Podcasts about Cursor

In this episode of Tank Talks, Matt Cohen sits down with Timothy Chen, the sole General Partner at Essence VC. Tim shares his remarkable journey from being a “nerdy, geeky kid” who hacked open-source projects to becoming one of the most respected early-stage infrastructure investors, backing breakout companies like Tabular (acquired by Databricks for $2.2 billion). A former engineer at Microsoft and VMware, co-founder of Hyperpilot (acquired by Cloudera), and now a solo GP who quietly raised over $41 million for his latest fund, Tim offers a unique, no-BS perspective on spotting technical founders, navigating the idea maze, and rethinking sales and traction in the world of AI and infrastructure.We dive deep into his unconventional path into VC, rejected by traditional Sand Hill Road firms, only to build a powerhouse reputation through sheer technical credibility and founder empathy. Tim reveals the patterns behind disruptive infra companies, why most VCs can't help with product-market fit, and how he leverages his engineering background to win competitive deals.Whether you're a founder building the next foundational layer or an investor trying to understand the infra and AI boom, this conversation is packed with hard-won insights.The Open Source Resume (00:03:44)* How contributing to Apache projects (Drill, Cloud Foundry) built his career when a CS degree couldn't.* The moment he realized open source was a path to industry influence, not just a hobby.* Why the open source model is more “vertical than horizontal”, allowing deep contribution without corporate red tape.From Engineer to Founder: The Hyperpilot Journey (00:13:24)* Leaving Docker to start Hyperpilot and raising seed funding from NEA and Bessemer.* The harsh reality of founder responsibility: “It's not about the effort hard, it's about all the other things that has to go right.”* Learning from being “way too early to market” and the acquisition by Cloudera.The Unlikely Path into Venture Capital (00:26:07)* Rejected by top-tier VC firms for a job, then prompted to start his own fund via AngelList.* Starting with a $1M “Tim Chen Angel Fund” focused solely on infrastructure.* How Bain Capital's small anchor investment gave him the initial credibility.Building a Brand Through Focus & Reputation (00:30:42)* Why focusing exclusively on infrastructure was his “best blessing” creating a standout identity in a sparse field.* The reputation flywheel: Founders praising his help led to introductions from top-tier GPs and LPs.* StepStone reaching out for a commitment before he even had fund documents ready.The Essence VC Investment Philosophy (00:44:34)* Pattern Recognition: What he learned from witnessing the early days of Confluent, Databricks, and Docker.* Seeking Disruptors, Not Incrementalists: Backing founders who have a “non-common belief” that leads to a 10x better product (e.g., Modal Labs, Cursor, Warp).* Rethinking Sales & Traction: Why revenue-first playbooks don't apply in early-stage infra; comfort comes from technical co-building and roadmap planning.* The “Superpower”: Using his engineering background to pressure-test technical assumptions and timelines with founders.The Future of Infra & AI (00:52:09)* Infrastructure as an “enabler” for new application paradigms (real-time video, multimodal apps).* The coming democratization of building complex systems (the “next Netflix” built by smaller teams).* The shift from generalist backend engineers to specialists, enabled by new stacks and AI.Solo GP Life & Staying Relevant (00:54:55)* Why being a solo GP doesn't mean being a lone wolf; 20-30% of his time is spent syncing with other investors to learn.* The importance of continuous learning and adaptation in a fast-moving tech landscape.* His toolkit: Using portfolio company Clerky (a CRM) to manage workflow.About Timothy ChenFounder and Sole General Partner, Essence VCTimothy Chen is the Sole General Partner at Essence VC, a fund focused on early-stage infrastructure, AI, and open-source innovation. A three-time founder with an exit, his journey from Microsoft engineer to sought-after investor is a masterclass in building credibility through technical depth and founder-centric support. He has backed companies like Tabular, Iteratively, and Warp, and his insights are shaped by hundreds of conversations at the bleeding edge of infrastructure.Connect with Timothy Chen on LinkedIn: linkedin.com/in/timchenVisit the Essence VC Website: https://www.essencevc.fund/Connect with Matt Cohen on LinkedIn: https://ca.linkedin.com/in/matt-cohen1Visit the Ripple Ventures website: https://www.rippleventures.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tanktalks.substack.com

In this episode of Run the Numbers, CJ sits down with Ken Stillwell, CFO and COO of Pegasystems, to explore the realities of leading from the second seat. Ken shares hard-earned lessons from guiding Pega through the shift from term licenses to ARR and ACV, including how to rework sales compensation without losing trust or momentum. They discuss the limits of KPI obsession, the importance of directional clarity over false precision, and why private equity often drives sharper execution than public markets—and how to apply that discipline while still playing the long game.—SPONSORS:Tabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/runAbacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.aiBrex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsMetronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comRightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.comRillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cj—LINKS:Ken on LinkedIn: https://www.linkedin.com/in/ken-stillwell-83a499a/Pegasystems: https://www.pega.com/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:How Finance Becomes a GTM Partner, Not a Bottleneck | Chris Brubakerhttps://youtu.be/T2YjdoiJtFA—TIMESTAMPS:00:00:00 Preview and Intro00:02:57 Sponsors — Tabs | Abacum | Brex00:07:26 The Strategic Value of Being Number Two00:08:46 Earnings Calls, Messaging, and Real-Time Judgment00:10:41 Using Feedback to Sharpen Executive Communication00:11:38 CFOs as Storytellers & Message Repetition00:12:31 Managing Up: Reading the Room00:13:59 Learning the Hard Way: Misreading Dynamics00:15:18 Confidence, Aggression, and Early CFO Mistakes00:15:58 Sponsors — Metronome | RightRev | Rillet00:19:45 When to Email vs Pick Up the Phone00:22:48 Tailoring Communication to Different Functions00:23:23 Audience-Specific Messaging: “Why Me?”00:25:24 Values vs Behaviors in Leadership00:28:13 Why Big Changes Need Anchoring00:31:14 Moving Pega to the Cloud00:32:43 Rewiring Sales Comp for ARR & ACV00:34:56 Sales Credibility Breakdowns with Customers00:36:20 Economics vs Trust in Sales Teams00:37:48 Balancing Field Feedback with Company Goals00:39:17 De-Emphasizing New Logos to Fix the Sales Model00:41:12 The Danger of Over-Obsessing on KPIs00:42:51 Public vs Private: Incentives and Operating Discipline00:45:57 Why Companies Go Private: Motivation Over Patience00:47:29 The Shrinking Public Markets00:47:57 Private vs Public CFO Mindsets00:49:39 Meeting Investors Where They Are00:50:16 A Risky Decision That Paid Off: Going All-In on the Cloud00:51:29 Long-Ass Lightning Round00:53:24 Ken's Finance Tech Stack & Craziest Expense00:54:39 Credits#RunTheNumbersPodcast #CFOLeadership #ExecutiveCommunication #SalesStrategy #PublicVsPrivate This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

From graduate engineer to CTO, Andrew Phillips' 16-year journey at Skyscanner is a story of continuous reinvention. He didn't chase titles—he chased growth, deliberately stepping out of his comfort zone and unlearning the habits that no longer served him. What's kept him at the company for over a decade isn't status, but challenge: new teams, unfamiliar problems, and the chance to stay close to the work, even as his scope of leadership expanded.In this episode, we explore how Andrew is now applying that same mindset to leading in the AI era—personally and professionally. He shares how he's built a personal AI stack to stay more present, how Skyscanner is blurring traditional team roles to unlock speed, and why “directed autonomy” is more important than ever. For leaders navigating scale, technology, and the desire to make meaningful impact without burning out, Andrew offers a powerful perspective.Key TakeawaysGrowth through discomfort: Andrew's biggest accelerations came from switching roles and leaving his comfort zone—not climbing a predefined ladder.AI as a leadership enabler: He uses AI tools to be more present, thoughtful, and effective—especially during high-stakes meetings.From feature factory to outcome focus: Leaders must reconnect people to impact, not just output.Directed autonomy: Empowering teams with AI means giving clear goals—not micromanaging the execution.Unlearning process overreach: Traditional roles, ticketing systems, and rigid handoffs are ripe for reinvention in AI-native organizations.Additional InsightsThe personal AI stack Andrew uses includes ChatGPT, Otter, Cursor, and SpecKit—enabling him to ideate on walks, build apps during board meetings, and maintain strategic presence.Skyscanner's senior engineers are back coding, using AI to close the gap between architectural thinking and execution.AI-driven productivity unlocks don't just mean faster work—they mean better work-life balance, deeper engagement, and more human leadership.Episode Highlights00:00 – Episode RecapAndrew Phillips shares how stepping into uncertainty—and building his own AI stack—transformed his leadership at Skyscanner. From personal growth to organizational reinvention, he's leading the charge on what modern technology leadership looks like.01:35 – Guest Introduction: Andrew PhillipsBarry introduces Andrew Phillips, CTO of Skyscanner, reflecting on their 15-year relationship and Andrew's rise from graduate engineer to technology leader.05:45 – The One Trick Pony MomentAndrew recalls the pivotal moment when a CEO challenged him to move teams and stop playing it safe—triggering his real leadership evolution.12:33 – Starting with Yourself in AIBefore transforming your company with AI, Andrew urges leaders to start by experimenting personally and learning from the ground up.15:15 – Writing Better Prompts, Building Better SpecsAI tools thrive on clear direction. Andrew realized that better prompting and crisp product requirements accelerated his results dramatically.20:01 – Directed Autonomy in the AI EraGiving AI tools (and people) the “why” rather than micromanaging the “how” builds trust, speed, and better outcomes.24:56 – Parallel Productivity and Boardroom AppsHow Andrew built an entire app—during a board meeting—by offloading work to AI and staying fully present in the room.27:13 – Reclaiming Work-Life BalanceAI allows Andrew to unload his mental backlog—using...

“I don't worry about being replaced by AI. I worry about being replaced by someone who's really good at using AI.”Atlassian has 10,000+ engineers currently split-testing the world's top AI coding tools, from GitHub Copilot and Cursor to Claude Code. In this episode, Co-Founder & CEO Mike Cannon-Brookes joins Lukas Biewald to share what their data reveals about the world's best AI tools today.Hear how 24 years of building a tech giant and a massive internal study on AI productivity have shaped Mike's vision for the future of dev jobs.Connect with us here:Mike Cannon-Brookes: https://www.linkedin.com/in/mcannonbrookes/?originalSubdomain=auAtlassian: https://www.linkedin.com/company/atlassian/?viewAsMember=trueLukas Biewald: https://www.linkedin.com/in/lbiewald/ Weights & Biases: https://www.linkedin.com/company/wandb/00:00 Trailer01:08 Introduction03:11 Connecting Technology and Business Teams07:22 The Impact of AI on Business Workflows13:26 Developer Productivity and AI21:03 Measuring Developer Efficiency25:41 Future of AI in Development34:59 Legacy Technology and Code Changes39:29 AI's Role in Developer Productivity47:40 AI and Junior Developers52:30 Product-Led Growth and Business Strategy01:00:29 Core Metrics for Sustainable Growth01:06:56 Staying Creative in the Tech Industry

In this episode of Run the Numbers, CJ sits down with Chris Brubaker, SVP of Finance at Postscript, who's helped build the finance function from the ground up. Chris shares how he partners with sales through deal desks, sets pricing guardrails, and makes sure finance helps close deals instead of slowing them down. They dig into his hands-on approach to automation using AI with limited engineering resources, how Postscript's metrics evolved as the company scaled, when to trust internal data over benchmarks, and where teams get tripped up. Plus, a private jet accounting story—because of course.—SPONSORS:Rillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cjTabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/runAbacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.aiBrex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsMetronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comRightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.com—LINKS:Chris on LinkedIn: https://www.linkedin.com/in/wchrisbrubaker/Postscript: https://postscript.io/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:So You're Looking for a “Strategic” CFO? Bloomerang's Steve Isom on What That Really Meanshttps://youtu.be/cgHOtvG1CesThe IPO Playbook: Expert Advice from Lee Kirkpatrick, Twilio's Former CFOhttps://youtu.be/PTKAUD7PSWUThe CFO Case for Probabilistic Forecasting With AI | Bruno Annicqhttps://youtu.be/Dl8nDZPJMpE—TIMESTAMPS:00:00:00 Preview and Intro00:02:22 Sponsors — Rillet | Tabs | Abacum00:06:55 Interview Begins00:07:36 First Finance Hire and Early Scale at Postscript00:09:02 Usage-Based Margins, COGS, and the Twilio Parallel00:10:31 Partnering With Sales and Building Deal Desk00:13:16 Pricing Guardrails, Payback, and Deal Economics00:15:35 How Deal Desk Evolves Over Time00:16:01 Sponsors — Brex | Metronome | RightRev00:19:44 Making Finance a Deal-Closing Partner00:20:44 Automating Deal Desk With a Slack Bot00:23:48 How Technical Finance Leaders Need to Be00:25:17 Automating Without Engineering Help00:27:12 Why Human Touch Still Matters in SaaS00:27:53 Postscript's Finance Tech Stack00:28:30 ERP Migration and Month-End Efficiency00:29:42 The Reality of Continuous Close00:30:34 First Real AI Wins in Accounting00:31:18 Experimenting With AI Forecasting00:33:32 Metrics That Matter: Usage as a Leading Indicator00:35:49 How Metrics Evolve as the Company Scales00:37:41 Understanding the Product in a Usage-Based Model00:39:27 Micro-Seasonality and Forecasting Volatility00:42:21 How to Use Benchmarks Without Misusing Them00:43:50 Long-Ass Lightning Round: A Costly Modeling Mistake00:45:45 Advice to a Younger Finance Leader00:47:05 The Private Jet Accounting Story00:49:11 Credits#RunTheNumbersPodcast #FinanceLeadership #DealDesk #UsageBasedSaaS #AIinFinance This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

Loïc Houssier (CTO, Superhuman) joins VC.fm to unpack the Grammarly acquisition of Superhuman and what it signals about the future of AI-native productivity tools.We talk AI in the workflow vs standalone AI tools (ChatGPT/Gemini), voice-first computing, vibe coding vs production engineering, AI's impact on hiring, and why UX taste and product design may be the real moat in an era where everyone has access to the same LLMs.Keywords: Grammarly acquires Superhuman, Superhuman email, Loïc Houssier, AI productivity, AI-native software, email AI, workflow AI, OpenAI, Anthropic, LLMs, vibe coding, Cursor, UX design moat, product-led growth, startup defensibility, AI hiring.Follow the PodcastInstagram: https://www.instagram.com/venturecapitalfm/Twitter: https://twitter.com/vcpodcastfmLinkedIn: https://www.linkedin.com/company/venturecapitalfm/Spotify: https://open.spotify.com/show/7BQimY8NJ6cr617lqtRr7N?si=ftylo2qHQiCgmT9dfloD_g&nd=1&dlsi=7b868f1b72094351Apple: https://podcasts.apple.com/us/podcast/venture-capital/id1575351789Website: https://www.venturecapital.fm/Follow Jon BradshawLinkedIn: https://www.linkedin.com/in/mrbradshaw/Instagram: https://www.instagram.com/mrjonbradshaw/Twitter: https://twitter.com/mrjonbradshawFollow Peter HarrisLinkedIn: https://www.linkedin.com/in/peterharris1Twitter: https://twitter.com/thevcstudentInstagram: https://instagram.com/shodanpeteYoutube: https://www.youtube.com/@peterharris2812#Superhuman #Grammarly #AI #Productivity #Startups #VentureCapital #Email #LLM #OpenAI #Anthropic #VibeCoding #UXDesign #ProductManagement #Engineering

Zevi Arnovitz is a product manager at Meta with no technical background who has figured out how to build and ship real products using AI. His engineering team at Meta asks him to teach them how he does what he does. In this episode, Zevi breaks down his complete AI workflow that allows non-technical people to build sophisticated products with Cursor.We discuss:1. The complete AI workflow that lets non-technical people build real products in Cursor2. How to use multiple AI models for different tasks (Claude for planning, Gemini for UI)3. Using slash commands to automate prompts4. Zevi's “peer review” technique, which uses different AI models to review each other's code5. Why this might be the best time to be a junior in tech, despite the challenging job market6. How Zevi used AI to prepare for his Meta PM interviews—Brought to you by:10Web—Vibe coding platform as an APIDX—The developer intelligence platform designed by leading researchersFramer—Build better websites faster—Episode transcript: https://www.lennysnewsletter.com/p/the-non-technical-pms-guide-to-building-with-cursor—Archive of all Lenny's Podcast transcripts:https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Zevi Arnovitz• X: https://x.com/ArnovitzZevi• LinkedIn: https://www.linkedin.com/in/zev-arnovitz• Website: https://zeviarnovitz.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Zevi Arnovitz(04:48) Zevi's background and journey into AI(07:41) Overview of Zevi's AI workflow(14:41) Screenshare: Exploring Zevi's workflow in detail(17:18) Building a feature live: StudyMate app(30:52) Executing the plan with Cursor(38:32) Using multiple AI models for code review(40:40) Personifying AI models(43:37) Peer review process(45:40) The importance of postmortems(51:05) Integrating AI in large companies(53:42) How AI has impacted the PM role(57:02) How to improve AI outputs(58:15) AI-assisted job interviews(01:02:57) Failure corner(01:06:20) Lightning round and final thoughts—Referenced:• Becoming a super IC: Lessons from 12 years as a PM individual contributor | Tal Raviv (Product Lead at Riverside): https://www.lennysnewsletter.com/p/the-super-ic-pm-tal-raviv• Wix: https://www.wix.com• Building AI Apps: From Idea to Viral in 30 Days: https://www.youtube.com/watch?v=j2w4y7pDi8w• Riley Brown on YouTube: https://www.youtube.com/channel/UCMcoud_ZW7cfxeIugBflSBw• Greg Isenberg on YouTube: https://www.youtube.com/@GregIsenberg• Bolt: https://bolt.new• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Lovable: https://lovable.dev• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• StudyMate: https://studymate.live• Dibur2text: https://dibur2text.app• Claude: https://claude.ai• Everyone should be using Claude Code more: https://www.lennysnewsletter.com/p/everyone-should-be-using-claude-code• Bun: https://bun.com• Zustand: https://zustand.docs.pmnd.rs/getting-started/introduction• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Wispr Flow: https://wisprflow.ai• Linear: https://linear.app• Linear's secret to building beloved B2B products | Nan Yu (Head of Product): https://www.lennysnewsletter.com/p/linears-secret-to-building-beloved-b2b-products-nan-yu• Cursor Composer: https://cursor.com/blog/composer• Replit: https://replit.com• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Base44: https://base44.com• Solo founder, $80M exit, 6 months: The Base44 bootstrapped startup success story | Maor Shlomo: https://www.lennysnewsletter.com/p/the-base44-bootstrapped-startup-success-story-maor-shlomo• v0: https://v0.app• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder & CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Cursor Browser mode: https://cursor.com/docs/agent/browser• Google Antigravity: https://antigravity.google• Grok: https://grok.com• Zapier: https://zapier.com• Airtable: https://www.airtable.com• Build Your Personal PM Productivity System & AI Copilot: https://maven.com/tal-raviv/product-manager-productivity-system• The definitive guide to mastering analytical thinking interviews: https://www.lennysnewsletter.com/p/the-definitive-guide-to-mastering-f81• AI tools are overdelivering: results from our large-scale AI productivity survey: https://www.lennysnewsletter.com/p/ai-tools-are-overdelivering-results-c08• Yaara Asaf on LinkedIn: https://www.linkedin.com/in/yaarasaf• The Pitt on Prime Video: https://www.amazon.com/The-Pitt-Season-1/dp/B0DNRR8QWD• Severance on AppleTV+: https://tv.apple.com/us/show/severance/umc.cmc.1srk2goyh2q2zdxcx605w8vtx• Loom: https://www.loom.com• Cap: https://cap.so• Supercut: https://supercut.ai...References continued at: https://www.lennysnewsletter.com/p/the-non-technical-pms-guide-to-building-with-cursor—Recommended books:• The Fountainhead: https://www.amazon.com/Fountainhead-Ayn-Rand/dp/0451191153• Shoe Dog: A Memoir by the Creator of Nike: https://www.amazon.com/Shoe-Dog-Memoir-Creator-Nike/dp/1501135910• Mindset: The New Psychology of Success: https://www.amazon.com/Mindset-Psychology-Carol-S-Dweck/dp/0345472322—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

From building internal AI labs to becoming CTO of Brex, James Reggio has helped lead one of the most disciplined AI transformations inside a real financial institution where compliance, auditability, and customer trust actually matter. We sat down with Reggio to unpack Brex's three-pillar AI strategy (corporate, operational, and product AI) [https://www.brex.com/journal/brex-ai-native-operations], how SOP-driven agents beat overengineered RL in ops, why Brex lets employees “build their own AI stack” instead of picking winners [https://www.conductorone.com/customers/brex/], and how a small, founder-heavy AI team is shipping production agents to 40,000+ companies. Reggio also goes deep on Brex's multi-agent “network” architecture, evals for multi-turn systems, agentic coding's second-order effects on codebase understanding, and why the future of finance software looks less like dashboards and more like executive assistants coordinating specialist agents behind the scenes. We discuss: Brex's three-pillar AI strategy: corporate AI for 10x employee workflows, operational AI for cost and compliance leverage, and product AI that lets customers justify Brex as part of their AI strategy to the board Why SOP-driven agents beat overengineered RL in finance ops, and how breaking work into auditable, repeatable steps unlocked faster automation in KYC, underwriting, fraud, and disputes Building an internal AI platform early: LLM gateways, prompt/version management, evals, cost observability, and why platform work quietly became the force multiplier behind everything else Multi-agent “networks” vs single-agent tools: why Brex's EA-style assistant coordinates specialist agents (policy, travel, reimbursements) through multi-turn conversations instead of one-shot tool calls The audit agent pattern: separating detection, judgment, and follow-up into different agents to reduce false negatives without overwhelming finance teams Centralized AI teams without resentment: how Brex avoided “AI envy” by tying work to business impact and letting anyone transfer in if they cared deeply enough Letting employees build their own AI stack: ChatGPT vs Claude vs Gemini, Cursor vs Windsurf, and why Brex refuses to pick winners in fast-moving tool races Measuring adoption without vanity metrics: why “% of code written by AI” is the wrong KPI and what second-order effects (slop, drift, code ownership) actually matter Evals in the real world: regression tests from ops QA, LLM-as-judge for multi-turn agents, and why integration-style evals break faster than you expect Teaching AI fluency at scale: the user → advocate → builder → native framework, ops-led training, spot bonuses, and avoiding fear-based adoption Re-interviewing the entire engineering org: using agentic coding interviews internally to force hands-on skill upgrades without formal performance scoring Headcount in the age of agents: why Brex grew the business without growing engineering, and why AI amplifies bad architecture as fast as good decisions The future of finance software: why dashboards fade, assistants take over, and agent-to-agent collaboration becomes the real UI — James Reggio X: https://x.com/jamesreggio LinkedIn: https://www.linkedin.com/in/jamesreggio/ Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction 00:01:24 From Mobile Engineer to CTO: The Founder's Path 00:03:00 Quitters Welcome: Building a Founder-Friendly Culture 00:05:13 The AI Team Structure: 10-Person Startup Within Brex 00:11:55 Building the Brex Agent Platform: Multi-Agent Networks 00:13:45 Tech Stack Decisions: TypeScript, Mastra, and MCP 00:24:32 Operational AI: Automating Underwriting, KYC, and Fraud 00:16:40 The Brex Assistant: Executive Assistant for Every Employee 00:40:26 Evaluation Strategy: From Simple SOPs to Multi-Turn Evals 00:37:11 Agentic Coding Adoption: Cursor, Windsurf, and the Engineering Interview 00:58:51 AI Fluency Levels: From User to Native 01:09:14 The Audit Agent Network: Finance Team Agents in Action 01:03:33 The Future of Engineering Headcount and AI Leverage

This is a recap of the top 10 posts on Hacker News on January 16, 2026. This podcast was generated by wondercraft.ai (00:30): Cloudflare acquires AstroOriginal post: https://news.ycombinator.com/item?id=46646645&utm_source=wondercraft_ai(01:56): STFUOriginal post: https://news.ycombinator.com/item?id=46649142&utm_source=wondercraft_ai(03:23): Just the BrowserOriginal post: https://news.ycombinator.com/item?id=46645615&utm_source=wondercraft_ai(04:49): Cursor's latest “browser experiment” implied success without evidenceOriginal post: https://news.ycombinator.com/item?id=46646777&utm_source=wondercraft_ai(06:16): Canada slashes 100% tariffs on Chinese EVs to 6%Original post: https://news.ycombinator.com/item?id=46648778&utm_source=wondercraft_ai(07:42): OpenBSD-current now runs as guest under Apple HypervisorOriginal post: https://news.ycombinator.com/item?id=46642560&utm_source=wondercraft_ai(09:09): East Germany balloon escapeOriginal post: https://news.ycombinator.com/item?id=46648916&utm_source=wondercraft_ai(10:35): 6-Day and IP Address Certificates Are Generally AvailableOriginal post: https://news.ycombinator.com/item?id=46647491&utm_source=wondercraft_ai(12:02): List of individual treesOriginal post: https://news.ycombinator.com/item?id=46641284&utm_source=wondercraft_ai(13:29): Michelangelo's first painting, created when he was 12 or 13Original post: https://news.ycombinator.com/item?id=46646263&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Sam Lessin is a partner at Slow Ventures, a former VP of Product at Facebook, and a two-time founder who's now teaching etiquette to Silicon Valley's founders. In this unconventional episode, Sam explains why proper etiquette has become a vital skill for founders in 2026—especially as technology becomes more central to society and trust becomes harder to build. His etiquette book and courses have become surprisingly popular, teaching founders how to “show up in a room with a low heart rate” and quickly build trust.We discuss:1. Why etiquette matters2. Sam's framework for showing up confidently, with a low heart rate, in any room3. How to navigate introductions, small talk, meetings, and meals like a pro4. Simple hacks for remembering names and handling awkward social situations5. 30+ specific etiquette tips—Brought to you by:10Web—Vibe-coding platform as an APIDX—The developer intelligence platform designed by leading researchersWorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs—Episode transcript: https://www.lennysnewsletter.com/p/silicon-valleys-missing-etiquette-playbook—Archive of all Lenny's Podcast transcripts:https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Sam Lessin:• X: https://x.com/lessin• LinkedIn: https://www.linkedin.com/in/wlessin• Website: https://www.wlessin.com• Podcast: https://moreorlesspod.com• Lettermeme: https://lettermeme.com/lessin—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Sam's background(04:18) The role of etiquette in business success(09:30) Introductions and entering a room(16:20) Engaging conversations and building relationships(23:55) Hygiene and dress code essentials(33:42) Dining etiquette(37:15) Tipping etiquette(41:36) The “B&D trick”(43:05) Humor in social settings(45:18) Self-deprecating humor(47:42) Winding down conversations(49:20) Scheduling etiquette(55:23) Communication and email etiquette(01:02:28) Meeting etiquette tips(01:04:03) Virtual meeting best practices(01:05:15) The importance of cleaning up after yourself(01:05:58) Exiting and follow-up etiquette(01:07:24) Final thoughts(01:09:20) AI corner(01:11:13) Contrarian corner(01:16:25) Lightning round—Referenced:• Y Combinator: https://www.ycombinator.com• Kleiner Perkins: https://www.kleinerperkins.com• “Lose Yourself” by Eminem on Spotify: https://open.spotify.com/track/7MJQ9Nfxzh8LPZ9e9u68Fq• Alison Gopnik on Childhood Learning, AI as a Cultural Technology, and Rethinking Nature vs. Nurture: https://conversationswithtyler.com/episodes/alison-gopnik• Garry Tan on LinkedIn: https://www.linkedin.com/in/garrytan• Bain & Company: https://www.bain.com• Evernote: https://evernote.com• Calendly: https://calendly.com• Morning Brew: https://www.morningbrew.com• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• DigitalOcean: https://www.digitalocean.com• Cloudflare: https://www.cloudflare.com• SpaceX: https://www.spacex.com• Marc Andreessen on X: https://x.com/pmarca• Landman on Prime Video: https://www.amazon.com/Landman-Season-1/dp/B0D4D8RTMD• Dave Morin on X: https://x.com/davemorin—Recommended books:• Modern Etiquette in Technology, Finance, Society, and at Home: A Slow Ventures Handbook: https://www.amazon.com/Modern-Etiquette-Technology-Finance-Society-ebook/dp/B0G4HSKSY5• Life, the Universe and Everything: https://www.amazon.com/Universe-Everything-Hitchhikers-Guide-Galaxy-ebook/dp/B001ODEQ7A• The Ancient City: A Study on the Religion, Laws, and Institutions of Greece and Rome: https://www.amazon.com/Ancient-City-Religion-Institutions-Greece/dp/0801823048• Man's Search for Meaning: https://www.amazon.com/Mans-Search-Meaning-Viktor-Frankl-ebook/dp/B009U9S6FI• Area 51: An Uncensored History of America's Top Secret Military Base: https://www.amazon.com/Area-51-Uncensored-Americas-Military-ebook/dp/B004THU68Q• The Lessons of History: https://www.amazon.com/Lessons-History-Will-Durant/dp/143914995X• The Fish That Ate the Whale: The Life and Times of America's Banana King: https://www.amazon.com/Fish-That-Ate-Whale-Americas/dp/1250033314• The Last Kings of Shanghai: The Rival Jewish Dynasties That Helped Create Modern China: https://www.amazon.com/Last-Kings-Shanghai-Jewish-Dynasties/dp/0735224439—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

AGENDA: 05:02 Anthropic's $10 Billion Fundraise 07:54 Has Claude Code Beaten Cursor Already 15:54 OpenAI Could Still Go to Zero 26:33 Andreessen Horowitz's $15 Billion Fundraise 45:16 The Middle is Dead: Boutique vs. Large Platforms in Venture 50:01 The Future of Venture Capital 01:08:06 The Impact of Wealth Taxes on the Industry      

In this episode of Run the Numbers, CJ sits down with Bruno Annicq, CFO of Wellhub (formerly Gympass), to unpack a practical finance playbook built around cash discipline, sustainable growth, and simplicity. Bruno explains how he rebuilt forecasting using an AI-driven, probabilistic ensemble model, moving teams beyond single-scenario planning. They also dig into his EMPOWER planning framework, usable OKRs, and why tighter alignment between finance, HR, and wellbeing is becoming a durable lever for long-term performance.—SPONSORS:RightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.comRillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cjTabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/runAbacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.aiBrex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsMetronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.com—LINKS:Bruno on LinkedIn: https://www.linkedin.com/in/bannicq/Wellhub: https://wellhub.com/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:“Run Toward a Tough Market” — Developing the Hard and Soft Skills To Be a Great Finance Leaderhttps://youtu.be/iNHbkcG7YEo—TIMESTAMPS:00:00:00 Preview and Intro00:02:19 Sponsors — RightRev, Rillet, Tabs00:06:43 Accidental CFO Origin Story00:07:34 Consulting to Operations Pivot00:08:12 Why Finance Clicked for Bruno00:09:28 McKinsey Prioritization in Real World00:10:02 Eisenhower Matrix and Prioritization00:11:08 Investing in Non-Urgent Work00:13:30 Lessons From AOL Reinvention00:16:10 Sponsors — Abacum, Brex, Metronome00:20:01 Career Growth Through Hard Problems00:20:52 Broadening Skills Through Change00:23:12 Five Core Finance Principles00:24:02 Cash Is King00:25:14 Driving Sustainable Growth00:26:01 No Surprises and Forecasting00:26:07 Finance as Business Enabler00:27:22 Less Is More Philosophy00:28:47 Hardest Principle: Less Is More00:29:46 Deterministic vs Probabilistic Forecasting00:31:11 Marketplace Volatility and Forecast Error00:32:10 Ensemble Models Explained00:33:37 Forecast Accuracy Gains00:34:53 Building Models In-House00:36:46 Why Explainability Matters00:37:48 Empower Framework Introduction00:47:47 Urgency, Compounding, Long-Term Thinking00:48:10 Advice to Younger Self00:50:06 Finance Stack and Expense Stories00:52:51 Credits#RunTheNumbersPodcast #CFO #FinanceLeadership #Forecasting #AIinFinance This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

Amir (Co-Founder at Humblytics) shares how he builds an “AI-native” company by focusing less on shiny tools and more on change management: assessing AI fluency across roles, setting the right success metrics, and creating shared context so AI can reliably ship work. The big theme is convergence—engineering, product, and design are collapsing into tighter loops thanks to tools like Cursor, MCP connectors, and Figma Make. Amir demos workflows like: AI-generated context files + auto-updated documentation, scraping customer domains to infer ICPs, turning screenshots into layered Figma designs, then converting Figma to working React code in minutes, and even running an “AI co-founder” Slack bot that files Linear tickets and can hand work to agents.Timestamps0:00 Introduction0:06 Amir's stance: “no AI experts” — it's constant learning in a fast-changing field.1:59 Cursor as the unlock: not just coding, but PM/strategy/design work via MCPs.4:17 The real problem: AI adoption is mostly change management + fluency assessment.5:18 The AI fluency rubric (helper → automator → augmentor → agentic) and why it matters.8:13 Cursor analytics: measuring AI-generated code and usage across the team.9:24 “New code is ~99% AI-generated” + how they keep quality via tight review + incremental changes.10:58 Docs workflow: GitBook connected to repo → AI edits docs and pushes live fast.14:02 ICP building: export Stripe customers → scrape domains with Firecrawl → cluster personas.17:45 Hallucination in the wild: AI misclassifies a company; human correction loop matters.34:43 Wild move: they often design in code and use an AI-generated style guide to stay consistent.38:10 Best demo: screenshot → Figma Make → layered design → Figma MCP → React code in minutes.45:29 “AI co-founder” Slack bot (Pixel): turns a bug report into a Linear ticket and can hand off to agents.48:46 Amir's wish list: we “solved dev”; now we need Cursor for marketing/sales → path to $1M ARR.Tools & technologies mentionedCursor — AI-first IDE used for coding and product/design/strategy workflows; includes team analytics.MCP (Model Context Protocol) — “connector” layer (Anthropic-origin) that lets LLMs interface with external tools/services.ChatGPT — used as a common baseline tool; discussed in the context of prompting practices and workflows.Microsoft Copilot — referenced via the law firm incentive story; used as an example of “usage metrics” gone wrong.Anthropic (AI fluency framework) — inspiration source for the helper/automator/augmentor/agentic rubric.GitBook — documentation platform connected to the repo so docs can be updated and published quickly.Firecrawl (MCP) — agentic web scraper used to analyze customer domains and infer ICP/personas.Stripe — source of customer export data (domains) to build ICP clustering.Figma — design collaboration tool; used here with Make + MCP to move from design → code.Figma Make — feature to recreate UI from an image/screenshot into editable, layered designs.Figma MCP — connector that allows Cursor/LLMs to pull Figma components/designs and generate code.React — front-end framework used in the demo for generating functional UI components.Supabase — mentioned as part of a sample stack when generating a PRD.React Router — mentioned as part of the sample stack in PRD generation.Slack — where Amir runs internal agents (including the “AI co-founder” bot).Linear — project management tool used for creating tickets from Slack/agent workflows.CI/CD — their deployment/review pipeline; emphasized as the human accountability layer.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

Greg Foster, Co-founder and CTO of Graphite (recently acquired by Cursor), joins the podcast to discuss the massive shift occurring in software engineering: the move from maximizing "Inner Loop" speed (writing code) to solving "Outer Loop" bottlenecks (reviewing, testing, merging). With AI generating code faster than humans can review it, the traditional Pull Request model is under pressure. Greg explains how "Stacked PRs" and agentic review workflows are essential for high-performing teams, and why he believes the role of the software engineer is evolving into an "architect of agents." We also cover the strategic rationale behind the Graphite/Cursor merger, the controversial "PRs per engineer" metric, and why he predicts that by 2029, manual code writing will be near zero—but demand for engineers will be higher than ever.

ProductLed 100 - The Solo-Founder Playbook: How to Run a $1M ARR SaaS with 1 person Most founders believe scaling requires a massive headcount, co-founders, and VC funding. They think success is measured by the size of the team, not the efficiency of the revenue. In this episode of the ProductLed 100 series, Wes Bush sits down with Vincent Jong (Founder of Poolside Ventures) and Esben Friis-Jensen (Co-Founder of Userflow) to discuss the emerging era of the "One-Person Company" - businesses designed to generate millions in revenue with just a single operator. Vincent reveals his strategy for building a portfolio of lean, highly profitable SaaS companies like MeetBot. Together with Esben, they break down how AI tools like Lovable and Cursor have removed the technical barrier to entry, why "speed" is the new competitive moat against incumbents like Calendly, and the exact skill sets required to thrive as a solo builder. Whether you are a developer looking to launch your own venture or a founder trying to maximize efficiency, this episode offers a blueprint for building high-revenue, low-headcount businesses that are built to last forever. Key Highlights: 01:36: Why Vincent stopped looking for co-founders and started building alone03:09: The AI Tech Stack: How tools like Lovable and Cursor replace engineering teams06:07: Why building the product is the easy part (and selling is the hard part)13:17: Disrupting a Red Ocean: Why MeetBot entered the crowded scheduling market16:53: The Economics of Infinite Runway: Operating a SaaS for a few hundred dollars a month20:31: Speed vs. Scale: How one-person teams outmaneuver incumbents27:21: The "Launch Early" myth vs. the new bar for MVP quality37:44: Vincent's advice: Don't quit your job. Build on weekends Resources:

In this episode of Run the Numbers, CJ sits down with Jason Kong, General Partner at Base10 Ventures, to unpack the firm's focus on “automation for the real economy” — software built for industries most tech investors overlook, but the world depends on. Jason breaks down what makes Series B investing uniquely hard, how he evaluates back-office and vertical SaaS opportunities, and where markets tip from niche to overcrowded. They also discuss Base10's decision to donate 50% of profits to fund scholarships, plus a lightning round spanning fantasy football, shorting SaaS in 2022, and a venture take that might spark debate.—SPONSORS:Metronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comRightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.comRillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cjTabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/runAbacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.aiBrex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metrics—LINKS:Jason on LinkedIn: https://www.linkedin.com/in/jasonykong/Base10 Partners: https://base10.vc/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:Scaling to $1B+ Revenue: From ServiceNow to Samsara | Dominic Phillipshttps://youtu.be/vBY6WZBMljw—TIMESTAMPS:00:00:00 Preview and Intro00:02:20 Sponsors — Metronome, RightRev, Rillet00:06:02 Base10 Background00:06:41 Automation for the Real Economy00:09:27 Vertical vs. Horizontal Software00:10:38 Cash Flow and Durability00:11:19 Product-Market Fit and ROI00:12:56 Growth Limits Selling to Tech00:13:19 The Size of the Real Economy00:14:16 Sponsors — Tabs, Abacum, Brex00:18:50 Base10's Giving Model00:20:30 Access, Education, and Tech00:21:53 Purpose and Founder Alignment00:22:51 Radical Transparency00:23:56 Portfolio Focus and Strategy00:24:05 Investing Ahead of Consensus00:26:29 ERP Adjacency as Alpha00:28:58 Lessons From Hedge Funds00:32:29 Public Markets Reality00:34:05 Public vs. Private Investing00:34:48 The Series B Sweet Spot00:36:49 A Bifurcated Series B Market00:38:56 Fast Series Bs and 2021 Vibes00:42:16 What Series B Looks Like Now00:44:36 Back Office Automation00:46:02 ERP-Centric Workflows00:48:33 Long-Ass Lightning Round00:49:36 Shorting SaaS in 202200:50:16 Fantasy Football and Investing00:52:57 Career Advice That Surprises00:55:03 A Contrarian Venture Take00:56:22 Credits#RunTheNumbersPodcast #SeriesB #RealEconomy #VerticalSaaS #BackOfficeAutomation This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

In this episode of Run the Numbers, CJ sits down with Dominic Phillips, CFO of Samsara, to unpack what it takes to scale a capital-intensive SaaS business from startup to public company in under a decade. Dominic reflects on his six-plus years at Samsara through hypergrowth, COVID disruption, supply chain constraints, a down-round survival raise, and an IPO at the very end of the 2021 tech window. Drawing on his earlier career at ServiceNow under Mike Scarpelli, he shares how experience across FP&A, IR, corp dev, and treasury shaped his approach to capital allocation, investor education, and analyst management. The conversation dives into asset-based pricing, selling into non-discretionary operations budgets, balancing hardware and software economics, and building credibility with a broad analyst base while scaling past $1B in ARR.—SPONSORS:Brex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsMetronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comRightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.comRillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cjTabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/runAbacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.ai—LINKS:Dominic on LinkedIn: https://www.linkedin.com/in/dominicphillips/Company: https://www.samsara.com/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:“Steal Your Boss's Job”: Calendly CFO John McCauley on Leadership, Ownership & Growthhttps://youtu.be/VRpTNDIfzPYFrom SMB to Enterprise: The CFO Scaling Playbook With Andrew Casey | Mostly Classicshttps://youtu.be/kMuJ6gAuEpgDriving revenue without selling | Greg Henry of 1Passwordhttps://youtu.be/f5FsNoG8A3E—TIMESTAMPS:00:00:00 Preview & Intro00:02:40 Sponsors — Brex | Metronome | RightRev00:06:18 Interview Begins00:06:46 Dominic's Early Career00:08:47 From ServiceNow to CFO00:09:47 Joining Samsara00:10:54 COVID, Burn, and a Down Round00:12:40 IPO Messaging and Investor Education00:15:50 Sponsors — Rillet | Tabs | Abacum00:20:27 Hardware + Software Story00:21:29 What Samsara Does00:22:30 Data, AI, and ROI00:23:23 Horizontal Platform and Verticals00:24:27 Growth Drivers at Scale00:26:09 Selling Into Operations00:28:19 Change Management in Legacy Orgs00:29:46 Non-Discretionary Budgets00:33:02 Storytelling Lessons from Scarpelli00:36:14 Managing Analysts00:39:23 Earnings Timing Strategy00:41:06 Metrics and Investor Trust00:42:38 Investor Communication Channels00:44:22 Investor Days and Long-Term Vision00:45:37 Annual Planning Maturity00:48:24 Forecast Accuracy and Cadence00:49:28 The 1000-Day Strategy00:50:40 Top-Line and Margin Targets00:51:59 Capital Allocation by Function00:54:46 Becoming a CFO00:58:21 Lightning Round and a CFO Mistake01:02:41 End Credits#RunTheNumbersPodcast #CFO #ScalingCompanies #B2BSaaS #PublicMarkets This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

In this episode, we separate the AI hype from the reality of the 2025 job market and look at why the "AGI" promises of tech founders haven't yet materialized. From "AI washing" in corporate layoffs to critical privacy alerts for Gmail users, here is what you need to know:The "AI Washing" Trend: Ryan explores why companies are using AI as an excuse for layoffs, arguing that replacing human customer service and coders with AI is often a move for headlines rather than actual efficiency.The Innovation Plateau: We discuss whether AI development has hit a wall; while early progress was lightning-fast, current updates feel like minor adjustments rather than revolutionary leaps.Coding vs. Vibe Coding: While tools like Claude Code are making development easier for non-coders, the CEO of Cursor warns that "vibe coding" can lead to shaky foundations and crumbling infrastructure without human oversight.Privacy Red Alert: A crucial breakdown on why Google has automatically opted Gmail users into AI training and the specific steps you must take to opt-out and protect your private data.AI Failures & Market Shifts: From a lawyer losing his career over fake AI citations to ChatGPT's recent 22% traffic drop following the Gemini 3 launch, we look at the growing skepticism surrounding LLM reliability.Claude coding - https://x.com/emollick/status/2008253907701821650@emollick

Our 230th episode with a summary and discussion of last week's big AI news!Recorded on 01/02/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:Nvidia's acquisition of AI chip startup Groq for $20 billion highlights a strategic move for enhanced inference technology in GPUs.New York's RAISE Act legislation aims to regulate AI safety, marking the second major AI safety bill in the US.The launch of GLM 4.7 by Zhipu AI marks a significant advancement in open-source AI models for coding.Evaluation of long-horizon AI agents raises concerns about the rising costs and efficiency of AI in performing extended tasks.Timestamps:(00:00:10) Intro / Banter(00:01:58) 2025 RetrospectiveTools & Apps(00:24:39) OpenAI bets big on audio as Silicon Valley declares war on screens | TechCrunchApplications & Business(00:26:39) Nvidia buying AI chip startup Groq for about $20 billion, biggest deal(00:34:28) Exclusive | Meta Buys AI Startup Manus, Adding Millions of Paying Users - WSJ(00:38:05) Cursor continues acquisition spree with Graphite deal | TechCrunch(00:39:15) Micron Hikes CapEx to $20B with 2026 HBM Supply Fully Booked; HBM4 Ramps 2Q26(00:42:06) Chinese fabs are reportedly upgrading older ASML DUV lithography chipmaking machines — secondary channels and independent engineers used to soup up Twinscan NXT seriesProjects & Open Source(00:47:52) Z.AI launches GLM-4.7, new SOTA open-source model for coding(00:50:11) Evaluating AI's ability to perform scientific research tasksResearch & Advancements(00:54:32) Large Causal Models from Large Language Models(00:57:33) Universally Converging Representations of Matter Across Scientific Foundation Models(01:02:11) META-RL INDUCES EXPLORATION IN LANGUAGE AGENTS(01:07:16) Are the Costs of AI Agents Also Rising Exponentially?(01:11:17) METR eval for Opus 4.5(01:16:19) How to game the METR plotPolicy & Safety(01:17:24) New York governor Kathy Hochul signs RAISE Act to regulate AI safety | TechCrunch(01:20:40) Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers(01:26:46) Monitoring Monitorability(01:32:07) Sam Altman is hiring someone to worry about the dangers of AI | The Verge(01:33:38) X users asking Grok to put this girl in bikini, Grok is happy obliging - India TodaySee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

It's been a travel-heavy hiatus—Mark's been living in Spain and Shashank's been bouncing across Asia (including a month in China)—but they're back to unpack a packed week of AI news. They start with the headline hardware story: the Groq (GROQ) deal/partnership dynamics and why ultra-fast inference is becoming the next battleground, plus how this could reshape access to cutting-edge serving across the ecosystem. From there, they pivot to NVIDIA's CES announcements and what “Vera Rubin” implies for data center upgrades, cost-per-token curves, and the messy real-world math of rolling hardware generations. Shashank then brings the future to life with on-the-ground stories from China: a Huawei “everything store” that feels like an Apple Store meets a luxury dealership, folding devices that look straight out of sci-fi, and a parade of robots—from coffee bots to delivery robots that can ride elevators and deliver to your hotel room. They also touch on companion-style consumer robots and why “cute” might be a serious product strategy. Finally, Mark announces the launch of Novacut, a long-form AI video editor built to turn hours of travel footage into a coherent vlog draft—plus export workflows for Premiere, DaVinci Resolve, and Final Cut. They close by talking about the 2026 shift from single model calls to “agentic” systems, including a fun (and slightly alarming) lesson from LLM outcome bias using poker hand reviews. Topics include: Groq inference, NVIDIA + CES, Vera Rubin GPUs, GPU depreciation math, China robotics, Huawei ecosystem, hotel delivery bots, companion robots, Novacut launch, Cursor vs agent workflows, and why agents still struggle with sparse feedback loops. Link mentioned: Novacut — https://novacut.ai

In this episode of Run the Numbers, CJ Gustafson sits down with Gordon Coyle, a 40-year commercial insurance veteran, to demystify one of the most anxiety-inducing topics for founders and CFOs: business insurance. Drawing on decades of experience with startups, scaleups, and regulated industries, Gordon breaks down what leaders need to know about D&O, E&O, cyber, and general liability, why investor pressure is rising, and where “cheap and easy” online policies fail when real risk hits. Through real-world examples, they explore how claims arise, how defense costs erode limits, why cyber insurance is as much about response as reimbursement, and how to balance budget, risk tolerance, and peer benchmarks—treating insurance as a critical layer of protection, not a box-checking exercise.—SPONSORS:Abacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.aiBrex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsMetronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comRightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.comRillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cjTabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/run—LINKS:Gordon on LinkedIn: https://www.linkedin.com/in/gordoncoyle/The Coyle Group: https://thecoylegroup.com/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:The Coyle Group - Business Insurancehttps://www.youtube.com/@TheCoyleGroupNY—TIMESTAMPS:00:00:00 Preview and Intro00:01:53 Sponsors — Abacum | Brex | Metronome00:05:39 Interview Begins with Gordon Coyle00:06:23 Gordon Coyle & The Coyle Group00:07:21 Explaining Insurance on YouTube00:08:40 Turning Education into Inbound Leads00:09:40 Content as a Pull Strategy00:10:53 Insurance Complexity for Tech Founders00:13:28 Why Investors Require D&O Insurance00:14:09 What D&O Covers and Why It Matters00:15:50 Sponsors — RightRev | Rillet | Tabs00:20:19 Who D&O Covers and Rising Investor Pressure00:22:37 D&O Limits and Cost Tradeoffs00:23:21 Panic Calls and Late D&O Purchases00:24:39 How Defense Costs Erode Coverage00:25:31 Common D&O Claims and Employment Risk00:27:08 D&O vs E&O Explained00:29:12 Cyber Insurance and Social Engineering00:31:59 AI's Impact on Cyber Risk00:33:50 Real-World Ransomware Stories00:34:17 Cyber Insurance as Money and Response00:35:29 Business Email Compromise Scams00:39:43 Why Tech Still Needs General Liability00:41:16 What a BOP Covers00:42:32 Convenience vs Proper Coverage00:44:29 Surprising General Liability Claims00:46:45 Insurance Costs for Startups00:47:36 Higher Costs in High-Risk Industries00:48:26 Balancing Budget, Risk, and Coverage00:50:39 PEOs, Workers' Comp, and EPLI00:54:39 Choosing the Right Insurance Partner00:56:42 End Credits#RunTheNumbersPodcast #StartupFinance #BusinessInsurance #RiskManagement #CyberRisk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

SaaStr 835: AI + B2B in 2026: Find the Tailwinds or Get Left Behind with SaaStr CEO and Founder Jason Lemkin Software spend is set to hit record levels in 2026, but you're not getting any of it unless you change. SaaStr CEO and Founder Jason Lemkin breaks down the paradox facing B2B companies right now: It's never been easier to scale to $100M (for a select few), while everyone else struggles. Half of all VC dollars are going into just 4 deals. IPOs ended the year with a whimper. And that AI copilot you built? It doesn't count. In this session, Jason shares the data on what's actually happening and what you need to do to capture your share of the hundreds of billions flowing into software. Key insights: Why "seed is for suckers" in today's VC environment The 3 types of AI products that unlock budget (and the one that doesn't) Why 30% of new IT budget is going to AI and how to steal it The TAM expansion math behind Cursor, Gamma, and AI SDR tools Why copilots and AI features alone won't save you The efficiency metrics every founder needs to track in 2026 If you didn't reaccelerate growth in 2025, you get a D. You can't get a D in 2026.

Jason Lemkin is the founder of SaaStr, the world's largest community for software founders, and a veteran SaaS investor who has deployed over $200 million into B2B startups. After his last salesperson quit, Jason made a radical decision: replace his entire go-to-market team with AI agents. What started as an experiment has transformed into a new operating model, where 20 AI agents managed by just 1.2 humans now do the work previously handled by a team of 10 SDRs and AEs. In this conversation, Jason shares his hands-on experience implementing AI to run his sales org, including what works, what doesn't, and how the GTM landscape is quickly being transformed.We discuss:1. How AI is fundamentally changing the sales function2. Why most SDRs and BDRs will be “extinct” within a year3. What Jason is observing across his portfolio about AI adoption in GTM4. How to become “hyper-employable” in the age of AI5. The specific AI tools and tactics he's using that have been working best6. Practical frameworks for integrating AI into your sales motion without losing what works7. Jason's 2026 predictions on where SaaS and GTM are heading next—Brought to you by:DX—The developer intelligence platform designed by leading researchersVercel—Your collaborative AI assistant to design, iterate, and scale full-stack applications for the webDatadog—Now home to Eppo, the leading experimentation and feature flagging platform—Transcript: https://www.lennysnewsletter.com/p/we-replaced-our-sales-team-with-20-ai-agents—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/182902716/my-biggest-takeaways-from-this-conversation—Where to find Jason Lemkin:• X: https://x.com/jasonlk• LinkedIn: https://www.linkedin.com/in/jasonmlemkin• Website: https://www.saastr.com• Substack: https://substack.com/@cloud—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Jason Lemkin(04:36) What SaaStr does(07:13) AI's impact on sales teams(10:11) How SaaStr's AI agents work and their performance(14:18) How go-to-market is changing in the AI era(19:19) The future of SDRs, BDRs, and AEs in sales(22:03) Why leadership roles are safe(23:43) How to be in the 20% who thrive in the AI sales future(28:40) Why you shouldn't build your own AI tools(30:10) Specific AI agents and their applications(36:40) Challenges and learnings in AI deployment(42:11) Making AI-generated emails good (not just acceptable)(47:31) When humans still beat AI in sales(52:39) An overview of SaaStr's org(53:50) The role of human oversight in AI operations(58:37) Advice for salespeople and founders in the AI era(01:05:40) Forward-deployed engineers(01:08:08) What's changing and what's staying the same in sales(01:16:21) Why AI is creating more work, not less(01:19:32) Why Jason says these are magical times(01:25:25) The "incognito mode test" for finding AI opportunities(01:27:19) The impact of AI on jobs(01:30:18) Lightning round and final thoughts—Referenced:• Building a world-class sales org | Jason Lemkin (SaaStr): https://www.lennysnewsletter.com/p/building-a-world-class-sales-org• SaaStr Annual: https://www.saastrannual.com• Delphi: https://www.delphi.ai/saastr/talk• Amelia Lerutte on LinkedIn: https://www.linkedin.com/in/amelialerutte/• Vercel: https://vercel.com• What world-class GTM looks like in 2026 | Jeanne DeWitt Grosser (Vercel, Stripe, Google): https://www.lennysnewsletter.com/p/what-the-best-gtm-teams-do-differently• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Replit: https://replit.com• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• ElevenLabs: https://elevenlabs.io• The exact AI playbook (using MCPs, custom GPTs, Granola) that saved ElevenLabs $100k+ and helps them ship daily | Luke Harries (Head of Growth): https://www.lennysnewsletter.com/p/the-ai-marketing-stack• Bolt: https://bolt.new• Lovable: https://lovable.dev• Harvey: https://www.harvey.ai• Samsara: https://www.samsara.com/products/platform/ai-samsara-intelligence• UiPath: https://www.uipath.com• Denise Dresser on LinkedIn: https://www.linkedin.com/in/denisedresser• Agentforce: https://www.salesforce.com/form/agentforce• SaaStr's AI Agent Playbook: https://saastr.ai/agents• Brian Halligan on LinkedIn: https://www.linkedin.com/in/brianhalligan• Brian Halligan's AI: https://www.delphi.ai/minds/bhalligan• Sierra: https://sierra.ai• Fin: https://fin.ai• Deccan: https://www.deccan.ai• Artisan: https://www.artisan.co• Qualified: https://www.qualified.com• Claude: https://claude.ai• HubSpot: https://www.hubspot.com• Gamma: https://gamma.app• Sam Blond on LinkedIn: https://www.linkedin.com/in/sam-blond-791026b• Brex: https://www.brex.com• Outreach: https://www.outreach.io• Gong: https://www.gong.io• Salesloft: https://www.salesloft.com• Mixmax: https://www.mixmax.com• “Sell the alpha, not the feature”: The enterprise sales playbook for $1M to $10M ARR | Jen Abel: https://www.lennysnewsletter.com/p/the-enterprise-sales-playbook-1m-to-10m-arr• Clay: https://www.clay.com• Owner: https://www.owner.com• Momentum: https://www.momentum.io• Attention: https://www.attention.com• Granola: https://www.granola.ai• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/behind-the-founder-marc-benioff• Palantir: https://www.palantir.com• Databricks: https://www.databricks.com• Garry Tan on LinkedIn: https://www.linkedin.com/in/garrytan• Rippling: https://www.rippling.com• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• The new AI growth playbook for 2026: How Lovable hit $200M ARR in one year | Elena Verna (Head of Growth): https://www.lennysnewsletter.com/p/the-new-ai-growth-playbook-for-2026-elena-verna• Pluribus on AppleTV+: https://tv.apple.com/us/show/pluribus/umc.cmc.37axgovs2yozlyh3c2cmwzlza• Sora: https://openai.com/sora• Reve: https://app.reve.com• Everything That Breaks on the Way to $1B ARR, with Mailchimp Co-Founder Ben Chestnut: https://www.saastr.com/everything-that-breaks-on-the-way-to-1b-arr-with-mailchimp-co-founder-ben-chestnut/• The Revenue Playbook: Rippling's Top 3 Growth Tactics at Scale, with Rippling CRO Matt Plank: https://www.youtube.com/watch?v=h3eYtzBpjRw• 10 contrarian leadership truths every leader needs to hear | Matt MacInnis (Rippling): https://www.lennysnewsletter.com/p/10-contrarian-leadership-truths—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

From creating SWE-bench in a Princeton basement to shipping CodeClash, SWE-bench Multimodal, and SWE-bench Multilingual, John Yang has spent the last year and a half watching his benchmark become the de facto standard for evaluating AI coding agents—trusted by Cognition (Devin), OpenAI, Anthropic, and every major lab racing to solve software engineering at scale. We caught up with John live at NeurIPS 2025 to dig into the state of code evals heading into 2026: why SWE-bench went from ignored (October 2023) to the industry standard after Devin's launch (and how Walden emailed him two weeks before the big reveal), how the benchmark evolved from Django-heavy to nine languages across 40 repos (JavaScript, Rust, Java, C, Ruby), why unit tests as verification are limiting and long-running agent tournaments might be the future (CodeClash: agents maintain codebases, compete in arenas, and iterate over multiple rounds), the proliferation of SWE-bench variants (SWE-bench Pro, SWE-bench Live, SWE-Efficiency, AlgoTune, SciCode) and how benchmark authors are now justifying their splits with curation techniques instead of just "more repos," why Tau-bench's "impossible tasks" controversy is actually a feature not a bug (intentionally including impossible tasks flags cheating), the tension between long autonomy (5-hour runs) vs. interactivity (Cognition's emphasis on fast back-and-forth), how Terminal-bench unlocked creativity by letting PhD students and non-coders design environments beyond GitHub issues and PRs, the academic data problem (companies like Cognition and Cursor have rich user interaction data, academics need user simulators or compelling products like LMArena to get similar signal), and his vision for CodeClash as a testbed for human-AI collaboration—freeze model capability, vary the collaboration setup (solo agent, multi-agent, human+agent), and measure how interaction patterns change as models climb the ladder from code completion to full codebase reasoning. We discuss: John's path: Princeton → SWE-bench (October 2023) → Stanford PhD with Diyi Yang and the Iris Group, focusing on code evals, human-AI collaboration, and long-running agent benchmarks The SWE-bench origin story: released October 2023, mostly ignored until Cognition's Devin launch kicked off the arms race (Walden emailed John two weeks before: "we have a good number") SWE-bench Verified: the curated, high-quality split that became the standard for serious evals SWE-bench Multimodal and Multilingual: nine languages (JavaScript, Rust, Java, C, Ruby) across 40 repos, moving beyond the Django-heavy original distribution The SWE-bench Pro controversy: independent authors used the "SWE-bench" name without John's blessing, but he's okay with it ("congrats to them, it's a great benchmark") CodeClash: John's new benchmark for long-horizon development—agents maintain their own codebases, edit and improve them each round, then compete in arenas (programming games like Halite, economic tasks like GDP optimization) SWE-Efficiency (Jeffrey Maugh, John's high school classmate): optimize code for speed without changing behavior (parallelization, SIMD operations) AlgoTune, SciCode, Terminal-bench, Tau-bench, SecBench, SRE-bench: the Cambrian explosion of code evals, each diving into different domains (security, SRE, science, user simulation) The Tau-bench "impossible tasks" debate: some tasks are underspecified or impossible, but John thinks that's actually a feature (flags cheating if you score above 75%) Cognition's research focus: codebase understanding (retrieval++), helping humans understand their own codebases, and automatic context engineering for LLMs (research sub-agents) The vision: CodeClash as a testbed for human-AI collaboration—vary the setup (solo agent, multi-agent, human+agent), freeze model capability, and measure how interaction changes as models improve — John Yang SWE-bench: https://www.swebench.com X: https://x.com/jyangballin Chapters 00:00:00 Introduction: John Yang on SWE-bench and Code Evaluations 00:00:31 SWE-bench Origins and Devon's Impact on the Coding Agent Arms Race 00:01:09 SWE-bench Ecosystem: Verified, Pro, Multimodal, and Multilingual Variants 00:02:17 Moving Beyond Django: Diversifying Code Evaluation Repositories 00:03:08 Code Clash: Long-Horizon Development Through Programming Tournaments 00:04:41 From Halite to Economic Value: Designing Competitive Coding Arenas 00:06:04 Ofir's Lab: SWE-ficiency, AlgoTune, and SciCode for Scientific Computing 00:07:52 The Benchmark Landscape: TAU-bench, Terminal-bench, and User Simulation 00:09:20 The Impossible Task Debate: Refusals, Ambiguity, and Benchmark Integrity 00:12:32 The Future of Code Evals: Long Autonomy vs Human-AI Collaboration 00:14:37 Call to Action: User Interaction Data and Codebase Understanding Research

From investing through the modern data stack era (DBT, Fivetran, and the analytics explosion) to now investing at the frontier of AI infrastructure and applications at Amplify Partners, Sarah Catanzaro has spent years at the intersection of data, compute, and intelligence—watching categories emerge, merge, and occasionally disappoint. We caught up with Sarah live at NeurIPS 2025 to dig into the state of AI startups heading into 2026: why $100M+ seed rounds with no near-term roadmap are now the norm (and why that terrifies her), what the DBT-Fivetran merger really signals about the modern data stack (spoiler: it's not dead, just ready for IPO), how frontier labs are using DBT and Fivetran to manage training data and agent analytics at scale, why data catalogs failed as standalone products but might succeed as metadata services for agents, the consumerization of AI and why personalization (memory, continual learning, K-factor) is the 2026 unlock for retention and growth, why she thinks RL environments are a fad and real-world logs beat synthetic clones every time, and her thesis for the most exciting AI startups: companies that marry hard research problems (RAG, rule-following, continual learning) with killer applications that were simply impossible before. We discuss: The DBT-Fivetran merger: not the death of the modern data stack, but a path to IPO scale (targeting $600M+ combined revenue) and a signal that both companies were already winning their categories How frontier labs use data infrastructure: DBT and Fivetran for training data curation, agent analytics, and managing increasingly complex interactions—plus the rise of transactional databases (RocksDB) and efficient data loading (Vortex) for GPU-bound workloads Why data catalogs failed: built for humans when they should have been built for machines, focused on discoverability when the real opportunity was governance, and ultimately subsumed as features inside Snowflake, DBT, and Fivetran The $100M+ seed phenomenon: raising massive rounds at billion-dollar valuations with no 6-month roadmap, seven-day decision windows, and founders optimizing for signal ("we're a unicorn") over partnership or dilution discipline Why world models are overhyped but underspecified: three competing definitions, unclear generalization across use cases (video games ≠ robotics ≠ autonomous driving), and a research problem masquerading as a product category The 2026 theme: consumerization of AI via personalization—memory management, continual learning, and solving retention/churn by making products learn skills, preferences, and adapt as the world changes (not just storing facts in cursor rules) Why RL environments are a fad: labs are paying 7–8 figures for synthetic clones when real-world logs, traces, and user activity (à la Cursor) are richer, cheaper, and more generalizable Sarah's investment thesis: research-driven applications that solve hard technical problems (RAG for Harvey, rule-following for Sierra, continual learning for the next killer app) and unlock experiences that were impossible before Infrastructure bets: memory, continual learning, stateful inference, and the systems challenges of loading/unloading personalized weights at scale Why K-factor and growth fundamentals matter again: AI felt magical in 2023–2024, but as the magic fades, retention and virality are back—and most AI founders have never heard of K-factor — Sarah Catanzaro X: https://x.com/sarahcat21 Amplify Partners: https://amplifypartners.com/ Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction: Sarah Catanzaro's Journey from Data to AI 00:01:02 The DBT-Fivetran Merger: Not the End of the Modern Data Stack 00:05:26 Data Catalogs and What Went Wrong 00:08:16 Data Infrastructure at AI Labs: Surprising Insights 00:10:13 The Crazy Funding Environment of 2024-2025 00:17:18 World Models: Hype, Confusion, and Market Potential 00:18:59 Memory Management and Continual Learning: The Next Frontier 00:23:27 Agent Environments: Just a Fad? 00:25:48 The Perfect AI Startup: Research Meets Application 00:28:02 Closing Thoughts and Where to Find Sarah

From Berkeley robotics and OpenAI's 2017 Dota-era internship to shipping RL breakthroughs on GPT-4o, o1, and o3, and now leading model development at Cursor, Ashvin Nair has done it all. We caught up with Ashvin at NeurIPS 2025 to dig into the inside story of OpenAI's reasoning team (spoiler: it went from a dozen people to 300+), why IOI Gold felt reachable in 2022 but somehow didn't change the world when o1 actually achieved it, how RL doesn't generalize beyond the training distribution (and why that means you need to bring economically useful tasks into distribution by co-designing products and models), the deeper lessons from the RL research era (2017–2022) and why most of it didn't pan out because the community overfitted to benchmarks, how Cursor is uniquely positioned to do continual learning at scale with policy updates every two hours and product-model co-design that keeps engineers in the loop instead of context-switching into ADHD hell, and his bet that the next paradigm shift is continual learning with infinite memory—where models experience something once (a bug, a mistake, a user pattern) and never forget it, storing millions of deployment tokens in weights without overloading capacity. We discuss: Ashvin's path: Berkeley robotics PhD → OpenAI 2017 intern (Dota era) → o1/o3 reasoning team → Cursor ML lead in three months Why robotics people are the most grounded at NeurIPS (they work with the real world) and simulation people are the most unhinged (Lex Fridman's take) The IOI Gold paradox: "If you told me we'd achieve IOI Gold in 2022, I'd assume we could all go on vacation—AI solved, no point working anymore. But life is still the same." The RL research era (2017–2022) and why most of it didn't pan out: overfitting to benchmarks, too many implicit knobs to tune, and the community rewarding complex ideas over simple ones that generalize Inside the o1 origin story: a dozen people, conviction from Ilya and Jakob Pachocki that RL would work, small-scale prototypes producing "surprisingly accurate reasoning traces" on math, and first-principles belief that scaled The reasoning team grew from ~12 to 300+ people as o1 became a product and safety, tooling, and deployment scaled up Why Cursor is uniquely positioned for continual learning: policy updates every two hours (online RL on tab), product and ML sitting next to each other, and the entire software engineering workflow (code, logs, debugging, DataDog) living in the product Composer as the start of product-model co-design: smart enough to use, fast enough to stay in the loop, and built by a 20–25 person ML team with high-taste co-founders who code daily The next paradigm shift: continual learning with infinite memory—models that experience something once (a bug, a user mistake) and store it in weights forever, learning from millions of deployment tokens without overloading capacity (trillions of pretraining tokens = plenty of room) Why off-policy RL is unstable (Ashvin's favorite interview question) and why Cursor does two-day work trials instead of whiteboard interviews The vision: automate software engineering as a process (not just answering prompts), co-design products so the entire workflow (write code, check logs, debug, iterate) is in-distribution for RL, and make models that never make the same mistake twice — Ashvin Nair Cursor: https://cursor.com X: https://x.com/ashvinnair_ Chapters 00:00:00 Introduction: From Robotics to Cursor via OpenAI 00:01:58 The Robotics to LLM Agent Transition: Why Code Won 00:09:11 RL Research Winter and Academic Overfitting 00:11:45 The Scaling Era and Moving Goalposts: IOI Gold Doesn't Mean AGI 00:21:30 OpenAI's Reasoning Journey: From Codex to O1 00:20:03 The Blip: Thanksgiving 2023 and OpenAI Governance 00:22:39 RL for Reasoning: The O-Series Conviction and Scaling 00:25:47 O1 to O3: Smooth Internal Progress vs External Hype Cycles 00:33:07 Why Cursor: Co-Designing Products and Models for Real Work 00:34:14 Composer and the Future: Online Learning Every Two Hours 00:35:15 Continual Learning: The Missing Paradigm Shift 00:44:00 Hiring at Cursor and Why Off-Policy RL is Unstable

En 2025, une nouvelle expression s'est imposée dans le vocabulaire de la tech : le « vibe coding ». Derrière ce terme intrigant se cache une pratique qui transforme en profondeur la manière de développer des logiciels.Le vibe coding, que l'on peut traduire par « programmation intuitive », désigne une approche où le développeur ne code plus ligne par ligne, mais décrit simplement ce qu'il souhaite obtenir à une intelligence artificielle. Popularisé par Andrei Karpathy, ancien responsable de l'IA chez Tesla et cofondateur d'OpenAI, ce concept est né dans les communautés de développeurs avant de se diffuser largement dans l'écosystème numérique.Concrètement, il suffit désormais de formuler une demande en langage naturel : créer un script Python, concevoir une page web avec un formulaire, modifier l'interface d'une application ou même développer un jeu ou une application mobile complète. Cette méthode permet un gain de temps spectaculaire et ouvre la création logicielle à des non-développeurs, capables de produire des outils fonctionnels pour le web, le mobile ou des usages métiers comme des CMS ou des ERP.De nombreux outils incarnent cette tendance, à commencer par GitHub Copilot, mais aussi Cursor, Windsurf ou des assistants généralistes comme ChatGPT, Claude ou Gemini, qui génèrent du code à intégrer ensuite de manière classique. D'autres solutions vont plus loin encore, en produisant directement des applications prêtes à l'emploi, comme le propose la startup suédoise Lovable.Dans cet épisode, Sébastien Stormacq, responsable des relations développeurs chez AWS, partage une expérience concrète : la création, en une heure et sans écrire une seule ligne de code, d'un jeu inspiré de Pac-Man grâce au vibe coding. Un exemple révélateur de la puissance, mais aussi des limites de cette approche.Le phénomène soulève des questions cruciales : qualité et sécurité du code généré, risques de bugs majeurs, mais aussi impact sur l'emploi. Si le vibe coding accélère le travail des équipes et augmente la productivité des développeurs expérimentés, il fragilise davantage les profils juniors. Une chose est sûre : plus qu'un simple outil, le vibe coding redéfinit en profondeur le métier de développeur.-----------♥️ Soutien : https://mondenumerique.info/don

Want to build your own website but don't know how to code? This episode is for you.Join JJ and Bubble expert Gio as they show how beginners can use AI-powered tools to design, build, and launch a personal website from scratch — for free.You'll learn how Vibe Coding works, how AI can help you write and edit code, and how tools like Cursor make building websites feel approachable, even if you've never coded before. JJ also shares his own journey from no-code tools to AI-assisted development, showing how anyone can level up their skills.By the end, you'll understand how to preview your site locally, save your work with GitHub, and deploy a live website on the internet — all with AI helping every step of the way.Perfect for students, creators, and curious beginners who want to build real projects using AI.What you'll learn:• What “Vibe Coding” is and why it's beginner-friendly• How AI helps you write, edit, and understand code • How to preview your website before publishing• How to host a personal website for free• How no-code and AI tools work togetherTimestamps:00:00 What is Vibe Coding?00:33 Gio's experience getting started03:59 Intro to GitHub (no stress)06:04 Creating and managing projects13:34 Using Cursor to build locally16:00 Editing and previewing with AI26:18 Deploying with Cloud tools28:30 Publishing your site live32:16 No-code vs AI-assisted building41:50 Where AI and no-code are headed48:10 Final thoughts + course update

Here's what I'm building with as of Dec 2025.Lovable - https://lovable.dev/Cursor - https://www.cursor.comClaude Code - https://claude.ai/ (Sonnet/Ops 4.5)Vercel - https://vercel.com/Railway - https://railway.com/Supabase - https://supabase.com/ Free Email Course - https://bootstrappersparadise.com/courseOnline Community - https://bootstrappersparadise.com/communityBootstrapper's Paradise - https://bootstrappersparadise.com/

Note: Steve and Gene's talk on Vibe Coding and the post IDE world was one of the top talks of AIE CODE: https://www.youtube.com/watch?v=7Dtu2bilcFs&t=1019s&pp=0gcJCU0KAYcqIYzv From building legendary platforms at Google and Amazon to authoring one of the most influential essays on AI-powered development (Revenge of the Junior Developer, quoted by Dario Amodei himself), Steve Yegge has spent decades at the frontier of software engineering—and now he's leading the charge into what he calls the "factory farming" era of code. After stints at SourceGraph and building Beads (a purely vibe-coded issue tracker with tens of thousands of users), Steve co-authored The Vibe Coding Book and is now building VC (VibeCoder), an agent orchestration dashboard designed to move developers from writing code to managing fleets of AI agents that coordinate, parallelize, and ship features while you sleep. We sat down with Steve at AI Engineer Summit to dig into why Claude Code, Cursor, and the entire 2024 stack are already obsolete, what it actually takes to trust an agent after 2,000 hours of practice (hint: they will delete your production database if you anthropomorphize them), why the real skill is no longer writing code but orchestrating agents like a NASCAR pit crew, how merging has become the new wall that every 10x-productive team is hitting (and why one company's solution is literally "one engineer per repo"), the rise of multi-agent workflows where agents reserve files, message each other via MCP, and coordinate like a little village, why Steve believes if you're still using an IDE to write code by January 1st, you're a bad engineer, how the 12–15 year experience bracket is the most resistant demographic (and why their identity is tied to obsolete workflows), the hidden chaos inside OpenAI, Anthropic, and Google as they scale at breakneck speed, why rewriting from scratch is now faster than refactoring for a growing class of codebases, and his 2025 prediction: we're moving from subsistence agriculture to John Deere-scale factory farming of code, and the Luddite backlash is only just beginning. We discuss: Why Claude Code, Cursor, and agentic coding tools are already last year's tech—and what comes next: agent orchestration dashboards where you manage fleets, not write lines The 2,000-hour rule: why it takes a full year of daily use before you can predict what an LLM will do, and why trust = predictability, not capability Steve's hot take: if you're still using an IDE to develop code by January 1st, 2025, you're a bad engineer—because the abstraction layer has moved from models to full-stack agents The demographic most resistant to vibe coding: 12–15 years of experience, senior engineers whose identity is tied to the way they work today, and why they're about to become the interns Why anthropomorphizing LLMs is the biggest mistake: the "hot hand" fallacy, agent amnesia, and how Steve's agent once locked him out of prod by changing his password to "fix" a problem Should kids learn to code? Steve's take: learn to vibe code—understand functions, classes, architecture, and capabilities in a language-neutral way, but skip the syntax The 2025 vision: "factory farming of code" where orchestrators run Cloud Code, scrub output, plan-implement-review-test in loops, and unlock programming for non-programmers at scale — Steve Yegge X: https://x.com/steve_yegge Substack (Stevie's Tech Talks): https://steve-yegge.medium.com/ GitHub (VC / VibeCoder): https://github.com/yegge-labs Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction: Steve Yegge on Vibe Coding and AI Engineering 00:00:59 The Backlash: Who Resists Vibe Coding and Why 00:04:26 The 2000 Hour Rule: Building Trust with AI Coding Tools 00:03:31 The January 1st Deadline: IDEs Are Becoming Obsolete 00:02:55 10X Productivity at OpenAI: The Performance Review Problem 00:07:49 The Hot Hand Fallacy: When AI Agents Betray Your Trust 00:11:12 Claude Code Isn't It: The Need for Agent Orchestration 00:15:20 The Orchestrator Revolution: From Cloud Code to Agent Villages 00:18:46 The Merge Wall: The Biggest Unsolved Problem in AI Coding 00:26:33 Never Rewrite Your Code - Until Now: Joel Spolsky Was Wrong 00:22:43 Factory Farming Code: The John Deere Era of Software 00:29:27 Google's Gemini Turnaround and the AI Lab Chaos 00:33:20 Should Your Kids Learn to Code? The New Answer 00:34:59 Code MCP and the Gossip Rate: Latest Vibe Coding Discoveries

Nvidia übernimmt die Assets des Chip-Startups Groq für 20 Milliarden Dollar. KI hat 2025 über 50 neue Milliardäre geschaffen, darunter die Gründer von Cursor, Lovable und 11 Labs. OpenAI veröffentlicht Nutzungsdaten: 90 Prozent der User machen weniger als fünf Anfragen pro Tag, nur 5 Prozent zahlen für den Service. Die New York Times vergleicht Tesla und Waymo: Tesla hat 30 Robotaxis in Austin, Waymo 2500 insgesamt. Das Manager Magazin deckt den Closed-Skandal auf: Der CFO der Hamburger Modemarke hat sich mutmaßlich 20 Millionen Euro von der Firma geliehen. Die USA sanktionieren fünf europäische Bürger, darunter Ex-EU-Kommissar Thierry Breton und die Geschäftsführerinnen von HateAid. Elon Musk wird zum unbeliebtesten Tech-Leader 2025 gewählt. Apple muss durch den Digital Markets Act Proximity Pairing und Notifications für Drittanbieter öffnen. Und 61 Prozent der US-Pastoren nutzen inzwischen KI für ihre Predigten. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Intro (00:01:15) Nvidia kauft Groq für 20 Mrd. (00:17:16) 50 neue KI-Milliardäre 2025 (00:27:29) OpenAI Nutzungsdaten: 90% unter 5 Anfragen/Tag (00:30:45) OpenAI Prompt Packs für Berufsgruppen (00:37:43) Tesla vs Waymo: 30 vs 2500 Robotaxis (00:44:52) Closed-Insolvenz: CFO leiht sich 20 Mio. (00:54:42) USA sanktionieren HateAid & Thierry Breton (01:01:04) Elon Musk unbeliebtester Tech-Leader (01:05:15) Epstein-Akten: Adobe-Schwärzung versagt (01:06:15) Apple öffnet AirPods-Kopplung (EU DMA) (01:09:21) 61% der Pastoren nutzen KI für Predigten Shownotes Nvidia wirbt Ingenieure von KI-Startup Groq ab - manager-magazin.de KI schuf über 50 neue Milliardäre 2025 - forbes.com Benedick Evans- linkedin.com OpenAI Prompt Packs - academy.openai.com Tesla Robotaxis in Austin: Konkurrenz für Waymo - nytimes.com Insolvenz der Modemarke: So ruinierten die Chefs alles - manager-magazin.de Breton plant Tech-Verbot - apnews.com Marco Rubio - patreon.com Elon Musk mochte Tech nicht - cybernews.com Musk Weihnachts Tweet - x.com Epstein-Akten: DOJ-Streichungen und Links - theverge.com will the robot shoot the human? - youtu.be iOS 26.3: AirPods-Kopplung verbessern - macrumors.com Pastors KI-Predigt - cybernews.com Glöcki KI Weihnachtsvideo - youtube.com

Aaron and Brian review the Year in AI, hand out AI awards, and discuss the biggest AI trends from 2025. Maybe a few predictions will be made as well.SHOW: 987SHOW TRANSCRIPT: The Cloudcast #987 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:SHOW NOTESCLOUD & AI NEWS OF THE MONTH - NOV 2025 (show)CLOUD & AI NEWS OF THE MONTH - OCT 2025 (show)CLOUD & AI NEWS OF THE MONTH - SEPT 2025 (show)CLOUD & AI NEWS OF THE MONTH - AUG 2025 (show)CLOUD & AI NEWS OF THE MONTH - JUL 2025 (show)CLOUD & AI NEWS OF THE MONTH - JUN 2025 (show)CLOUD & AI NEWS OF THE MONTH - MAY 2025 (show)CLOUD & AI NEWS OF THE MONTH - APR 2025 (show)CLOUD & AI NEWS OF THE MONTH - MAR 2025 (show)CLOUD & AI NEWS OF THE MONTH - FEB 2025 (show)CLOUD & AI NEWS OF THE MONTH - JAN 2025 (show)2025 AI YEAR IN REVIEWThe Year of OpenAIThe Year of NVIDIAThe Year of MicrosoftThe Year of GoogleThe Year of OracleThe Year of China AIThe Year of AppleThe Year of Coding Agents (Anthropic, Cursor, Windsurf, CLIs, etc..)The Year of Data CentersAI Highlights and Lowlights (Corporate Layoffs, Acquihires, Funding, etc..)2026 AI DraftFEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

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The Information's Aaron Holmes talks with TITV Host Akash Pasricha about Satya Nadella's deep-dive into Microsoft's product management to fix Copilot. We also talk with Graphite CEO Merrill Lutsky about selling his startup to Cursor, and Madrona Ventures' Matt McIlwain about the future of software investing in 2026. AI Reporter Rocket Drew speaks about the safety risks of humanoid robots, and EV reporter Steve LeVine about Ford's decision to ditch EV production for AI data centers.Articles discussed on this episode: https://www.theinformation.com/articles/microsofts-nadella-pressures-deputies-accelerate-copilot-improvementshttps://www.theinformation.com/articles/electric-fords-leap-powering-ai-data-centers-reflects-industry-adrifthttps://www.theinformation.com/briefings/waymo-suspends-san-francisco-service-city-outageTITV airs on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Subscribe to: - The Information on YouTube: https://www.youtube.com/@theinformation- The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agenda

Send us a textStefan Georgie made $30M by age 23 and has scaled multiple 8-figure businesses. In this conversation, he reveals why AI is creating the biggest wealth transfer opportunity of our generation and why most people are missing it.The marketing world is being rewritten in real time. AI is eliminating old skill sets while creating unprecedented opportunities for those who act fast. Stefan breaks down exactly how young entrepreneurs can leverage AI tools like vibe coding, Cursor, and Claude to build valuable solutions in days, not months.What You'll Learn:• Why AI makes it easier than ever to build profitable businesses from scratch• The exact AI skills that are in highest demand right now (and how to learn them fast)• How to use AI to solve real problems for established businesses willing to pay• Why aging "boomer businesses" are goldmines for AI-savvy entrepreneurs• The hiring story: How a 22-year-old with $40 got a $3K/month job using AI• Why teams are desperate for people who can think AND execute with AI• The fastest path to making your first $10K using AI toolsStefan doesn't hold back, he shares why 98% of your competition can't think critically, why the bar is lower than you think, and how curiosity + AI skills = unlimited opportunity.Connect with Stefan! https://www.stefanpaulgeorgi.com/Connect with Us!https://www.instagram.com/alchemists.library/https://twitter.com/RyanJAyala

This is a recap of the top 10 posts on Hacker News on December 18, 2025. This podcast was generated by wondercraft.ai (00:30): Beginning January 2026, all ACM publications will be made open accessOriginal post: https://news.ycombinator.com/item?id=46313991&utm_source=wondercraft_ai(01:53): We pwned X, Vercel, Cursor, and Discord through a supply-chain attackOriginal post: https://news.ycombinator.com/item?id=46317098&utm_source=wondercraft_ai(03:16): Your job is to deliver code you have proven to workOriginal post: https://news.ycombinator.com/item?id=46313297&utm_source=wondercraft_ai(04:39): Classical statues were not painted horriblyOriginal post: https://news.ycombinator.com/item?id=46311856&utm_source=wondercraft_ai(06:02): Are Apple gift cards safe to redeem?Original post: https://news.ycombinator.com/item?id=46313061&utm_source=wondercraft_ai(07:25): Please just try HTMXOriginal post: https://news.ycombinator.com/item?id=46312973&utm_source=wondercraft_ai(08:48): GPT-5.2-CodexOriginal post: https://news.ycombinator.com/item?id=46316367&utm_source=wondercraft_ai(10:11): Ask HN: Those making $500/month on side projects in 2025 – Show and tellOriginal post: https://news.ycombinator.com/item?id=46307973&utm_source=wondercraft_ai(11:34): Independent review of UK national security law warns of overreachOriginal post: https://news.ycombinator.com/item?id=46311355&utm_source=wondercraft_ai(12:58): History LLMs: Models trained exclusively on pre-1913 textsOriginal post: https://news.ycombinator.com/item?id=46319826&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Elena Verna is the head of growth at Lovable, the leading AI-powered app builder that hit $200 million in annual recurring revenue in under a year with just 100 employees. In this record fourth appearance on the podcast, Elena shares how the traditional growth playbook has been completely rewritten for AI companies. She explains why Lovable focuses on innovation over optimization, how they've shifted from activation to building new features, and why giving away their product for free has become their most powerful growth strategy.We discuss:1. Why 60% to 70% of traditional growth tactics no longer apply in AI2. Why you have to re-find product-market fit every 3 months3. The specific growth tactics driving Lovable's unprecedented growth4. Why giving away product is a growth strategy that beats paid ads5. “Minimum lovable product” as the new standard (not minimum viable product)6. Why activation now belongs to product teams, not growth teams7. Whether you should join an AI startup (honest tradeoffs)—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUsVercel—Your collaborative AI assistant to design, iterate, and scale full-stack applications for the webPersona—A global leader in digital identity verification—Transcript: ⁠https://www.lennysnewsletter.com/p/the-new-ai-growth-playbook-for-2026-elena-verna⁠—My biggest takeaways (for paid newsletter subscribers): ⁠https://www.lennysnewsletter.com/i/181207556/my-biggest-takeaways-from-this-conversation⁠—Where to find Elena Verna:• X: https://x.com/elenaverna• LinkedIn: https://www.linkedin.com/in/elenaverna• Newsletter: https://www.elenaverna.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Elena Verna(05:19) The scale and growth of Lovable(08:55) Confidence in Lovable as a business(12:17) Retention at Lovable(15:02) Lovable's unique growth levers(28:13) The role of marketing in Lovable's success(38:09) Launching new features(40:59) Hiring and team dynamics(43:17) The value of vibe coding(49:46) The importance of community(51:47) Giving away your product for free(56:26) Tripling their company size(01:00:23) Product-market-fit challenges(01:08:50) Advice for joining AI companies(01:12:00) Work-life balance(01:15:20) What it's like to work at Lovable(01:19:45) Women in tech(01:25:29) Final thoughts and lightning round—Referenced:• Elena Verna on how B2B growth is changing, product-led growth, product-led sales, why you should go freemium not trial, what features to make free, and much more: https://www.lennysnewsletter.com/p/elena-verna-on-why-every-company• The ultimate guide to product-led sales | Elena Verna: https://www.lennysnewsletter.com/p/the-ultimate-guide-to-product-led• 10 growth tactics that never work | Elena Verna (Amplitude, Miro, Dropbox, SurveyMonkey): https://www.lennysnewsletter.com/p/10-growth-tactics-that-never-work-elena-verna• Lovable: https://lovable.dev• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Stripe: https://stripe.com• What differentiates the highest-performing product teams | John Cutler (Amplitude, The Beautiful Mess): https://www.lennysnewsletter.com/p/what-differentiates-the-highest-performing• How to win in the AI era: Ship a feature every week, embrace technical debt, ruthlessly cut scope, and create magic your competitors can't copy | Gaurav Misra (CEO and co-founder of Captions): https://www.lennysnewsletter.com/p/how-to-win-in-the-ai-era-gaurav-misra• “Dumbest idea I've heard” to $100M ARR: Inside the rise of Gamma | Grant Lee (CEO): https://www.lennysnewsletter.com/p/how-50-people-built-a-profitable-ai-unicorn• Eric Ries on LinkedIn: https://www.linkedin.com/in/eries• Elena's post on LinkedIn about Lovable Missions: https://www.linkedin.com/posts/elenaverna_everythingispossible-lovableway-activity-7401627519646474242-hn6e• SheBuilds: https://shebuilds.lovable.app• Shopify + Lovable: https://lovable.dev/shopify• The Product-Market Fit Treadmill: Why every AI company is sprinting just to stay in place: https://www.elenaverna.com/p/the-product-market-fit-treadmill• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Unorthodox frameworks for growing your product, career, and impact | Bangaly Kaba (YouTube, Instagram, Facebook, Instacart): https://www.lennysnewsletter.com/p/frameworks-for-growing-your-career-bangaly-kaba• The adjacent user: https://brianbalfour.com/quick-takes/the-adjacent-user• Granola: https://www.granola.ai• Wispr Flow: https://wisprflow.ai• I'm worried about women in tech: https://www.elenaverna.com/p/im-worried-about-women-in-tech• Slack founder: Mental models for building products people love ft. Stewart Butterfield: https://www.lennysnewsletter.com/p/slack-founder-stewart-butterfield—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Did AI end up being a political force this year?

AGENDA: 03:32 Lightspeed's $9 Billion Fundraise 05:20 The Impact of Mega Funds on Seed VCs 10:09 The Supercycle of Growth and Late-Stage Investments 13:06 Disney Invests $1BN into OpenAI and What It Means 23:19 Oracle Hit Hard: Is Now the Time to Buy 28:34 Broadcom's Market Cap Drop and Anthropic's AI Chip Orders 35:04 Cursor Competes with Figma: The Convergence of Design and Coding Tools 46:20 The Biggest Danger for Incumbents: Being Maimed by AI 55:28 Boom Supersonic Raising $300M to… Power Data Centres… WTF 01:00:24 Will SpaceX IPO at $1.5TRN and The Elon Option Value    

You open Excel daily, but are you using AI to make it work for you? While 58% of professionals have tried AI, only 17% use it regularly—a missed opportunity. Join CPA Kyle Ashcraft in this hands-on webinar to learn vibe coding—a no-programming approach using Cursor AI to automate repetitive Excel tasks. Watch Kyle transform messy spreadsheets, organize GL data, and reconcile transactions with simple AI prompts while keeping data secure. You'll get three ready-to-use scripts plus a framework to automate countless tasks and reclaim hours weekly.(Originally recorded on October 20, 2025, on Earmark Webinars+)Chapters(02:18) - Meet Kyle Ashcraft and His AI Journey (02:31) - The Importance of AI in Accounting (03:30) - Kyle's Background and CPA Review (04:38) - Live Webinar and Audience Interaction (05:12) - Kyle's AI Projects and Cursor Introduction (07:39) - Data Privacy Concerns with AI (17:18) - Practical AI in Excel: Examples and Demonstration (20:03) - Getting Started with Cursor (23:55) - First Cursor Project: Cleaning Up Excel Data (31:38) - Jumping into Financial Document Verification (32:50) - Exploring Cursor's Privacy Settings (33:48) - Understanding Data Retention Policies (36:23) - Comparing Excel Files with Cursor (36:48) - Analyzing Complex GL Details (42:22) - Using Cursor for Recurring Accounting Tasks (49:20) - Leveraging AI for Audit and Analysis (50:53) - Practical Tips for Implementing Cursor (53:56) - Q&A: Advanced Cursor Features (59:04) - Conclusion and Next Steps Earn CPE for this episode: https://www.earmark.app/c/2854Sign up to get free CPE for listening to this podcasthttps://earmarkcpe.comhttps://earmark.app/Download the Earmark CPE App Apple: https://apps.apple.com/us/app/earmark-cpe/id1562599728Android: https://play.google.com/store/apps/details?id=com.earmarkcpe.appResourcesIntro to Cursor PDF Guide - https://mcusercontent.com/02dbcae4a3e3f15021db25a0c/files/deff5647-e0a3-51d7-4225-cf8b3a48532d/Cursor_AI_Quick_Guide.pdfWebinar presentation - https://ai.maxwellstudy.com/Connect with Our Guest, Kyle Ashcraft, CPALinkedIn: https://www.linkedin.com/in/kyle-ashcraft-cpa-7638a42aLearn more about Maxwell CPA Reviewhttps://maxwellcpareview.com/Connect with Blake Oliver, CPALinkedIn: https://www.linkedin.com/in/blaketoliverTwitter: https://twitter.com/blaketoliver/

Ryo Lu spent years watching his designs die in meetings. Then he discovered the tool that lets designers ship code at the speed of thought: Cursor, the company where Ryo is now Head of Design. In this episode, a16z General Partner Jennifer Li sits down with Ryo to discuss why "taste" is the wrong framework for understanding the future, why purposeful apps are "selfish," how System 7 holds secrets about AI interfaces, and the radical bet that one codebase can serve everyone if you design the concepts right instead of the buttons. Timecodes:00:01:45 - Design Becomes Approachable to Everyone00:02:36 - From Years to Minutes: Product Feedback Loops Collapse00:07:54 - "Each role used their own tool...their own lingo"00:13:15 - "If you don't have an opinion, you'll get AI slop"00:17:18 - The Lost Art of Being a Complete Builder00:21:42 - Design Is Not About Aesthetics00:28:57 - User-Centric vs System-Centric Philosophy00:34:00 - AI as Universal Interface, Not Chat Box00:38:42 - "Simplicity is the Biggest Constraint"00:43:42 - "I Don't Sit in Figma All Day Making Mocks"00:46:33 - RyoOS: Building A Personal Operating System00:48:45 - "We've been doing the same thing since 1984" Resources:Follow Ryo Lu on X: https://x.com/ryolu_Follow Jennifer Li on X: https://x.com/JenniferHliFollow Erik Torenberg on X: https://x.com/eriktorenberg Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!  Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

A deadbolt clicks. This email, that voice--they sound all right. Then things go sideways. This week, 911 Cyber CEO Marc Raphael joins the pod to explore how AI makes scams faster, smoother, and harder to spot, and what you can do to stay hard to hit in the new threatscape.  Learn more about your ad choices. Visit megaphone.fm/adchoices

David George is a General Partner at Andreessen Horowitz, where he leads the firm's Growth investing team. His team has backed many of the defining companies of this era, including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI, and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. AGENDA: 03:05 – Why Everyone is Wrong: Mega Funds Does Not Reduce Returns 10:40 – Is Public Market Capital Actually Cheaper Than Private Capital? 18:55 – The Biggest Advantage of Staying Private for Longer 23:30 – The #1 Investing Rule for a16z: Always Invest in the Founder's Strength of Strengths 31:20 – Why Fear of Theoretical Competition Makes Investors Miss Great Companies 35:10 – Does Revenue Matter as Much in a World of AI? 44:10 – Does Kingmaking Still Exist in Venture Capital Today? 49:20 – Do Margins Matter Less Than Ever in an AI-First World? 53:50 – My Biggest Miss: Anthropic and What I Learn From it?  56:30 – Has OpenAI Won Consumer AI? Will Anthropic Win Enterprise? 59:45 – The Most Controversial Decision in Andreessen Horowitz History 1:01:30 – Why Did You Invest $300M into Adam Neumann and Flow?    

What if understanding your codebase was no longer a blocker for great testing? Most testers were trained to work around the code — clicking through UIs, guessing selectors, and relying on outdated docs or developer explanations. In this episode, Playwright expert Ben Fellows flip that model on its head. Using AI tools like Cursor, testers can now explore the codebase directly — asking questions, uncovering APIs, understanding data relationships, and spotting risk before a single test is written. This isn't about becoming a developer. It's about using AI to finally see how the system really works — and using that insight to test smarter, earlier, and with far more confidence. If you've ever joined a new team, inherited a legacy app, or struggled to understand what really changed in a release, this episode is for you. Registration for Automation Guild 2026 Now: https://testguild.me/podag26

Corey Quinn reconnects with Keith Townsend, founder of The CTO Advisor, for a candid conversation about the massive gap between AI hype and enterprise reality. Keith shares why a biopharma company gave Microsoft Copilot a hard no, and why AI has genuinely 10x'd his personal productivity while Fortune 500 companies treat it like radioactive material. From building apps with Cursor to watching enterprises freeze in fear of being the next AI disaster in the news, Keith and Corey dig into why the tools transforming solo founders and small teams are dead on arrival in the enterprise, and what it'll actually take to bridge that gap.About Keith TownsendKeith Townsend is an enterprise technologist and founder of The Advisor Bench LLC, where he helps major IT vendors refine their go-to-market strategies through practitioner-driven insights from CIOs, CTOs, and enterprise architects. Known as “The CTO Advisor,” Keith blends deep expertise in IT infrastructure, AI, and cloud with a talent for translating complex technology into clear business strategy.With more than 20 years of experience, including roles as a systems engineer, enterprise architect, and PwC consultant, Keith has advised clients such as HPE, Google Cloud, Adobe, Intel, and AWS. His content series, 100 Days of AI and CloudEveryday.dev, provide practical, plainspoken guidance for IT leaders. A frequent speaker at VMware Explore, Interop, and Tech Field Day, Keith is a trusted voice on cloud and infrastructure transformation.Show Highlights(01:25) Life After the Futurum Group Acquisition(03:56) Building Apps You're Not Qualified to Build with Cursor(05:45)Creating an AI-Powered RSS Reader(09:01) Why AI is Great at Language But Not Intelligence(11:39) Are You Looking for Advice or Just Validation?(13:49) Why Startups Can Risk AI Disasters and AWS Can't(17:28) You Can't Outsource Responsibility(19:52) Business Users Are Scared of AI Too(23:00) LinkedIn's AI Writing Tool Misses the Point(26:42) Private AI is Starting to Look Appealing(29:00) Never Going Back to Pre-AI Development(34:27) AI for Jobs You'd Never Hire Someone to Do(39:09) Where to Find Keith and Closing ThoughtsLinksThe CTO Advisor:  https://thectoadvisor.comSponsor: https://www.sumologic.com/solutions/dojo-aihttps://wiz.io/crying-out-cloud

Eytan Seidman, VP of product at Shopify, joins the podcast to unpack Shopify's Winter '26 Edition and how AI is emerging into the market for developers and merchants. They discuss the new Dev MCP server, showing how tools like Cursor and Claude Desktop can rapidly scaffold Shopify apps, wire up Shopify functions, and ship payment customization and checkout UI extension experiences that lean on Shopify primitives like meta fields and meta objects across online stores and point of sale. Eytan also breaks down how Sidekick connects with apps, why the new analytics API and ShopifyQL open fresh analytics use cases, and more. Links Shopify Winter '26 Edition: https://www.shopify.com/editions/winter2026 We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Fill out our listener survey (https://t.co/oKVAEXipxu)! https://t.co/oKVAEXipxu Let us know by sending an email to our producer, Elizabeth, at elizabeth.becz@logrocket.com (mailto:elizabeth.becz@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Check out our newsletter (https://blog.logrocket.com/the-replay-newsletter/)! https://blog.logrocket.com/the-replay-newsletter/ Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. (https://logrocket.com/signup/?pdr) Chapters 01:00 — AI as the Focus of Winter '26 02:00 — MCP Server as the Ideal Dev Workflow 03:00 — Best Clients for MCP (Cursor, Claude Desktop) 04:00 — Hallucinations & Code Validation in MCP 06:00 — Developer Judgment & Platform Primitives 07:00 — Storage Choices: Meta Fields vs External Storage 09:00 — Learning UI Patterns Through MCP 10:00 — Sidekick Overview & Merchant Automation 11:00 — Apps Inside Sidekick: Data & UI Integration 13:00 — Scopes, Data Access & Developer Responsibility 14:00 — AI-Ready Platform & Explosion of New Apps 16:00 — New Developer Demographics Entering Shopify 17:00 — Where Indie Devs Should Focus (POS, Analytics) 18:00 — New Analytics API & Opportunities 19:00 — Full Platform Coverage via MCP Tools 20:00 — Building Complete Apps in Minutes 21:00 — Large Stores, Token Limits & MCP Scaling 22:00 — Reducing Errors with UI & Function Testing 23:00 — Lessons from Building the MCP Server 25:00 — Lowering Barriers for Non-Experts 26:00 — High-Quality Rust Functions via MCP 27:00 — MCP Spec Adoption: Tools Over Resources 28:00 — Future: Speed, Quality & UI Precision 29:00 — Model Evolution, Evals & Reliability 31:00 — Core Shopify Primitives to Build On 33:00 — Docs, Community & Learning Resources

Transitioning a mature organization from an API-first model to an AI-first model is no small feat. In this episode, Yash Kosaraju, CISO of Sendbird, shares the story of how they pivoted from a traditional chat API platform to an AI agent platform and how security had to evolve to keep up.Yash spoke about the industry's obsession with "Zero Trust," arguing instead for a practical "Multi-Layer Trust" approach that assumes controls will fail . We dive deep into the specific architecture of securing AI agents, including the concept of a "Trust OS," dealing with new incident response definitions (is a wrong AI answer an incident?), and the critical need to secure the bridge between AI agents and customer environments .This episode is packed with actionable advice for AppSec engineers feeling overwhelmed by the speed of AI. Yash shares how his team embeds security engineers into sprint teams for real-time feedback, the importance of "AI CTFs" for security awareness, and why enabling employees with enterprise-grade AI tools is better than blocking them entirely .Questions asked:Guest Socials - Yash's LinkedinPodcast Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CloudSecPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Podcast- Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Newsletter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you are interested in AI Cybersecurity, you can check out our sister podcast -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AI Security Podcast⁠Questions asked:(00:00) Introduction(02:20) Who is Yash Kosaraju? (CISO at Sendbird)(03:30) Sendbird's Pivot: From Chat API to AI Agent Platform(05:00) Balancing Speed and Security in an AI Transition(06:50) Embedding Security Engineers into AI Sprint Teams(08:20) Threats in the AI Agent World (Data & Vendor Risks)(10:50) Blind Spots: "It's Microsoft, so it must be secure"(12:00) Securing AI Agents vs. AI-Embedded Applications(13:15) The Risk of Agents Making Changes in Customer Environments(14:30) Multi-Layer Trust vs. Zero Trust (Marketing vs. Reality) (17:30) Practical Multi-Layer Security: Device, Browser, Identity, MFA(18:25) What is "Trust OS"? A Foundation for Responsible AI(20:45) Balancing Agent Security vs. Endpoint Security(24:15) AI Incident Response: When an AI Gives a Wrong Answer(29:20) Security for Platform Engineers: Enabling vs. Blocking(30:45) Providing Enterprise AI Tools (Gemini, ChatGPT, Cursor) to Employees(32:45) Building a "Security as Enabler" Culture(36:15) What Questions to Ask AI Vendors (Paying with Data?)(39:20) Personal Use of Corporate AI Accounts(43:30) Using AI to Learn AI (Gemini Conversations)(45:00) The Stress on AppSec Engineers: "I Don't Know What I'm Doing"(48:20) The AI CTF: Gamifying Security Training(50:10) Fun Questions: Outdoors, Team Building, and Indian/Korean Food

Tomer Cohen is the longtime chief product officer at LinkedIn, where he's pioneering the Full Stack Builder program, a radical new approach to product development that fully embraces what AI makes possible. Under his leadership, LinkedIn has scrapped its traditional Associate Product Manager program and replaced it with an Associate Product Builder program that teaches coding, design, and PM skills together. He's also introduced a formal “Full Stack Builder” title and career ladder, enabling anyone from any function to take products from idea to launch. In this conversation, Tomer explains why product development has become too complex at most companies and how LinkedIn is building an AI-powered product team that can move faster, adapt more quickly, and do more with less.We discuss:1. How 70% of the skills needed for jobs will change by 20302. The broken traditional model: organizational bloat slows features to a six-month cycle3. The Full Stack Builder model4. Three pillars of making FSB work: platform, agents, and culture (culture matters most)5. Building specialized agents that critique ideas and find vulnerabilities6. Why off-the-shelf AI tools never work on enterprise code without customization7. Top performers adopt AI tools fastest, contrary to expectations about leveling effects8. Change management tactics: celebrating wins, making tools exclusive, updating performance reviews—Brought to you by:Vanta—Automate compliance. Simplify security: https://vanta.com/lennyFigma Make—A prompt-to-code tool for making ideas real: https://www.figma.com/lenny/Miro—The AI Innovation Workspace where teams discover, plan, and ship breakthrough products: https://miro.com/lenny—Transcript: https://www.lennysnewsletter.com/p/why-linkedin-is-replacing-pms—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/180042347/my-takeaways-from-this-conversation—Where to find Tomer Cohen:• LinkedIn: https://www.linkedin.com/in/tomercohen• Podcast: https://podcasts.apple.com/us/podcast/building-one-with-tomer-cohen/id1726672498—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Tomer Cohen(04:42) The need for change in product development(11:52) The full-stack builder model explained(16:03) Implementing AI and automation in product development(19:17) Building and customizing AI tools(27:51) The timeline to launch(31:46) Pilot program and early results(37:04) Feedback from top talent(39:48) Change management and adoption(46:53) Encouraging people to play with AI tools(41:21) Performance reviews and full-stack builders(48:00) Challenges and specialization(50:05) Finding talent(52:46) Tips for implementing in your own company(56:43) Lightning round and final thoughts—Referenced:• How LinkedIn became interesting: The inside story | Tomer Cohen (CPO at LinkedIn): https://www.lennysnewsletter.com/p/how-linkedin-became-interesting-tomer-cohen• LinkedIn: https://www.linkedin.com• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Devin: https://devin.ai• Figma: https://www.figma.com• Microsoft Copilot: https://copilot.microsoft.com• Windsurf: https://windsurf.com• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan• Lovable: https://lovable.dev• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• APB program at LinkedIn: https://careers.linkedin.com/pathways-programs/entry-level/apb• Naval Ravikant on X: https://x.com/naval• One Song podcast: https://podcasts.apple.com/us/podcast/%D7%A9%D7%99%D7%A8-%D7%90%D7%97%D7%93-one-song/id1201883177• Song Exploder podcast: https://songexploder.net• Grok on Tesla: https://www.tesla.com/support/grok• Reid Hoffman on X: https://x.com/reidhoffman—Recommended books:• Why Nations Fail: The Origins of Power, Prosperity, and Poverty: https://www.amazon.com/Why-Nations-Fail-Origins-Prosperity/dp/0307719227• Outlive: The Science and Art of Longevity: https://www.amazon.com/Outlive-Longevity-Peter-Attia-MD/dp/0593236599• The Beginning of Infinity: Explanations That Transform the World: https://www.amazon.com/Beginning-Infinity-Explanations-Transform-World/dp/0143121359—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

This Week In Startups is made possible by:LinkedIn Ads - http://linkedin.com/thisweekinstartupsVanta - https://www.vanta.com/twistPilot - https://pilot.com/twistToday's show: Did you know there's actually a shortage of US bricklayers? It's TRUE! So feel free to marvel at Monumental's brick-laying robots. They're not putting anyone out of work, but filling a much-needed gap.Join Alex and Monumental founder/CEO Salar al Khafaji for a deep-dive on how the startup is making construction robots play nice together by maintaining separate “zones” of operation, why Salar thinks startups need to focus on truly complex, real-world problems to truly blossom, and the secrets of fundraising in Europe.PLUS Alex chats with Seasats CEO Mike Flanigan about designing the next generation of autonomous marine crafts. (That is to say, ocean drones.) From their home base in San Diego, the company is trying to get completely independent of all Chinese parts. Find out how it's going, how they're overcoming the “wildly negative” ROI on maritime tech, and why we have so few defenses against tiny, agile drones.All that AND Jason takes some of YOUR Founder Questions.Timestamps:(03:23) How Monumental determined what kinds of robots construction sites need the most(06:49) How maintaining “zones” ensure that the robots all play nice with one another(07:52) There's a shortage of bricklayers, so Monumental's NOT taking anyone's job(9:16) LinkedIn Ads: Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to http://linkedin.com/thisweekinstartups to claim your credit.(13:21) Why startups need to tackle large-scale, complex, real-world problems to really grow(15:44) Why Monumental is building in The Netherlands, and running pilots in the UK(19:07) Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist(20:44) Why construction is unique among applications for automation and robots(26:01) Salar argues that fundraising in Europe is not as hard as you may have heard(27:55) We don't just need housing, we need BEAUTIFUL housing(31:11) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first year. (33:25) How the Scout autonomous boat challenge inspired Seasats(35:28) Trying to make drones into an “iPhone Style” project(37:39) Why Seasats is focused on endurance and staying power more than launches(39:15) The complexities of working with fuel cells(42:27) The importance of beautiful design even when working on government technology(45:51) Why they're building Seasats in beautiful San Diego, CA(47:29) The challenge of getting entirely free from Chinese components(53:52) “The Power of Small Things Has Changed”(55:18) The “wildly negative” ROI on most humanoid robotics companies also applies to maritime tech(59:09) Why there are so few defense nets against people with tiny but agile drones(01:02:32) FOUNDER Q's: Is a founder working 24/7 a red flag?(01:10:11) How bad is it to use VC money to pay off credit cards?(01:12:49) A look at Cursor's unique recruitment strategy.(01:19:57) Should young VCs go to startup conferences?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Thank you to our partners:(9:16) LinkedIn Ads: Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to http://linkedin.com/thisweekinstartups to claim your credit.(19:07) Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist(31:11) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first year.

My guest today is David George. David is a General Partner at Andreessen Horowitz, where he leads the firm's growth investing business. His team has backed many of the defining companies of this era – including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI – and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. This conversation is a detailed look at how David built and runs the a16z growth practice. He shares how he recruits and builds his team a “Yankees-level” culture, how his team makes investment decisions without traditional committees, and how they work with founders years before investing to win the most competitive deals. Much of our conversation centers on AI and how his team is investing across the stack, from foundational models to applications. David draws parallels to past platform shifts – from SaaS to mobile – and explains why he believes this period will produce some of the largest companies ever built. David also outlines the models that guide his approach – why markets often misprice consistent growth, what makes “pull” businesses so powerful, and why most great tech markets end up winner-take-all. David reflects on what he's learned from studying exceptional founders and why he's drawn to a particular type, the “technical terminator.” Please enjoy my conversation with David George. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp's mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ramp.com/invest to sign up for free and get a $250 welcome bonus. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. ----- This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like The Best (00:04:00) Meet David George (00:03:04) Understanding the Impact of AI on Consumers and Enterprises (00:05:56) Monetizing AI: What is AI's Business Model (00:11:04) Investing in Robotics and American Dynamism (00:13:31) Lessons from Investing in Waymo (00:15:55) Investment Philosophy and Strategy (00:17:15) Investing in Technical Terminators (00:20:18) Market Leaders Capture All of the Value Creation (00:24:56) The Maturation of VC and Competitive Landscape (00:28:18) What a16z Does to Win Deals (00:33:06) David's Daily Routine: Meetings Structure and Blocking Time to Think (00:36:34) Why David Invests: Curiosity and Competition (00:40:12) The Unique Culture at Andreessen Horowitz (00:42:46) The Perfect Conditions for Growth Investing (00:47:04) Push v. Pull Businesses (00:49:19) The Three Metrics a16z Uses to Evaluate AI Companies (00:52:15) Unique Products and Unique Distribution (00:54:55) Tradeoffs of the a16z Firm Structure (00:59:04) a16z's Semi-Algorithmic Approach to Selling (01:00:54) Three Ways Startups can Beat Incumbents in AI (01:03:44) The Kindest Thing