most of software development is not the coding of Tetris. That is hardly the hard part of the problem." - Philip Su (30:11)"We used to think with the Jetsons that the robots would clean our houses while we did art and music and all this stuff. And it turns out that the robots first came for the art and the music, and we're still cleaning our own houses." - Philip Su (39:54)"Winter is coming. That is my warning." - Philip Su (49:03)Connect with usWebsite: www.1st10.comPodcast: www.1st10.com/podcast Twitter www.x.com/1st10engineersLinkedIn: www.linkedin.com/company/1st10/YouTube: www.youtube.com/@1st10podcast Links:Music by Roman Senyk from PixabayProducer: Shrikant Joshi

SummaryOn this final episode of Season 2 of the 1st10 Podcast, Boris Epstein and Alexis Munger outline a comprehensive Hiring Playbook for founders building early-stage startups. They list seven critical steps to attract and hire top talent, emphasizing the importance of storytelling, leveraging networks, and the founder's active role in recruiting. Through anecdotes, examples, and actionable advice, they explore how founders can craft compelling narratives, identify red flags, and sell their vision to potential hires.Some key takeaways from this episode:Storytelling is King: Without a compelling narrative, even the best opportunities can fall flat.  Founders Must Recruit: Founders need to be deeply involved in outreach, even if it means facing a high rejection rate.  Sell the Vision: Top candidates are drawn to the mission and the team, not just the salary.Go Beyond Technical Skills: Cultural fit, conflict resolution, and collaboration skills are just as important as technical abilities.  Specifically, don't miss the part where Boris and Alexis compare recruiting to getting married! That one will definitely unlock a whole new perspective about startup recruiting for sure!Chapters00:00 Introductions02:55 Hiring With Stories: Why Narrative Matters07:32 Hidden Networks: Talent You Already Know12:07 Founder's Grind: Don't Outsource Recruiting15:08 Filter for Fit: Know Your Deal-Breakers and Red Flags23:00 Beyond the Code: Interview for Culture and Conflict27:22 Sell the Dream: How to Win Over Top Talent35:44 Art of the Offer: Make It Personal39:25 Final Thoughts: What Really Moves the Needle?Quotes"I feel like some of the best hires I've ever made where I can see that that person stuck around the company a long time probably didn't look obvious on paper." - Alexis Munger (16:01)"If your story sucks but your deal-breakers are high, you're going to be doing a lot of evening-crying." - Boris Epstein (22:05)  "Founders and startups do a very poor job of infusing a sense of conflict and tension into the interview process." - Boris Epstein (23:49)  "Don't underestimate the emotional aspect of changing jobs and how that plays into a candidate's decision. It's not just money-based!" - Alexis Munger (30:35)  "At that point, you're basically asking the candidate to marry you!" - Boris Epstein (35:55)Follow UsSpotify: https://podcasters.spotify.com/pod/show/1st10podcast Amazon: https://music.amazon.com/podcasts/7e8ec9af-f38c-4cd9-8c68-1c1dd4516b 27/1st10-podcastApple: https://podcasts.apple.com/us/podcast/1st10-podcast/id1760411207 Podcast: https://www.1st10.com/podcast YouTube: https://www.youtube.com/@1st10podcast Website: www.1st10.comTwitter www.x.com/1st10engineersLinkedIn: www.linkedin.com/company/1st10/LinksMusic by Roman Senyk from PixabayProducer: Shrikant Joshi