Podcasts about ramp

Ara Kharazian is the lead economist at Ramp. Kharazian joins Big Technology to discuss how much companies are actually spending on AI and whether that spending is producing real value. Tune in to hear why Anthropic has overtaken OpenAI among businesses, how AI spending varies dramatically from company to company, and whether “tokenmaxing” is really happening. We also cover Anthropic's clash with the White House, the resurgence of DeepSeek, Google's underrated position in AI, and whether the predicted SaaS apocalypse is materializing. Hit play for a data-driven look at which AI narratives are real, which are exaggerated, and where business adoption goes next. Learn more about your ad choices. Visit megaphone.fm/adchoices

Invest Like the Best: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- My guest today is Alex Sacerdote, founder of Whale Rock Capital Management.  Whale Rock is a technology focused investment firm that manages more than $17 billion across hedge fund, long only, and hybrid strategies. Over the past three years it has been one of the best performing hedge funds, compounding at roughly 44 percent a year. Alex invests through a single lens that he has refined over twenty years. He looks for technology S-curves, durable competitive advantages, and underappreciated earnings power.  This conversation is a tour through how he applies that framework right now. We start with his highest conviction position, which is Anthropic, and use it to work through the entire AI stack from chips to models to applications.  Please enjoy my conversation with Alex Sacerdote. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠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. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠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. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like The Best (00:00:00) Welcome to Invest Like The Best (00:02:29) Alex Sacerdote (00:03:08) Anthropic: Highest Conviction Position (00:13:23) Investing in Private Markets at Scale (00:19:08) S-Curves: The Full Framework (00:25:08) When to Buy Tech Companies (00:30:20) Identifying the Leader from the Pack (00:34:04) Anthropic & OpenAI's Competitive Moats (00:37:31) AI's Threat to Enterprise Software (00:43:18) Network Effects in the Agent Era (00:44:22) The Hardware Renaissance: Chips & Infrastructure (00:53:56) Why So Few Investors Get This Right (00:55:36) Key Risks to the AI Bull Case (00:57:47) The Application Layer (00:59:40) How AI Is Changing Research at WhaleRock (01:02:53) The Role of Investor Networks & Idea Sharing (01:03:40) Building a Multi-Product Firm (01:07:58) WhaleRock as a Learning Machine (01:09:15) The Kindest Thing

Here's my brief recap of the amazing Irresistible 2026 (photos coming), and my discussion with clients about many things, including the new insane costs of AI. I just read a study that Ramp (credit card) did, discovering that the top AI users are spending $7500 per month per employee on AI. (Yikes!) That aside, the conference was spectacular and we all learned a lot. Stay tuned for a more detailed article on the Pacesetters and other major research we unveiled. In the meantime here's my update on economics and AI maturity (companies are maturing and learning about this stuff quickly), as well as my heartfelt thanks to everyone who participated. Additional Information Announcements: The Josh Bersin Institute, HR 2030, And The Global HR Excellence Certification. HR 2030: Overview and Detailed Blueprint for clients and Galileo Users AI Prices Are Going Up, Up, Up – And What This Means For Enterprise AI Chapters (00:00:00) - Irresistible Conference 2017(00:00:55) - What I Learned at the Conference on AI & the Code(00:01:52) - The role of data in AI HR(00:03:44) - The Token Economics of AI(00:08:03) - Intro to Enterprise AI and HR(00:12:29) - The Future of AI HR(00:15:42) - Happy Summer Solstice!

Het WK is van start! En dus bespreken Valentijn Driessen, Mike Verweij, Jeroen Kapteijns en Hein Keijser de allereerste wedstrijd van het toernooi in de voetbalpodcast Kick-off Oranje. Verder gaat het over de training van Oranje, waar Bart Verbruggen individueel trainde. Bij Japan heeft de aanvoerder van het elftal, Wataru Endo, geblesseerd moeten afhaken. Wat betekent dit voor de wedstrijd tegen Nederland, en komt een volgende ronde voor Japan in gevaar? En: The special one is eigenlijk de Louis van Gaal van Portugal en Uefa en Fifa delen speldenprikjes aan elkaar uit. See omnystudio.com/listener for privacy information.

On this special segment of The Full Ratchet, the following Investors are featured: Ben Orthlieb of Blue Moon Seth Levine of Foundry Steve Blank is an Adjunct Professor at Stanford We asked guests to tell the most important lesson they've learned in their career. The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

What I learned from reading Jony Ive: The Genius Behind Apple's Greatest Products by  Leander Kahney. Made possible by: Ramp: https://ramp.com Axon by Applovin: https://axon.ai/founders Vanta: https://vanta.com/founders

Can AI now do bookkeeping better than humans? Blake and David dig into new data showing major AI models outperforming outsourced accountants on basic transaction coding, then explore what that means for firms, finance teams, and the future of audit. They also cover a one-person finance team powered by AI agents, KPMG's scramble to keep up, and why the accounting talent shortage still isn't going away.SponsorsOnPay - http://accountingpodcast.promo/onpayThe Value Builder System - http://accountingpodcast.promo/valueR.E. Cost Seg - http://accountingpodcast.promo/recostsegChapters(00:00) - TAP 491 (00:38) - Top stories preview (03:23) - OnPay support story (04:08) - Finance team of one (06:49) - LLMs vs humans benchmarks (09:15) - Ramp Stack agents (13:04) - Digits interview begins (19:55) - Outcome pricing and skills (28:05) - Livestream Q&A reactions (29:27) - Future of audit Oath (30:29) - Oath AI Audit Vision (31:46) - Continuous Audit Workflow (32:21) - Business Model Debate (33:02) - Big Four On Alert (33:07) - Accounting Engineer Hiring (33:47) - KPMG Courts AI Startups (35:15) - Talent Shortage Worsens (36:31) - Why Seniors Are Scarce (39:55) - Ramp Stack AI Agents (47:14) - Procurement Agents And Valuation (48:50) - KPMG Token Maxing Dashboard (52:31) - KPMG Australia Fallout (54:45) - Trump Tax Settlement Update (56:14) - IRS Leadership Vacuum (59:28) - Wrap Up And Earmark News  Show NotesDigits "Beyond the AI Hype" Benchmark — AI Models Now Beat Human Accountantshttps://blog.insightfulaccountant.com/digits-releases-latest-edition-of-their-beyond-the-ai-hype-benchmarkRamp Launches Stack, an AI Operating System for Accounting Firmshttps://www.prnewswire.com/news-releases/ramp-launches-stack-an-ai-operating-system-for-accounting-firms-302789630.htmlRamp Launches Fleet of AI Agents Across Its Procurement Platformhttps://www.prnewswire.com/news-releases/ramp-launches-fleet-of-ai-agents-across-its-procurement-platform-302756657.htmlRamp Raises $750 Million Series F at $44 Billion Valuationhttps://www.prnewswire.com/news-releases/ramp-raises-series-f-at-44-billion-valuation-302791103.htmlAccounting Talent Shortage Surges — Accounting Todayhttps://www.accountingtoday.com/news/accounting-talent-shortage-surgesEx-PCAOB Regulator Joins AI Audit Startup Oath Targeting 80% Automationhttps://thefinancestory.com/ex-pcaob-regulator-joins-ai-native-audit-firm-oathKPMG Exploring Start-Up Deals in Silicon Valley to Counter AI Threat — Financial Timeshttps://www.internationalaccountingbulletin.com/news/kpmg-exploring-start-up-deals/KPMG Sets 75% AI Usage Target with New Dashboard, Employees Flag It's Easy to Game — Business Insiderhttps://www.aol.com/articles/kpmg-now-dashboard-where-consultants-154532433.htmlAmazon Shuts Down Internal AI Leaderboard After Employees Inflate Usage via Tokenmaxxinghttps://www.hcamag.com/us/specialization/hr-technology/amazon-shuts-down-ai-leaderboard-after-tokenmaxxing/577189KPMG Australia CEO Andrew Yates Resigns Amid Whistleblower Scandalhttps://www.internationalaccountingbulletin.com/news/kpmg-australia-ceo-andrew-yates-resigns-amid-whistleblower-scandal/Trump Administration Drops $1.8 Billion Anti-Weaponization Fund — Todd Blanche Testimonyhttps://www.cnbc.com/2026/06/02/doj-fund-trump-todd-blanche.htmlBessent Says He Is Performing IRS Commissioner Duties Amid Trump Tax Settlement Scrutinyhttps://www.cnbc.com/2026/06/03/bessent-irs-commissioner-trump-tax-settlement-doj-fund.htmlNeed CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring The Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast: http://cloudacctpod.link/Over...

Die Folge, nach der Sie gefragt habt, und ein gutes Stück früher als geplant. Seit dem 7. Juni 2026 gilt die EU-Frist zur Entgelttransparenz. Die meisten reden über Compliance. Die eigentliche Frage ist: Was bedeutet das für Ihre nächste Gehaltsverhandlung?Jan Nordh ordnet die neue EU-Entgelttransparenzrichtlinie aus der Marktperspektive ein, praktisch, nicht juristisch. Warum die Regel Verhandlungsmacht Richtung Kandidat verschiebt, warum Deutschland die Frist verpasst hat und bis voraussichtlich 2027 hinterherhinkt, und was das für euch trotzdem schon heute ändert. Im Zentrum steht der Teil, über den im Sales kaum jemand konkret spricht: die variable Vergütung. Wichtig dabei: Provision, Bonus und OTE sind von der Regel ausdrücklich erfasst, fixer und variabler Teil müssen sogar getrennt berichtet werden. Der eigentliche Hebel ist deshalb nicht die Base, sondern die Frage, wo im Vertrieb die Ungleichheit wirklich sitzt: in Territorium, Accounts, Quota und Ramp.Die fünf Kernpunkte der Richtlinie in einfachen Worten, und was sie praktisch bedeutenWarum der Wegfall der Gehaltshistorie-Frage euren größten Verhandlungsnachteil beseitigtWarum im Sales die Ungleichheit nicht in der Base sitzt, sondern im variablen TeilDie richtige Frage im Gespräch: ist das die Base oder die On-Target-Earnings?Für IT-Vertriebsprofis, Enterprise Account Executives, Sales Leader und alle in Cybersecurity, Enterprise Software und AI im DACH-Raum und in den Nordics. Stand Juni 2026.https://www.nordh.de

My guest today is Alex Sacerdote, founder of Whale Rock Capital Management.  Whale Rock is a technology focused investment firm that manages more than $17 billion across hedge fund, long only, and hybrid strategies. Over the past three years it has been one of the best performing hedge funds, compounding at roughly 44 percent a year. Alex invests through a single lens that he has refined over twenty years. He looks for technology S-curves, durable competitive advantages, and underappreciated earnings power.  This conversation is a tour through how he applies that framework right now. We start with his highest conviction position, which is Anthropic, and use it to work through the entire AI stack from chips to models to applications.  Please enjoy my conversation with Alex Sacerdote. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠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. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠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. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like The Best (00:00:00) Welcome to Invest Like The Best (00:02:29) Alex Sacerdote (00:03:08) Anthropic: Highest Conviction Position (00:13:23) Investing in Private Markets at Scale (00:19:08) S-Curves: The Full Framework (00:25:08) When to Buy Tech Companies (00:30:20) Identifying the Leader from the Pack (00:34:04) Anthropic & OpenAI's Competitive Moats (00:37:31) AI's Threat to Enterprise Software (00:43:18) Network Effects in the Agent Era (00:44:22) The Hardware Renaissance: Chips & Infrastructure (00:53:56) Why So Few Investors Get This Right (00:55:36) Key Risks to the AI Bull Case (00:57:47) The Application Layer (00:59:40) How AI Is Changing Research at WhaleRock (01:02:53) The Role of Investor Networks & Idea Sharing (01:03:40) Building a Multi-Product Firm (01:07:58) WhaleRock as a Learning Machine (01:09:15) The Kindest Thing

Pastor Levi and Lisa talk about Ruth 1:16 and how Commitment Becomes Real at the Exit Ramp. This is an episode of Pearls & Swine on the Evangel Houghton Podcast from Evangel Community Church, Houghton, Michigan, June 9, 2026.

El año 2026 se ha consolidado como un periodo marcado por importantes debuts en los mercados bursátiles. Entre ellos destaca el de SpaceX, que apunta a convertirse en la mayor salida a Bolsa jamás registrada. A este movimiento se sumó recientemente Anthropic, y en las últimas horas ha sido OpenAI quien ha dado el paso, presentando de forma confidencial su solicitud ante la Comisión de Bolsa y Valores para iniciar su proceso de cotización pública. A este grupo de compañías tecnológicas se une ahora Perplexity, ampliando el conjunto de empresas que buscan protagonismo en el mercado financiero. No obstante, su estreno no será inmediato, ya que su director ejecutivo, Aravind Srinivas, ha confirmado que la compañía planea salir a Bolsa en 2028. Perplexity se posiciona como un motor de búsqueda basado en inteligencia artificial que, al igual que otras herramientas similares, responde a preguntas formuladas en lenguaje natural para ofrecer información relevante al usuario. A diferencia de los buscadores tradicionales como Google o Yahoo, este tipo de plataformas priorizan la interacción conversacional y la personalización de respuestas. En el caso de Perplexity, uno de sus rasgos distintivos es su apuesta por la transparencia, ya que muestra claramente las fuentes utilizadas para generar sus resultados. Sin embargo, tanto esta empresa como sus competidores deben vigilar de cerca el crecimiento de rivales internacionales, especialmente el avance de DeepSeek desde China, cuyo uso está aumentando de forma notable en Estados Unidos. El crecimiento de DeepSeek ha quedado reflejado en informes recientes, como el de la empresa Ramp, donde lidera la adopción entre proveedores de software. Mientras tanto, Perplexity atraviesa un momento financiero sólido, con un incremento significativo de ingresos y una base de más de 100 millones de usuarios activos mensuales. Aun así, no ha estado exenta de polémicas, ya que medios como CNN o The New York Times han cuestionado sus prácticas, acusándola de reproducir contenidos sin autorización y de facilitar el acceso a información protegida por muros de pago.

Welcome back to the Bar Exam Toolbox podcast! This episode is part of the series in which we demystify the shift from MBE to NextGen multiple-choice questions. Today Lee walks through four questions on negligence -- two in classic MBE style and two in the NextGen format. What differences can you expect between the two exam versions? Find out now! In this episode, we discuss: Question 1: Negligence per se (MBE) Question 2: Causation (MBE) Question 3: Causation (NextGen) Question 4: Issue-spotting (NextGen) Study tips for multiple-choice questions RAMP study tool Resources: https://barexamtoolbox.com/ramp (https://barexamtoolbox.com/ramp) Podcast Episode 316: Spotlight on Torts (Part 1 – Negligence) (https://barexamtoolbox.com/podcast-episode-316-spotlight-on-torts-part-1-negligence/) Download the Transcript (https://barexamtoolbox.com/episode-351-listen-and-learn-mbe-vs-nextgen-multiple-choice-negligence/) If you enjoy the podcast, we'd love a nice review and/or rating on Apple Podcasts (https://itunes.apple.com/us/podcast/bar-exam-toolbox-podcast-pass-bar-exam-less-stress/id1370651486) or your favorite listening app. And feel free to reach out to us directly. You can always reach us via the contact form on the Bar Exam Toolbox website (https://barexamtoolbox.com/contact-us/). Finally, if you don't want to miss anything, you can sign up for podcast updates (https://barexamtoolbox.com/get-bar-exam-toolbox-podcast-updates/)! Thanks for listening! Alison & Lee

Eric Ries of the Lean Startup joins Nick to discuss The Hyper-Scaler CEO Whisperer and Founder of the Lean Startup Movement on Incorruptible Startups, Building to Thrive and Survive, and Creating a Governance Fortress. In this episode we cover: The Concept Behind "Incorruptible" The Story of Saul Price and FedMart The Governance Fortress and Legal Structures The Role of Mission-Driven Companies The Case of Novo Nordisk Advice for Founders The Importance of Mission-Driven Entrepreneurship Eric's Approach to Advice Guest Links: Eric's LinkedIn Eric's X Eric's Newsletter  Eric's Podcast The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

In this episode, we examine several developments that may be shaping technology and capital markets. We first discuss recent price action in bitcoin and explore potential factors behind the latest market decline, including futures market positioning and the implications of Strategy's recent decision to sell a small portion of its bitcoin holdings. We turn to SpaceX, reviewing Morningstar's recent valuation analysis, its financial position, and discussions of its potential path toward S&P 500 inclusion following its anticipated IPO. The conversation also covers Ramp's latest $750 million funding round at a reported $44 billion valuation and what it may signal about investor appetite for fintech and enterprise software. Finally, we discuss OpenAI CEO Sam Altman's new game show initiative and its intersection with AI, media, and consumer engagement. Chart of the week: Morning Star's SpaceX Valuation Analysis and Compute Capacity Remember to Stay Current! To learn more, visit us on the web at https://www.morgancreekcap.com/morgan-creek-digital/. To speak to a team member or sign up for additional content, please email mcdigital@morgancreekcap.com Legal Disclaimer This podcast is for informational purposes only and should not be construed as investment advice or a solicitation for the sale of any security, advisory, or other service. Investments related to the themes and ideas discussed may be owned by funds managed by the host and podcast guests. Any conflicts mentioned by the host are subject to change. Listeners should consult their personal financial advisors before making any investment decisions.

Binnen enkele dagen barst het grootste WK voetbal uit de geschiedenis los, maar achter de schermen is de strijd om de macht al begonnen. De bal wordt een cynisch geopolitiek wapen. Kijk alleen al naar het feit dat aartsvijand Iran gewoon meedoet en minstens drie poulewedstrijden op Amerikaanse bodem speelt.Wat deze vijf weken in de VS, Canada en Mexico echt angstaanjagend maakt, is de onvermijdelijke escalatie tot één grote, gepolariseerde Trump-show. Maarten van Rossem en Tom Jessen leggen bloot waarom dit toernooi de boeken in zal gaan als een grote politieke gijzeling. Kijk deze podcast hier met beeld

This week's Department of Know is hosted by Rich Stroffolino, with guests Robb Dunewood, host, Daily Tech News Show, and David Cross, CISO, Atlassian. Get the show notes here. Missed the live show? Check it out on YouTube. The Department of Know is live every Friday at 4:00 p.m. ET. Join us each week by registering for the open discussion at CISOSeries.com. Your team just added its 67th AI tool. And unfortunately, also your 67th security blind spot. The good news: The Vanta Agent works like a GRC engineer in the background, finding every app your team uses, scoring the risk, and drafting fixes for you. Vanta is the platform used by over sixteen thousand fast-moving companies like Ramp, Cursor, and Harvey who are shaping the future with AI, AND staying ahead of AI risk. Get started at vanta.com/headlines. 

Chinese cybercrime group sets record pace Cisco warns of critical Unified CM flaw with PoC exploit code Hackers spied on a stock exchange executive's Outlook mailbox for five months Get the show notes here: https://cisoseries.com/cybersecurity-news-chinese-cybercrime-group-cisco-cm-flaw-cisa-faces-changes/ Huge thanks to our episode sponsor, Vanta Your team just added its 67th AI tool. And unfortunately, also your 67th security blind spot.   The good news: The Vanta  [rhymes with Santa] Agent works like a GRC engineer in the background, finding every app your team uses, scoring the risk, and drafting fixes for you.   Vanta is the platform used by over sixteen thousand fast-moving companies like Ramp, Cursor, and Harvey who are shaping the future with AI, AND staying ahead of AI risk.   Get started at vanta.com/headlines. 

What I learned from reading Steve Jobs in Exile: The Untold Story of NeXT and the Remaking of an American Visionary by Geoffrey Cain. Made possible by: Ramp: https://ramp.com Axon by Applovin: https://axon.ai/founders Vanta: https://vanta.com/founders

Google released Gemma 4 12B, a multimodal model that runs locally on 16GB devices. TSMC's CEO warned chip supply won't meet demand for years. Ramp raised $750M at $44B, and Anthropic says 80%+ of its merged code is now Claude-authored. Google releases Gemma 4 12B, an 11.95B-parameter unified, encoder-free open multimodal model that can run locally on devices with 16GB of VRAM or unified memory (VentureBeat) Public First: 26% of Americans support increased data center construction, the lowest share among 15 large countries, such as Brazil, Japan, the UK, and Canada (FT) Sam Altman and Dario Amodei are among the signatories on a public letter urging improved tracking of synthetic DNA that could be used in AI-developed bioweapons (Wired) TSMC CEO C.C. Wei says the company won't be able to fulfill the demand led by US customers even as more capacity comes online in the US over the next few years (Bloomberg) Corporate spending management platform Ramp raised $750M at a $44B valuation led by Iconiq, Singapore's GIC, and the OTPP, taking its total funding to $3B (Bloomberg) Anthropic details its progress toward recursive self-improvement, and its implications, and says 80%+ of the code merged into its codebase is authored by Claude (Anthropic) Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, Alex Pardo reconnects with Dan to dig into the financial and strategic reality of his 28,000-square-foot storage facility under contract for $2.625M. This is part 3 of a multi-part series, and the conversation gets raw and unfiltered as they work through the deal's tightest challenge: Dan's initial miss on revenue ramp timing and how it impacts his cash flow projections and partnership structures. Alex uses this live deal walkthrough to unpack the critical thinking required before committing capital and equity to a first storage facility. It's messy, it's real, and it's exactly how serious operators need to evaluate opportunities before pulling the trigger.   You'll Learn How To: Understand revenue ramp dynamics and why projections don't happen overnight Evaluate whether a deal is worth equity and capital when returns are below market expectations Structure deals with debt and equity partners to manage cash flow gaps Identify when an interest rate or term change becomes a caution flag in a deal Design a facility exit strategy before you sign the purchase agreement Run conservative, likely, and best-case scenarios without falling into best-case bias Know the difference between doing a deal for experience and doing the right deal for returns   What You'll Learn in This Episode [00:00] Alex and Dan discuss the three-part series on Dan's 28K sq ft facility deal under contract [01:10] The critical oversight: revenue doesn't jump immediately when you raise rates, it ramps slowly [02:00] How a 2-3 person per month net move-in creates negative cash flow for 5–10 months [03:29] Dan's mixed emotions: value of the first deal vs. whether the juice is worth the squeeze [04:01] Equity structure options: 40% equity with 8% preferred return vs. 12% interest-only with smaller equity [05:41] Projected returns: 9–11% cash-on-cash over five years, annualized 17–18% (below market expectations) [06:37] Alex's philosophy: first deal doesn't need to be a home run, but it has to be a base hit with low risk [08:05] Alex's cautionary tale: his early deals in certain markets he wouldn't repeat, but bar was lower because he was learning [09:24] The decision framework: enough due diligence to confidently move forward or walk away with reason [14:15] Where community homework and market analysis become invaluable in deal evaluation [16:03] Revenue ramp isn't a light switch: it's a slow burn that models must account for with conservative assumptions [16:49] Conservative, likely, and best-case scenarios: don't make offers expecting everything goes right [17:02] Going back to the seller after due diligence to renegotiate price, terms, or structure [17:25] Interest rate sensitivity: if 70–80 basis points breaks the deal, it's a yellow flag [18:34] Partnership scenarios: 40% equity vs. 20–30% equity depending on your time and value contribution [19:15] Exit strategy before entry: you determine how you exit, and rarely do you buy and operate forever   Who This Episode Is For: First-time storage investors evaluating their first deal and unsure if the numbers work Operators with a property under contract trying to decide between partnerships, debt, or walking Investors who've been analyzing deals but haven't pulled the trigger and need a reality check Deal makers questioning whether their first facility has to be a grand slam or just a win Real estate operators learning the difference between deal experience and deal returns Anyone struggling with confidence on deal evaluation, market selection, or partnership structures   Why You Should Listen: This episode does something most storage content doesn't: it shows you the real conversation a smart operator has when a deal is tight, promising, but not yet perfect. Alex doesn't tell Dan "do it" or "don't do it." Instead, he walks him through the thinking process—how to weigh risk, returns, equity dilution, and the value of your first facility against the need to protect your capital and time. The key insight here is revenue ramp. It's the single detail that shifted Dan's deal from "looks good" to "needs more work." In self-storage, you don't buy a 60% occupied facility at a certain price, make some operational improvements, and suddenly it's 90% occupied next month. It takes time. Every month you're adding a few units, pushing rates on the existing base, and slowly building to your pro forma. If your financing doesn't account for that reality, your deal can go negative cash flow for longer than your capital can sustain. The broader lesson is this: your first storage deal should absolutely get you on base. It should teach you how to find, evaluate, underwrite, and operate a self-storage facility. But it shouldn't be a financially reckless trade just to check the box. Do the first one right, and you'll be confident to repeat it faster. Do the first one wrong, and you might be out capital, confidence, and momentum.   Follow Alex Pardo here: Storage Wins Podcast — storagwins.com Facebook — Storage Wins Community (join the group for continued learning and peer support) Instagram — @alexcpardo YouTube — Storage Wins   Doing your first storage facility is a big decision, and the temptation to move fast is real. But as Alex reminds Dan, there's no rush. You're not trying to do a deal for the sake of doing a deal. You're trying to do the right deal at the right time with returns that actually work. If you're ready to evaluate your first storage opportunity with clarity and confidence, head over to storagwins.com/call to schedule a free discovery call with Alex and explore whether self-storage is the right next move for you. The only thing standing between you and your goals is action.

On this special segment of The Full Ratchet, the following Investors are featured: Navin Chaddha of Mayfield Eric Byunn of Centana Growth Willy Schlacks of EquipmentShare We asked guests to discuss the most visionary founder that they've worked with and what makes them so special. The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

Welcome back Pauper fam! This week, Derrick Smith returns for another very fun episode where we dive into the Elves deck, how it works, and how to play against it. We also dig into Thomas' testing with the new version of Jeskai Ephemerate and discuss some options and play patterns to consider. Special shoutout to Robert White and Devin Northcutt for their commentary excellence. Thank you as always for listening!Join our Discord! https://discord.gg/kdvSavFkpzCheck out our YouTube channel: https://www.youtube.com/@CommonGroundMTGExample Elves Decklist: https://mtgdecks.net/Pauper/elves-decklist-by-kokoloko3435-2968349Thomas' Current Jeskai Decklist: https://moxfield.com/decks/9PB0xyFmCECc8_c-2-FTjgDerrick's Win-A-Box Coverage VOD @ Infinity Games: https://www.twitch.tv/videos/2784656139Michael's Artwork: https://www.facebook.com/share/1Ead2jrtQU/?mibextid=wwXIfrSponsored by: Game Knight (Columbia TN) The premier LGS in the Middle Tennessee area! Check out their upcoming events and order cards for local pickup here: https://www.gameknighttn.com/Upcoming Pauper Events:Every Tuesday @ Game Knight in Columbia TN - Weekly Pauper League feeding into an Invitational alongside Just Roll With It Games' (Spring Hill TN) Pauper League!Check out our Discord's #events channel for more events and information!June 27th - Court of Commons Yearly @ Enchanted Gaming Emporium, Murray KY - https://topdeck.gg/event/court-of-commons-yearly-get-boltedJuly 12th - NYC Pauper League's "PauperGenesis" @ Baltimore, MD - https://melee.gg/Tournament/View/409325 - 30 seats just added!The 4th Common Ground Cup! July 25th @ Game Knight, Columbia TN! $2k+ cash prizes! 100 capacity! Information, Registration, Hotel Block Reservation, and Live-Stream Links can all be found here: https://linktr.ee/commongroundcupNorth Carolina-Area Listeners: Check out the Piedmont Pauper League @ Dragon's Hoard, Greensboro NC! 6 monthly tournaments culminate in a grand prize: travel stipend and entry into CGCup4 this summer! Their FINAL event for the season is June 13th and registration is open now: https://www.spicerack.gg/events/3216328The Cascadia Pauper Circuit presented by Pauper PNW: www.PauperPNW.org Next event is June 13th!Nashville-Area Thursday Pauper League @ Middle TN Gaming in Bellevue: https://www.facebook.com/p/Middle-Tennessee-Gaming-61567309793600/Any questions or feedback for us? Email us at: commongroundmtgpod@gmail.com 

Law enforcement cracks down on illegal streamers The European Commission releases digital sovereignty plan The startup costs for US cyber force Get the show notes here: https://cisoseries.com/cybersecurity-news-illegal-streamers-eu-digital-sovereignty-cost-of-a-cyber-force/  Huge thanks to our episode sponsor, Vanta Your team just added its 67th AI tool. And unfortunately, also your 67th security blind spot.   The good news: The Vanta  [rhymes with Santa] Agent works like a GRC engineer in the background, finding every app your team uses, scoring the risk, and drafting fixes for you.   Vanta is the platform used by over sixteen thousand fast-moving companies like Ramp, Cursor, and Harvey who are shaping the future with AI, AND staying ahead of AI risk.   Get started at vanta.com/headlines. 

My guest today is Dara Khosrowshahi, the CEO of Uber. Before Uber, Dara ran Expedia for thirteen years. We start with why he took this job in 2017, and a big part of that story is Daniel Ek, who told him that life is not about happiness, it is about impact. We talk about what the chaos felt like on day one, and how his family leaving Iran when he was nine shaped the way he handles pressure today.  We spend most of our time on autonomous vehicles and Uber's role as the demand aggregator in a world of physical AI. Dara explains why Uber is a supply-led company, what it will take to win, and why he expects many winners in AVs rather than one.  We also discuss Uber's $10 billion in free cash flow, the push toward a single app for everything, and what he has learned from Allen & Co, Barry Diller and Reed Hastings. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠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. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠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. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:29) Intro to Dara Khosrowshahi (00:03:37) How Daniel Ek Convinced Dara to Take the Uber Job (00:06:54) Bringing Order to Chaos (00:09:20) Managing Stress as a Leader (00:11:22) The Chip on His Shoulder (00:12:53) Parenting Lessons (00:17:01) Mandate for AI Adoption (00:21:21) Uber's Role in Physical AI (00:22:48) Winning the AV Demand Race (00:27:41) Partnering vs. Competing with Waymo (00:32:05) AV Success Unlocks New Markets (00:35:09) Why Drones Haven't Arrived Yet (00:36:27) Regional AV Rollout Differences (00:37:35) Uber Eats International Winning Formula (00:39:44) Key to Aggregating Supply Well (00:44:34) Adding Hotels to Uber Platform (00:50:46) Lessons in Marketing at Scale (00:52:59) Apps vs. AI Agents in Seven Years (00:54:08) What Dara Learned from Barry Diller (00:56:52) What Dara Learned from Allen & Co (01:00:09) Buybacks vs. Growth Investing (01:04:17) Lessons from Reed Hastings (01:05:49) The Kindest Thing

Everyone says they are one-shotting workflows with AI. We brought on the guy who can tell us what's actually happening in middle-market private equity companies. Kyle Roemer, Head of Data & AI at Accordion, has a unique view because his firm advises over 350+ private equity clients. He can see what's real and what's hype, and Accordion has the Ramp data to tell the difference. Kyle walks Devin through the rapid changes over the past year, function by function, so you can decide if you're ahead or behind. One prediction: the Office of the CFO will go through the biggest revolution over the next year, which they believe will "Make Finance Fun Again!" Kyle Roemer is the host of Accordion's podcast "AI & PE: The Future of Value Creation"  For more about Accordion visit accordion.com and reach out to Kyle and his team at ai@accordion.com. Also check out Accordion's latest AI white paper: "AI in PE: Ahead of the market, behind the curve" in partnership with Ramp to see where AI adoption stands

Russia claims officials' surveillance Project Glasswing access expands CISA flags two-year-old Oracle flaw Get the show notes here: https://cisoseries.com/cybersecurity-news-russia-claims-officials-surveillance-project-glasswing-expands-cisa-flags-two-year-old-oracle-flaw/ Huge thanks to our episode sponsor, Vanta Your team just added its 67th AI tool. And unfortunately, also your 67th security blind spot.   The good news: The Vanta  [rhymes with Santa] Agent works like a GRC engineer in the background, finding every app your team uses, scoring the risk, and drafting fixes for you.   Vanta is the platform used by over sixteen thousand fast-moving companies like Ramp, Cursor, and Harvey who are shaping the future with AI, AND staying ahead of AI risk.   Get started at vanta.com/headlines. 

Meta AI hands over Instagram account access Dutch police dismantle huge botnet RedHat packages get backdoored Get the show notes here: https://cisoseries.com/meta-ai-hands-over-instagram-access-dutch-police-dismantle-botnet-redhat-packages-backdoored/ Huge thanks to our episode sponsor, Vanta Your team just added its 67th AI tool. And unfortunately, also your 67th security blind spot.   The good news: The Vanta  [rhymes with Santa] Agent works like a GRC engineer in the background, finding every app your team uses, scoring the risk, and drafting fixes for you.   Vanta is the platform used by over sixteen thousand fast-moving companies like Ramp, Cursor, and Harvey who are shaping the future with AI, AND staying ahead of AI risk.   Get started at vanta.com/headlines. 

A couple of weeks ago I recorded my first ever episode in front of a live audience (at Ramp HQ in NYC)

Palo Alto GlobalProtect VPN auth bypass flaw now exploited in attacks ChatGPT share links used to host fake outage pages to deliver malware Federal audit reveals NIST's NVD problems Get the show notes here: https://cisoseries.com/cybersecurity-news-globalprotect-vpn-exploited-chatgpt-share-links-exploits-feds-criticize-nist/ Huge thanks to our episode sponsor, Vanta Your team just added its 67th AI tool. And unfortunately, also your 67th security blind spot.   The good news: The Vanta  [rhymes with Santa] Agent works like a GRC engineer in the background, finding every app your team uses, scoring the risk, and drafting fixes for you.   Vanta is the platform used by over sixteen thousand fast-moving companies like Ramp, Cursor, and Harvey who are shaping the future with AI, AND staying ahead of AI risk.   Get started at vanta.com/headlines. 

What if the next five years of your career isn't defined by which AI you use, but by who you're working with?In this episode of KP Unpacked, KP Reddy and Nick unpack the quiet revolution happening in management consulting. OpenAI just launched a deployment company and acquired a consulting firm. Anthropic is backing enterprise AI consultancies. PE firms are partnering with AI-enabled consultants and offering equity instead of hourly fees. The result? Three tiers of value capture emerging: billable hours (worst talent), risk-based fees (middle tier), and equity models (where the best people go). If you're still getting paid by the hour to do AI transformation work, you're in the bottom tier.But the deeper insight is about career trajectory. KP argues the next five years aren't defined by how good your Claude skills are. They're defined by who you're sitting next to. Are you in a firm where Opus 4.8 launching makes everyone's Slack light up with memes and excitement? Or are you somewhere people still think AI is a threat? The gap between those two environments is the gap between relevance and obsolescence. The conversation also unpacks skills files as potentially employee-owned IP (not company-owned), why structural engineers still double-check software calculations in Excel despite working for billion-dollar firms, and why Zero's training program spends two-thirds of its time on mental models and thinking frameworks, not AI mechanics.Key questions answered:Why are OpenAI and Anthropic launching consulting practices and partnering with PE firms?What are the three tiers of value capture in AI consulting (billable hours, risk fees, equity)?Where does the best consulting talent go: hourly billing or equity models?Do you own your skills files, or does your company?Should companies make employees sign IP agreements for marketing coordinators building AI workflows?Why do structural engineers still double-check software calculations in Excel?What's Zero's training curriculum focused on: AI tools or thinking frameworks?Why does ambition and optimism matter more than technical AI skill?How should you choose between working at a forward-leaning AI firm versus a traditional one?What happens when Opus 4.8 launches: does your team's Slack light up or stay silent?Why would you sell a $250M/year AI consulting firm when you're banking $50M annually?What's Ramp tracking now: token spend by industry?If you're deciding between firms based on AI adoption, wondering whether your skills files are actually your IP, or trying to figure out whether billable hours still work in an AI-enabled consulting world, this episode will make you realize the technology matters less than the ambition and optimism of the people around you.Listen now.

My guest today is Dan Loeb, the founder and CEO of Third Point.  Dan started Third Point in 1995 with a few million dollars, and today the firm manages over 24 billion across equities, corporate and structured credit, venture, and insurance.  He is best known for his activist work at companies like Sotheby's, Sony, and Yahoo, and for the public letters he has written to boards over the years. What I find most interesting about Dan is how much his approach has evolved across thirty years.  He came up as a credit and event-driven investor at Warburg Pincus and Jefferies, built Third Point, then layered in quality investing, thematic technology investing, and now a very large credit business that sits alongside the hedge fund. We cover how he thinks about the AI stack and the companies inside it he believes matter most, the difference between good and bad governance, what FTX taught him about due diligence, the Sony and Sotheby's stories, and the power of writing. Please enjoy my conversation with Dan Loeb. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠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. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠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. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:29) Dan Loeb (00:03:21) Mental Models Information Overload (00:06:50) Dan's Identity as an Investor (00:11:24) The End of Classic Event-Driven Investing (00:13:52) Evolving Strategy Over 30 Years (00:17:48) Return Opportunities in Today's Market (00:21:12) Sources of Alpha for Fundamental Investors (00:22:10) Good vs. Bad Governance (00:26:17) Writing as an Investing Tool (00:27:29) The Sotheby's Story (00:30:04) Activism Opportunities Today (00:31:03) Third Point's Evolution to 60% Credit (00:36:10) Dan as Sole Portfolio Manager (00:38:09) Value Investor Perspective on Today's Market (00:39:23) Investing Outside the US (00:40:33) The Sony Activism Story (00:43:59) Lessons from 30 Years of Investing (00:46:26) Danaher and Operational Excellence (00:48:48) Building the Insurance Liability Business (00:51:19) The FTX Story (00:53:07) Leading a Team Through Uncertainty (00:54:29) Where Third Point Is Most Contrarian (00:56:22) What Makes a Great Analyst Today (00:58:12) The Next 10 Years (01:00:24) The Kindest Thing

n this special segment of The Full Ratchet, the following Investors are featured: David Ulevitch of Andreessen Horowitz Jake Saper of Emergence Capital Sandesh Patnam of Premji Invest Each investor highlights a situation where they decided not to invest, why they passed, and how it played out. The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

Produced by Foundersuite (for startups: www.foundersuite.com) and Fundingstack (for emerging manager VCs: www.fundingstack.com), "How I Raised It" goes behind the scenes with startup founders and investors who have raised capital. This episode is with with Andrei Serban of Console, a San Francisco-based startup that provides an AI-powered IT Service Management platform that automates routine internal support requests and IT tasks directly through platforms like Slack and Microsoft Teams. Learn more at www.console.com In this episode, we discuss the acquisition of Andrei's previous company, Fuzzbuzz, by Rippling and he shares tips for managing the exit process. We then discuss what Console does and why he started the company. Following that, Andrei shares the story of raising capital from Thrive Capital, DST Global and prominent angels, how he ran a really tight 2 week process, how he used AI and an Investor Memo in the process, tips for who to target at a VC fund, why he likes to hire ex founders, and more. Andrei is a repeat guest of the show -- to catch the original episode when he was building Fuzzbuzz, click here: https://soundcloud.com/user-2586856/ep-106-how-i-raised-it-with-andrew-serban-of-fuzzbuzz Console has raised $29M from Thrive Capital and DST Global, with backers including Ramp's founders, Box CEO Aaron Levie, and Palo Alto Networks CEO Nikesh Arora. How I Raised It is produced by Foundersuite, makers of software to raise capital and manage investor relations. Foundersuite's customers have raised over $21 Billion since 2016. If you are a startup, create a free account at www.foundersuite.com. If you are a VC, venture studio or investment banker, check out our new platform, www.fundingstack.com

The new AIEWF website is live! CFPs close in 2 days and we will run our first New Engineer Orientation this weekend, get your tickets booked ASAP as they -will- sell out. Take the AI Engineering Survey and get >$2k in credits and free AIE WF tickets!One of the central tensions in the agents industry is that even while there are major decacorn agent labs like Sierra, Decagon, Notion and Cursor being built up, it is also true that it has never been easier to DIY agents, with a plethora of agent frameworks like LangGraph and Pydantic and Flue, and managed agents from Anthropic and Gemini and Amazon. There has been a wave of companies building their own background agents from Shopify to Stripe to Paradigm to Razorpay, and even Cognition's friends Ramp have built their own coding agent with other friend Modal.You'd think Cognition might feel a bit threatened, but they're not - even after all this, they were way oversubscribed for the $1B Series D they just announced:Walden Yan, coiner of context engineering and Chief Product Officer/Cofounder of Cognition, invited OpenInspect's Cole Murray to talk about why the Devin is in the Details.Full conversation live on the pod today: In retrospect, async agents were the most AGI pilled bet you could make in 2024 - the models weren't good enough yet to vibecode, and people didn't trust AI enough to let it rip, nobody (including early Cognition) was sure about the form factors. Now it is obvious:* The first wave of AI coding tools made the developer faster but remain heavily in the loop. Copilor and Cursor's tab autocomplete are prime examples However, the workflow was still heavily centered around and bottlenecked by the developer's local workflow: a developer in an IDE, watching the model, accepting or rejecting changes, and pushing code one interaction at a time.* The second wave was local agents: Claude Code, Windsurf, Cursor's agents pane: first one and increasingly many terminals all running concurrently.* The current Age of Async Agents points to a different future focused more on agent orchestration which drives end-to-end development.According to previous guest Steve Yegge, there are finer-grained 8 levels to agent adoption, but we have collapsed it into three.As Cursor's Michael Truell put it in The third era of AI software development:Cursor is no longer primarily about writing code. It is about helping developers build the factory that creates their software. This factory is made up of fleets of agents that they interact with as teammates: providing initial direction, equipping them with the tools to work independently, and reviewing their work.The agent should not sit solely inside the developer's flow. It should be setup to work in the background so that you can give it a task, a repo, a machine, a shell, a browser, tests, memory, and review loops to go do the work somewhere else.In less than a year, the sentiment has shifted from avoiding multi-agent systems:to suggesting approaches that actually work:From coining “context engineering” to building the infrastructure behind Devin's 7x PR growth and jump from 16% to 80% of commits across Cognition repos, Walden Yan has had a front-row seat to the background-agent shift. In this episode, Cognition co-founder and CPO Walden Yan joins swyx alongside Cole Murray, creator of OpenInspect, to unpack why everyone is building their own Devin, what changed after the December 2025 model inflection, and why “spec to pull request” is now becoming a real production workflow.We go deep on the architecture of background agents: harness-in-the-box vs out-of-the-box, why Devin separates the “brain” from the machine, why repo setup is still one of the hardest problems, why Docker is not always enough, and how full VMs, snapshots, scoped secrets, GitHub bots, Slack integrations, and video-based testing all fit together. Walden and Cole also dig into memory, MCP limitations, multi-agent orchestration, AI code review, SRE auto-triage, PMs shipping code from Slack, Windsurf 2.0, hybrid frontier/sub-frontier systems, and the real failure mode of uncontrolled vibe coding: your codebase regressing to your worst engineer.And as agents eat software… and software eats the world… you can draw the conclusion on what is next:We discuss:* Why the engineering world is waking up to background agents and cloud agents* The December 2025 model inflection that made spec-to-PR workflows practical* Devin's 7x merged PR growth and rise from 16% to 80% of commits* Why Cole built OpenInspect as an open-source background-agent system* The economics of $20/seat agent products and why monetization is tricky* What Cognition actually sells beyond Devin: infra, onboarding, integrations, and adoption* Harness in the box vs out of the box, and why architecture matters* Why Devin separates the brain from the machine for security and permissions* Repo setup, scoped secrets, Docker Compose, and agent-ready dev environments* Why full VMs matter when agents need to run real applications and test them* Android, macOS, Windows, nested virtualization, and machine-specific agent work* Why testing is much harder than “computer use”* Screenshots, video verification, and the “I know it works” merge moment* GitHub UX, Devin Review, AI reviewers, and agents responding to PR comments* Why MCP alone is not enough for first-class Slack and enterprise integrations* Memory, Knowledge, skills, Claude.md, and why retrieval is still unsolved* Devin's auto-generated memories and the challenge of memory pruning* Always-on agents as permanent PMs for issues, tickets, and product areas* Sub-agents, meta-Devin management, and what multi-agent systems actually add* Why pure auto-merge vibe coding breaks down after about two weeks* AI code smells, lint rules, reward hacking, and Semgrep for agent-written code* GitAI, inline context, and preserving the “why” behind code changes* Local testing, mock servers, older codebases, and preparing companies for agents* Windsurf 2.0 and the handoff between local foreground agents and cloud background agents* SRE auto-triage, support workflows, and agents as first responders* PMs, marketing, and non-engineers creating pull requests from Slack* AI agent budgets, $1k-$5k per engineer spend, and hybrid frontier/sub-frontier systems* The rise of autonomous coding factories and who Cognition is hiringWalden Yan* X: https://x.com/walden_yan* LinkedIn: https://www.linkedin.com/in/waldenyan/Cole Murray* X: https://x.com/_colemurray* LinkedIn: https://www.linkedin.com/in/colemurray/* OpenInspect / Background Agents: https://github.com/ColeMurray/background-agentsTimestamps00:00:00 Introduction00:00:43 Why Everyone Is Building Their Own Devin00:01:57 Devin's 2025 Ramp: 7x PR Growth and 80% of Commits00:03:49 OpenInspect and the Rise of Open-Source Background Agents00:07:59 What Cognition Actually Sells Beyond Devin00:09:56 Background Agent Architecture: Harness In vs Out of the Box00:12:08 Separating the Brain from the Machine00:14:07 Repo Setup, Secrets, Docker, and Full VMs00:19:13 Why Testing Is Harder Than Computer Use00:22:40 Video Verification and the “I Know It Works” Merge Moment00:23:19 GitHub UX, Devin Review, and AI Code Review00:25:42 MCP, Slack, and Enterprise Agent Integrations00:28:59 Memory, Knowledge, and Always-On Agents00:36:16 Sub-Agents, Multi-Agent Orchestration, and Meta-Devin00:43:55 Vibe Coding, Auto-Merge, and Codebase Decay00:48:38 Agent Infra, VPCs, Cloud Providers, and Fast VM Restore00:52:25 AI Code Smells, Reward Hacking, and Code Review Systems00:56:10 Making Codebases Agent-Ready00:58:30 Windsurf 2.0 and the Local-to-Cloud Agent Handoff01:01:15 SRE Auto-Triage, PMs Shipping Code, and Agent Use Cases01:04:32 Agent Budgets, Hybrid Models, and Autonomous Coding Factories01:06:51 Hiring at Cognition and OpenInspect Consulting01:07:45 OutroTranscriptIntroduction: Walden Yan, Cole Murray, and Context EngineeringSwyx [00:00:00]: All right, we're in the studio with Walden Yan, co-founder of Cognition, CPO.Walden [00:00:08]: Happy to be here.Swyx [00:00:09]: Which is a cool title. And coiner of context engineering.Walden [00:00:15]: Although I think there are many people who'd used the terms in various ways beforehand, but I did find that people, both internally and externally, enjoyed the upgrade from prompt engineering or model wrapping into maybe a more thoughtful way to build agents.Swyx [00:00:33]: For those who haven't caught up on that, I have on screen the Don't Build Multi-Agents post, which you should go read on and we might refer to, and Cole Murray, who created OpenInspect.Cole [00:00:43]: Great to be here.Swyx [00:00:43]: So let's talk about it. Everyone is building their own Devins. What's going on?The December Shift: From Handholding Models to Autonomous PRsCole [00:00:51]: So I think the engineering world is waking up to this idea of background agents, cloud agents, whatever you'd like to call it. And I think we saw a shift around the December timeframe of 2025, where the models Opus 4.5 and GPT 5.2, they reached a capability where we moved away from handholding the model and being able to actually more or less autonomously drive the model. And what I mean by that is that we could pretty much go from a specification to a completed pull request, assuming the spec was good enough, with very little friction. And that paradigm alone, I think, changed a lot of how we interact with agents, and opened this world where background agents became more practical.Swyx [00:01:41]: I think for Cole, everyone experienced this in December, but I feel like there was just this increasing ramp, right? There was this moment which was, I think, Sonnet 3.7, where, You guys rewrote Devin in one night or something. So describe 2025 or how it felt from your side.Walden [00:02:01]: In retrospect, we always thought it was ramping up, but then even now, over the last three, four months from today, it's been ramping up even faster. So it's almost funny to be talking about how, big of a leap Sonnet 3.7 was, and honestly, a lot of it was stripping out parts of Devin that were no longer needed with that jump in of intelligence. But I also just think that a lot of the recent leaps, especially, you look at, models like Opus and the latest GPT models, they are reaching levels of autonomy where people are actually finding that they actually can just be hands-off. And people who were once debating, “Oh, do I need to be in the weeds with my model in the IDE? Can I just completely move it off into the cloud?” That's a more serious conversation, and we've seen that in all of our growth charts. Internally there's this funny graph where our usage has, of PRs, our merged PRs, has grown 7X since I forget what it was called.Swyx [00:02:57]: I think Dev, maybe tweeted that. Yes.Walden [00:03:01]: it grew like 7X over, the last, I think it was, two months, three months, something like that. And then you see our engineering headcount growth. It's, gone up by, 10% or something.Swyx [00:03:11]: We were, we were afraid To release this. So this is Devin commit percentages on all Devin repos, was 16% in January and now 80% in March.Walden [00:03:25]: It's a big shift right now. And so it makes sense that a lot of people are now thinking about, buying Devin, but also maybe, trying to build their own and there's Lots of I have a lot of fun building Devin, so I can see why other people would want to build their own cloud agents as well. Matt, well, maybe it's good to hear, what initially inspired you to try to build OpenInspect?OpenInspect: Ramp, Cloud Agents, and Open SourceCole [00:03:49]: OpenInspect came about, through primarily my clients observing how they were using tools like Claude, OpenAI's Codex at the time, and seeing some of the friction that they were having with it. Primarily the Claude was being used through Slack, and a big issue they ran into was that the sessions that were launched were specific to whoever called it via Slack. And so if a PM was the one who invoked the session and they would then go to pass context to engineering can't see the session. And that in itself was a deal breaker because the PM, “Hey, engineering, can you jump in?” But there's nothing to jump in on unless they're copy-pasting out or the single response that came back. And so seeing some of these problems, I had built a similar architecture internally, just to experiment with, test out different ideas as this trend of moving off of localhost was starting to become, And as Ramp released their blog post, I had a lot of the pieces for this already in place, and just thought it would be funny to, see what Claude could do just purely from the blog post. And on my X account, there's actually a thread of where I live tweeted, going through thisCole [00:05:14]: comparing GPT and Claude as both of them are going through it.Swyx [00:05:17]: On the announcement thing or something else?Cole [00:05:19]: right after it got released. We can put it in the show notes. Yeah, it was helpful that I had already knew how to verify the system. I knew what I was looking for. I think Ramp did a great job of really illustrating, the technical aspects of how to build something. It was much more than just like, “Hey, we built a great system.” It was, “And here's how you can build it too.” And so, I resonated a lot with that, just with the problems that I was already seeing, and I thought that, looking around, I didn't really see anything in the open source community that, met this type of system. I think there's a lot that run, in localhost like Superset, Conductor, and many others.But nothing that was actually running in the cloud. And so, I built it, and I thought it was interesting to just open source it and allow anyone to then have a foundation that they can mix and match on top of.The Business of Background Agents: Open Source vs. DevinSwyx [00:06:16]: So literally after Devin was launched was, there was OpenDevin Which became All Hands. I don't know if you tried that orWalden [00:06:22]: I was going to say, one of the things that interested me a lot with OpenInspect was, you didn't try to go make it then something you monetize. There are a lot of, I think, these open source projects would then go and really try to, raise VSwyx [00:06:36]: That's why no OpenDevin. Yeah.Walden [00:06:38]: yeah, and how did you think about that? I thought that was very interesting.Cole [00:06:44]: I thought, and just what I had seen across my clients, was that having a background agent system is going to become a critical infrastructure within their company. And so because of that, I think that I wanted to open source it so that they could fork it and put in whatever customization they wanted. To that question though, I get asked all, “Oh, are you going to raise? Are you going to turn this into a service?”Walden [00:07:08]: I'm sure you've gotten offers.Cole [00:07:09]: but primarily I don't want to do that for a few reasons. One, I think that I don't want to compete for, $20 a seat. I think that is just a really difficult business. I think it's very easy to copy the main pieces of it. Again, I built this fairly quickly. And I think because you are not owning, I guess, the entire stack, it's hard to monetize. You have money being made at the sandbox layer with Daytona, E2b, many other players. You have money being made at the model layer. And you sit in this weird in-between gray area where what are you actually selling? You're selling, I guess, the infrastructure. You're selling, the integrations maybe.Swyx [00:07:55]: let's ask the guy. What are you What are you selling?Walden [00:07:59]: Well, yeah, there's multiple layers to this in practice, and actually it's funny you mentioned the infrastructure, ‘cause when we got started building Devin as well, we had to go figure out how to make the infrastructure as well because,Swyx [00:08:10]: You had to build this two years before everyone else,?Swyx [00:08:15]: Including, the model sideWalden [00:08:17]: It was not, it was not very polished at the start, when we just built it off of raw VMs from cloud providers like EC2, the boot up time was so slow, I think, And especially then, turning off the machines, saving them, and then to be able to bring them back up again when the, when you want Devin to wake up again later. It would just be out cold for like 10 minutes because that's just how long these systems took. They were not built for this repeated down and up usage. And so we actually had to go do all of that. And as a result now, one thing we offer when we go and sell Devin to people is, you don't have to worry about all the compute side of things. We'll make it work. We'll make it work in your cloud if you want it to. But aside from the product, and I want to go into the agents and the tuning of the intelligence part later, but I think a big part of what we do at Cognition as well is to just make sure that your company learns and uses and adopts these coding agents. ‘Cause I think for especially the largest enterprises in the world, you find that there is a lot of people who want to move over to using AI for their day-to-day workloads. But because of the way projects are planned, because, not everyone is literate in using AI in these ways, having a team of engineers who can actually go in and onboard you, set up all the integrations you need, the automations you need to really get to that level of, leverage with AI, is super helpful. And so We do that. We show thought partners to the customers that we work with as well.Swyx [00:09:56]: So let's talk about, architectural stuff. I think that's always, that is something that was the topic of conversation between the two of you. Is this, the mental model that you want to start with or something else? I'll just leave the floor open to you guys.Agent Architecture: Harness in the Box vs. Out of the BoxCole [00:10:11]: I think, maybe we can start here as just a general what are the pieces of a background agent system. And then maybe we can go into some of the nuances of, Decisions that you can make.Swyx [00:10:22]: But I guess I also Like, what, maybe what Walden is saying is the agent is like in this open code box, I guess. Right? This is infra, and then there's, that's the agent. And you had this discussion about whether you put the agent in here or in Out externally. Can you tease that out?Cole [00:10:39]: In a background agent systems, you have a decision to make of where the agent is actually going to run. This is typically described as the harness in the box or out of the box. With running the agent in the box, you're making some trade-offs by doing that. The negative trade-off you're making is primarily security. Because the agent is running in that box, unless you otherwise design it, all of your secrets need to go into that box as well. And given the nature of AI, it can be unpredictable, and you could very easily end up accidentally exfilling your secrets, or other unintended behavior. Now, the out of the box is the idea that we are going to have the actual agent running not directly in the sandbox, and we will have, quote-unquote, the brain of the agent running in some type of worker, control plane. That sandbox then is going to serve as the hands where the brain is basically operating and making tool calls into that environment to manipulate it. I guess other trade-off that you're making between the two systems is that, in my opinion, running it out of the box is much more complex because, you have state that has to be managed, whereas if you're running it in the box, all of the state of that agent is actually in the box, and yes, it's you could persist it elsewhere, but it's all localized and you have less concerns to worry about.Walden [00:12:08]: I think a lot of that, what you mentioned, is why we actually from the start built Devin to what we called separate the brain from the machine. The other thing that this allows you to do is reuse any existing infrastructure you have for dev boxes Perhaps. And so you don't have to worry as much about making a new type of dev box that has all the dependencies the brain needs, as you mentioned, the secrets the brain needs as well. One thing that we've seen some customers run into is, you have a GitHub app and you want Devin, your agent, whatever, be able to interact with GitHub through this application, but then you have different users with different actual permissions. If they are all interacting through the same GitHub app and there's no actual, separation between the system that decides, what it does and the actual secrets on the machine, then you run into an issue where, okay, it's hard to do the separation. But in practice, with Devin, it's much easier because we just say whatever you put on the machine, that is, the scope of basically what the user is free to do, what the agent is free to do. So only put the most scoped secrets on that machine, and then the brain is fully not accessible from the machine. So you don't have to worry about messing with the, any of the most secure parts of the brain if the user is free to do whatever they want with the machine.Swyx [00:13:31]: I was going to just bring, I have this, chart from OpenAI, where I don't know if this is, in the box, out of the box. That is something that they do use to describe it. And then also recently Anthropic did, managed agentsSwyx [00:13:44]: Which is, this is their thing. I don't know. It's all, it's all variations of the same pattern, right?Cole [00:13:49]: So this would be out of the box.Swyx [00:13:51]: Which, is preferable for them because it's less work?Cole [00:13:56]: I would say it's more work.Swyx [00:13:58]: It's more work?Cole [00:13:58]: But it, in my opinion, it is the better architecture of the two. It's just, you're taking on a bit of complexity by doing that.Repo Setup, Docker, and VM-Based Development EnvironmentsWalden [00:14:07]: One thing I've not seen a lot of other players do well is how do you manage what's actually on the box? And this can be complex for many reasons. Let's say you have a big repository that's changing and updating a lot with changing dependencies. How do you make sure that the working environment of the agent actually stays up to date, has all the credentials it needs to, let's say, run the app and test it, and all the things you want your autonomousSwyx [00:14:34]: So a repo setup.Walden [00:14:35]: Exactly. So in, internally At Cognition, we call this repo setup.Cole [00:14:39]: The hardest part ofWalden [00:14:40]: It's been a perennial problem since the start of the company, of how do we help people get this set up? Because not everyone just has, working cloud environments working out of the box. And do you find this to be a common problem withSwyx [00:14:53]: How do you solve it?Walden [00:14:53]: Your clients?Cole [00:14:54]: This is a very common problem, and through my consulting, this is a lot of what I help teams do. A lot of teams don't really have great developer environment setups, if any. A lot of the times it's, “Go talk to Bob and get the secrets,” and that obviously doesn't work when the agent needs to actually set this up. And so a lot of that, most teams are using Docker Compose or some type of microservices. And so for theSwyx [00:15:19]: Even in prod?Cole [00:15:20]: Not in prod. With the OpenInspect, you are using this primarily to interact, and make code changes. There is other use cases, but you can hook, whether through CLI, MCPs, other tools, you can then hook that into your production systems primarily for, SRE type use cases. But you are not, necessarily, trying to test your prod internal microservice through the system.Walden [00:15:48]: And you mentioned Docker Compose. I think one direction we saw some of our friends take early on was, using Docker containers as the level of abstraction for their models. There's lots of reasons, I think, why Docker containers are not great. One thing is, Docker container's not really a true security boundary, for one. But the other is, if you are running real applications, a lot of times those applications use Docker, and then you have to think about Docker in Docker, which is, really weird. And so I think part of, the really hard challenge of getting VMs to work, why did we do that? Well, it was because we realized that you actually needed, full VMs to be able to do these types of things. And especially nowadays where there's actually value in running the application and clicking around and sending you screen recordings of these things. The value just, keeps adding on top of that. But it is a decision I see people run into when they try to build their own systems, is, “Oh, do we, in addition to this, do we put the agent in the machine or out of the machine? Do we use Docker? Do we use something else?” What do you recommend people nowadays?Cole [00:16:57]: I think Docker is a good solution for maybe not running the agent, but running your infrastructure, because that is more or less the same setup your engineers are probably already using. If they're not, then I don't know what they're using. But they're probably already using Docker Compose.Swyx [00:17:14]: I've always had a small candle for web containers. I don't know if you guys have tried them before.Swyx [00:17:19]: To me, they were, supposed to be like Docker Light.Cole [00:17:22]: Is it?Swyx [00:17:22]: I don't know.Cole [00:17:22]: No, I haven't tried it. But yeah, I think any environment that you've set up that is a good experience for your developer naturally lends itself to being easy to set up for the agent. And once you figure out that local developer story, you've more or less solved the agent in a sandbox, environment setup. OpenInspect does have hooks as well, where you can, run a setup SH script that will pre-install everything. You can then pre-snapshot that build so it starts instantly, and then there is a second hook to actually then, restore the state of the sandbox when it comes back. And so you can already have all of those microservices running and basically get the same experience that you would on your machine within the sandbox.Testing Agents: Computer Use, Screenshots, and Real App WorkflowsWalden [00:18:08]: Another thing that we've been thinking a lot about is like Different VM service offerings. Have you had customers where they needed like macOS specific VMs or like Windows specificWalden [00:18:20]: VMs?Walden [00:18:22]: There are like many technologies in the world that only work on specific types of machines, right? If you're building a.NET application that has to run on Windows or like, maybe more commonly if you want to build iOS or macOS Does that workSwyx [00:18:32]: Does Commission supportSwyx [00:18:33]: Choices like that?Walden [00:18:35]: The fundamental architecture we do, because we do the separation, it does support, but the actual work in progress is happening right now on these. Another thing that we've actually recently added support now for, it's in beta, is doing Android development. To do that, we needed to support, I think, nested virtualization within our machines because the VM itself is like a, is a virtualized Firecracker instance, and then you had to then run another Android emulator inside. And there's like weird performance issues that like, it, which is why it's like still in beta. We have to think through these problems, but it unlocks a lot for anyone who wants to do Android development.Swyx [00:19:13]: I was trying to find like a reference video for the testing thing. I couldn't find it, but I think you worked on the testing, capability. Why call it testing and not like computer use or I don't know, it's, what's the general Category of problem?Walden [00:19:26]: I think that when people think about the ability of an AI to run your app and test it, I think they actually over-index on the computer use part of it because computer use in my mind is the literal, okay, you want what button you want to click. Can you emit the right coordinates to go click that button? I think testing is actually a really interesting likeWalden [00:19:48]: Problem-solving, challenge for these AIs because if you wanted to do arbitrary testing, imagine you make a change that spans the frontend and the backend, maybe, even some other like even more deeply nested service. To actually test that change, we have to reason through what-- how do you first run these applications to orchestrate with each other with the right version of the code? Then, okay, how do I trigger the feature or how do I make the thing actually happen? And this can get arbitrarily hard, maybe you have to be an admin. Maybe a certain thing has to be feature flagged on. Maybe, you have to like run two sessions and then send us a very specific word into one of them to trigger a specific behavior. And figuring out how do you do that requires a lot of code base context, requires, a lot of orchestration that we've specifically done. And in some cases, we found that you actually, no one frontier model can actually do this full end-to-end task itself.Walden [00:20:42]: We've seen cases where we actually had to orchestrate different frontier models together to solve this problem together. That is where we spend most of our time when we think about this testing problem, not so much the computer use part. Computer use for what it's worth has gotten a lot better with recent models and it's made that part of the job certainly easier.Swyx [00:20:58]: Especially with like even 4.7, that they released yesterday, apparently like way better in terms of the vision stuff, which is going to be encompassing computer use.Walden [00:21:08]: Having evals for all these as well is something that like takes a while to build up. And having the evals be right is tricky as well. Do you ever see like, clients who are building their own agents have to start standing up evals to make sure things don't regress?Swyx [00:21:25]: Not so much evals in the traditional sense, but specific to the testing part that has just gone in. I just added support for screenshots And in theory you can also do video. I need to put in a plugin to do that. But they do show up natively, and it was a very heavily requested feature, especially after Cursor's recording came out. I think that was very enlightening for everyone of like, “Oh, this is a very good feature to actually have.”, I think with Devin you guys have had this for a while.Swyx [00:21:57]: Oh, yeah. See how screenshots work. Yeah, I don't know if there's anything, super and not obvious. It's like once what feature to build, you can just prompt it and it Will mostly work.Walden [00:22:09]: I think to Walden's point, though, the computer use is a subset of the larger testing problem, and I think that's very specific to the code base that you're working and it's not something that, out of the box that you could just solve it. The-- you do need the code base context to actually know how to test it. And I think in the case of a background agent system, you fortunately do have that code base locally that what is changing and could then inspect it and use that to drive the model.Swyx [00:22:40]: For those who haven't seen it before, this is an example of how it works. You, after the PR is done, you click testing approved, and then it sends you back a video. What I really like is that it labels, It's very small here, but it actually labels what it's testing. And then it-- and then you actually see the cursor and everything. So I don't know, yeah, the engineering in this, just Whatever you want to show. ‘cause this is like, this is one of those like, oh, few of the AGI moments, right? ‘cause Once I look at this, I actually don't I wish I can just merge inside Of Slack instead of going to GitHub ‘cause I don't need to see the code. I know it works.Walden [00:23:19]: Maybe a new feature in Cursor. Yeah, the annotations at the bottom was also a big difference for me when I, when I added those.Swyx [00:23:27]: It's just like, what am I looking at? What are you trying to demonstrate?Walden [00:23:30]: Exactly. There's a surprisingly long tail of small details that ends up making a big difference for this end metric of like how fast do you actually merge the code in. One experience that we spent a lot of time tuning early on was what is the right experience on GitHub for these tools. Because I think, most tools out there when you build the agent, you'll think about, oh, it'll create the PR for you. We try to take that a step further and say, “Oh, what if we actually made sure you could interact Devin, with direct Devin directly on GitHub?” And so we made sure that you can comment on GitHub, and Devin would actually receive those comments and address them back. But there's actually quite a bit of tuning you have to do here because you can imagine that actually like-We recently have Devin Review, for example. Devin Review will post comments on his own PR And then Devin has to then goGitHub Workflows: Devin Review, Comments, and PR AutomationSwyx [00:24:23]: He answers his own comments, which is Really loopy. So like, yeah, I like that it just updates here that it's, that I have commented But usually it's just me saying like, “Hey, merged, fix any merge conflicts.”Walden [00:24:37]: The, so when Devin fixes his own comments, you might be scared that, oh, maybe I'll infinite loop. But we've put a lot of work into making sure it doesn't, both by making sure that the comments are high signal, but also that the agent is thoughtful about what comments it immediately goes and tries to fix, and what comments it's like, “Wait a second, I think you're wrong.” Actually, that's one of my favorite moments is when Devin tells me that I'm wrong, when I try to get it to do something different. But tuning that behavior, actually makes a big difference in terms of how useful the actual GitHub experience is.Cole [00:25:06]: I think to touch on that as well, I think having the AI reviewer integrated into the system is a critical part of this background system. OpenInspect does have that. It has a GitHub code reviewer that you can control the prompt. It does do comments as well. It doesn't do them automatically yet. The capability is there, but it's not fully used.Swyx [00:25:27]: So you have to ask for it?Cole [00:25:28]: you do, yeah. You can tag it on GitHub, and then whatever you named your, GitHub bot, it will then follow up on it. It will then, if you have merge conflicts or whatever you have asked it to resolve, it will then resolve it, but it doesn't do it automatically yet.Integrations: Slack, MCP, and First-Party Agent InterfacesWalden [00:25:42]: Well, I'm curious, what is, the most common thing that people end up requesting, that they still need on top of OpenInspect when you help them go implement it?Cole [00:25:52]: I think a lot of it comes down to actually integrating it into the company. It's one thing to have the background agent system set up, but if it isn't actually integrated into your larger ecosystem, it isn't that useful. It is useful to be able to kick off sessions, but what we really want to be able to do is hook it into all of our other systems, whether that is the production database with read-only credentials, the logs, a Confluence or internal knowledge-based system. I think that is where I see the huge leap for companies, and that can be a challenge for companies as well who are maybe not familiar with exactly how to approach it, especially if they're in environments that have more compliance type things where, access control can be pretty big and how do you deliberately think about these problems, I find to be, one of the problems that comes with a system like this.Walden [00:26:46]: The thing we found is So, MCPs, obviously it has been like this, really big explosion of, oh, you can go, integrate it with all these different things. But to actually get the integration right and the and get the right experience, oftentimes we found that we had to go build our own ad hoc things. I think Slack is a great example of this. You could give your agent a Slack MCP and okay, it can post messages back to you on Slack. But we actually use Devin like a coworker in Slack, and that's how it's been built from the ground up. But to do that, you actually need to, support webhooks that come back, right? And then Devin has to respond in a natural way and then hopefully don't spam your threads too much and annoy the people in your company. So you got to tune that experience just right. Especially when there's a lot of back and forths, we find that we actually have to go beyond the simple MCP integrations in these places.Swyx [00:27:39]: I just pulled up the MCP marketplace. I know this is a Fair amount of work. Is the answer to eventually take first party control of all the top MCPs? Is that theWalden [00:27:48]: I would love a world where you could have something that's more expressive than MCP. That, goes both ways, not just a set of tools, but a proper system that interacts back and lets it Have the right experience with all these interfaces.Swyx [00:28:03]: So there actually is sampling in the MCP spec, but nobody Uses it, right?Walden [00:28:07]: And so I think that's the other part is, actually we found that when the MCP spec starts to get too complicated, it starts to lose its original promise of Being like a simple one-step connect. Now then we have to go figure out how to support all these different variations of things and It starts to look a lot like just building the first party integrations in a lot of these cases now.Cole [00:28:29]: I think it matters, too, how critical it is to your company, right? If this is something that nearly every session is going through, it probably makes sense to own it so that you can make optimizations on top of it Versus just whatever is off the shelf.Swyx [00:28:43]: Awesome. Other than MCPs, what else, sorry, well, I don't know if that's Narrowing in too much on, integrations. But what else? What other elements of building OpenInspect or Devin that you guys really sink on?Memory and Knowledge: What Agents Should RememberCole [00:28:59]: I think, a problem that comes up very frequently is this idea of memories or knowledge base.Swyx [00:29:05]: Oh, boy. How do you solve it?Cole [00:29:08]: so not solved yet, is the short answer.Cole [00:29:11]: it's something, there's a open issue for it, someone asking about it.Swyx [00:29:16]: There's, I, D Wiki hasn't indexed anything about memory yet.Cole [00:29:20]: how I'm seeing it solved across my clients is primarily through skills. I find that skills can be a good gap within that or updating Claude MD, but I think memory as a whole is a pretty unsolved problem, and it is why I've been hesitant to add it. I think there is parts of memory and that can be addressed, but I think as a whole it's a very difficult retrieval problem.Swyx [00:29:44]: Oh my God. RAMP didn't write anything about memory? I see zero search results.Walden [00:29:50]: No. Memory can be quite tricky to get right because it's the retrieval, but also the generation of the memories that can be really tricky. You don't want it to just like Remember very specific details.Swyx [00:29:59]: Walk us through the Devin memory journey because I know there's been a journey.Walden [00:30:03]: the first version of memory that like stuck around for a while was A system we have called Knowledge. And the idea was we wanted it to pick up things over time and not need the user to be proactive about teaching Devin things. So, okay, any time you remind Devin, “Wait, no, that's not quite the way you're supposed to use Git”Like, we actually want Devin to say, “Hey, do you want me to actually just remember this for the future?” And for you to just basically quickly approve or reject and for it to build up over time. ‘Cause I find that, 95%, I think, or some crazy stat like that of the memories that Devin has are all through these auto-generated things. Very few people actually just want to sit down and write big docs on Here's how you're supposed to work with the technology, et cetera. The generation and the retrieval has been something that we've been trying to tune a lot over the years. Generation, you don't want it to remember something like, if you asked one time to like, “Oh, please open as a draft PR,” you don't want to be like, “Oh, everyone forever now should get their PRs as draft PRs.” But you do want some, conveyor. Maybe you want to say like, “Oh, Cole generally likes, things to be created as draft PRs.” Same with retrieval, if you have thousands of these memories, how do you actually make sure they're retrieved at the right time? And that can be quite tricky to do right without exploding the context with a bunch of useful yeah, useless information. Surprising amount of just, eval work to just make sure that, memory is, remains a reliable system as new models come and go.Cole [00:31:31]: Do you have anything that you could share on, memory pruning? And like the temporal aspect of memory?Swyx [00:31:36]: Deleting and forgetting?Walden [00:31:39]: The, today, the, So the things they could do is it could edit memories. And so if your memory used to say like, “Oh, Cole likes to open everything as like a draft PR,” then you can imagine, “No, don't do that.” And then it'll say, “Oh, do you want me to update the memory to be Cole now want everything as, open PRs?” I think that at the same time we don't know if this is going to be the final version of the system. Whatever we have here will probably, translate into the new system that we'll be coming up with. But I think one big difference between two years ago and today is these agents are really good at using anything that resembles a file system natively. And so part of us are, is thinking, “Oh, should we rebuild memories to feel more like a file system that we let the agent navigate on its own?” That's been an interesting exploration. Also similar ideas in the scale space.Swyx [00:32:35]: I am pulling up OpenClaude's memory thing right now. So memory, OpenClaude has like this like daily memory journal thing, right? And you can I mean, that is a file system you can grep through and is a source of truth. I don't know if it's the best. It's probably super noisy, but at least, if you lose something you can discover it or you can apply some, forgetting algorithm to, more ancient memories that don't get recalled again or something. I don't know.Walden [00:33:01]: One thing we've been trying to do to push the boundaries of how you use agents at your company is letting an agent basically have a very similar file, a memory.md or something, and just like be your permanent PM for a specific set of issues maybe. So we have like some Slack channels internally, maybe a Slack channel dedicated to, a specific product like DeepWiki maybe. And you can imagine that, or you want a Devin that never stops, it's just always awake, but it has this like memory dock that it can just maintain for itself about, okay, what are like the number one priorities of what we have to fix and prioritize? Who is responsible for some upcoming work? Maybe they'll even Devin will even tag you on some recurring basis. And so it's been an interesting move to see, okay, how can we actually use Devin for more than just engineering? Can we actually upstream above the engineering process and maybe it's just Devin creating tickets, which then maybe some humans do, but then maybe other Devins do.Swyx [00:34:00]: One of my more fun automations is go research competitors and just suggest stuff to me on a weekly basis. That's the automation. I can't find it right now, but basically it just like, “Look at competitors and suggest things.” “And here are three things that you've suggested that I don't want any more of,” and you just stick that in the prompts. But like I wish actually So for like when I, for example, when I reject a PR, I wish that it updated memory so that I can then just not have to go up, go back and update the scheduled, sync, but anyway, feature request.Walden [00:34:31]: what? We might change it soon. I guess OpenInspect, in the time you've been around, has there been anything you tried to implement but then you had to like undo and like do a different way?OpenInspect Architecture: Webhooks, Control Planes, and Agent StateCole [00:34:41]: Nothing yet, but something that is on my mind. The initial way that I built it was that each of the integrations lives as its own package. And so you have The Slack bot, which is what's handling the webhooks, and then is basically interacting with the control plane. As I'm seeing the system starting to be more integrated, specifically with the GitHub bot integration, I'm considering bringing that all into the central control plane because especially now I want to start, And a request that I'm getting is the ability to monitor, the actual, pull requests being merged, as well as just tracking ofSwyx [00:35:19]: What do I have open?Cole [00:35:21]: What do I have open? How many of these are getting merged? How many comments are showing up? To just understand the health of the system. And so in the case of a GitHub app, you only have one webhook. And so then it's a question of do I put that webhook in that GitHub bot package? That's weird. It doesn't really make sense to live there because that package is more for like the code reviewer. Or do I like centralize it? So that's something that's on my mind of, making that decision. I think the other one we touched on earlier is the harness in the box versus out of the box. I think long term the architecture will eventually come back out of the box. Some of the newer tools that I've added are calling back into the control plane so that you don't have the secrets in the sandbox. And so I think long term I probably will pull the actual, agent out of the box, but I think for now it's fine.Subagents and Multi-Agent Systems: When Parallelism Helps or HurtsSwyx [00:36:16]: Just, a quick question on pulling the agent out of the box. I'm One thing I'm very bullish on this year is agents calling other agents or spawning sub-agents or Whatever you want to call it. Does that make it harder or easier? I can't tell. Because if the harness is in the box, you can just spin up more boxes. If the harness is outside the box, then you're, it's less easy because you are, you have a unicorn pet of a, of a harness that's, living outside the box.Cole [00:36:45]: In theory it would be the same way, right? Whether, one agent has launched many, sub-sessions within it, OpenInspect, for example, can launch sub-sessions and actually create other environments and then monitor them. In the case where it is out of the box, that would basically just be an additional session that's running. And so that session is also running outside of the box. It's running in your worker plane, wherever you're running this. And then you really just have to think about how does your top level agent then interact with it. I do think it can be more complex, just ‘cause again, you have now a more difficult architecture. But I think if you figured it out once, it's probably fine.Swyx [00:37:26]: Well, then I'm just, throwing it open to you in terms of, I call this like meta Devin management. Which is like the, Devin's calling Devins or Devin scheduling Devins or querying trajectories or anything like that. What have you built or unshipped, anything?Cole [00:37:46]: I think one of the surprising things we've seen is that a lot of the ways that, these, separate agents work with each other, and you want them to, parallelize their work, has still mostly followed the same manager sub-agents regime. And a lot of people I think are excited about this world where you have swarms of agents that, talk with each other all over the place. We've actually given Devin an MCP so they can just go arbitrarily message other Devins And create new Devins, et cetera. But I guess, it somehow creates, a really chaotic world in that sense. And so we've still found that most practical use on a day-to-day basis has been one single Devin.Cole [00:38:33]: Figuring out how to segregate the work and get, have other Devins work on it in, a relatively isolated sense, each with their own boxes Not sharing machines, so there's, a very little room for conflict is the regime that you have to create today.Swyx [00:38:50]: I'll call out, the experiments from Cursor, right? This is Wilson Lin's work on Single agent to multi-agent, and you're obviously famously on the side of don't build multi-agent. But they went through the whole thing, only to arrive at, this Which is exactly what Devin has, I think.Cole [00:39:08]: I think there will be a revision to that post at some point AboutSwyx [00:39:12]: Tell us about itCole [00:39:12]: I think multi-agents were very much not at all possible a year ago. You do see more multi-agent experiments today, but you can argue, are they really multi-agents, or are they just just, tool calls,? There are people who, will create sub-agents to go look for XYZ file, XYZ implementation. Has really nice context management benefits because all of the tool calls and tokens that it spends then get collapsed back to just the answer for the main agent. There's a lot of benefits to doing this. We basically have Devin do this with Deep Bookie, make a call out to Deep Bookie, give you back the results, but that feels like a tool call,? It's not like these, two collaborators actually talking back with each, back and forth with each other. But I think the thing that gives me the most bullishness that multi-agents might actually be possible is actually what I said earlier about Devin will actually sometimes tell me I'm wrong and push back, and I think that demonstrates a level of maturity and communication today that makes a multi-agent world possible. One, can two agents who have seen different information come back to each other and actually figure out who is right, what is the correct implementation? They're not just, yes men. Claude, I guess is like, used to just say, what is it? “You're right,” or,Swyx [00:40:25]: “You're absolutely right.”Cole [00:40:26]: “You're absolutely right.” Yeah.Swyx [00:40:28]: The Have you seen, did you seeCole [00:40:29]: The age is overSwyx [00:40:30]: The Codex app troll in Topic? This is the Codex app. Inside of Settings, there's a little, there's a little Easter egg, right? So if you go to, the Themes or Appearance, right? There's all these, color codes, and the top is absolutely, and it's the Topic's colors. Which is such a troll. Anyway.Model Behavior: Pushback, Adversarial Prompts, and Agent SkepticismCole [00:40:53]: I love that Easter egg. Did you discover that yourself?Swyx [00:40:54]: No, it was, someone was, tweeting about it And I was like, I was like, “Is this true?” Because, sometimes people just tweet stuff to, get a rise out of you. But yeah, there you go, in Topic colors.Cole [00:41:06]: Yeah. So yeah, we're out of this regime where, it just says you're absolutely right, and they can have real conversations and real back and forths.Swyx [00:41:13]: You can prompt it as well to be more adversarial or whatever. Yeah. Okay. Yeah, that, I mean, to me, that is more intelligence, right? That is not just something that's, a dumb tool, it's actually pushing back on you I think. Yeah.Cole [00:41:24]: when you mentioned, of course, the blog posts. There was one blog they had where they fed a swarm of agents together and built a browser.Swyx [00:41:34]: That was I think that was the one.Cole [00:41:36]: You can have, likeSwyx [00:41:37]: I think it's the same oneCole [00:41:37]: Creation of it. We found a surprising success of, don't do a swarm or anything, just have one Devin, it does its own context management. Just let it keep running for a while and give it some crazy tasks. I think we asked it to, rebuild, a Windows OS system. And it managed to do it just like, going on for long enough. It'sSwyx [00:41:55]: Was this Andrew's thing?Cole [00:41:58]: there were lots of demos that we ended up not posting, ‘cause at some point we'd just be posting way too much a bunch of, Demos. But I love that because it shows that I think the multi-agent thing still has, a bit of exciting sexiness to it, which is maybe still beyond still, the actual delta it adds to the capabilities of these systems. But it's absolutely the future. I think we're heading in that direction and we can see the progress being made there already.Swyx [00:42:25]: If I were to, make one super minor pushback because I don't feel that confident about it yetCole [00:42:33]: Go for itSwyx [00:42:33]: But I've had Ryan Lopopolo from OpenAI on the pod And he's a super slop cannon, right? Oh my God, that's my coding agent being done. I downloaded this, Peon Ping. I don't know if you guys have heard this. It takes like-, sound packs from popular games like, Command and Conquer and Warcraft, and then it plays it whenever it's done. And so it's like, “Work,” or whatever, “At your command,” or something. Anyway, what I got from the Cursor code base and from Ryan's thing was that there's a slop cannon approach where you try to loosen the single agent's, bottleneck, and I feel like that is, probably an, a very important thing to try to figure out. I don't think anyone's, really solved it. Because then you just have more reviewer slop on top of the agent slop To try to wrangle it all. Ryan will probably very strongly object that I say that he hasn't solved it, but he thinks he's He thinks he's completely solved it. But I think it's still I think it's, very important, ‘cause, that is a bottleneck, right? I feel Devin is slow sometimes Because I'm like, well, yeah, this is very readable and very sensible, but also it is slower than it could be if I just, I want a button to just say, “Just ramp this up 1,000 next parallel, in parallel and just, see what happens,”? And I don't know if that's, feasible at some point in the future.Code Review, Entropy, and AI SlopWalden [00:43:55]: I And we've also run experiments internally where we've basically tried to build entire products, true products that we knew we would eventually ship, but for now, let's try to see if we can do it just by purely, vibe coding on top of each other, auto merge, no code review at all. And then there's this benchmark of how many weeks can you go onto this for Before you say, “We have the trashiest code base.”Walden [00:44:18]: “Let's actually rewrite it from scratch.”Swyx [00:44:19]: Start a new factory, yeah. What'd you find?Walden [00:44:21]: I think we found that the state-of-the-art in December was you can probably, run this for about two weeks. By the end of those two weeks, you'd find that, hey, you want to, change the color of a button. Well, it turns out this button is implemented in, 10 different places, and they, have All these different variations, and oh, you forgot one of them, and actually it's a slightly different color in one spot. And you're like, “Okay, this is too much to work with. Let's actually try to do code review at the same time.” And make sure that we're on top of our software, actually cleaning it up a bit And making sure it's done in a scalable way.Cole [00:44:54]: I think building on that, the idea of, you don't have to look at code, I think is generally a bad idea. And the meme that I have for thatWalden [00:45:03]: What timeline, all right, is Do you think that statement will be true on?Cole [00:45:06]: I think probably for a while it'll be true that you should continue to look at your code. A problem that I see a lot of teams run into that I work with who are embracing AI native, AI first coding, is The meme that I have is that your code base regresses to your worst engineer, because that engineer who is, very gung-ho about AI and is not auditing their code, their pattern starts cementing into the code, and now the AI is referencing their patterns. And so now their if/else block that, is 20 if/elses back and forth, the AI is seeing that as the pattern of how things are done and starts to then exponentially grow this slop. And I find to your point, a pretty good approach to that is having scheduled cleanup, whether by humans or through systems, that are looking for duplication. They then address that. You'll end up with like 12 helpers for how to format a date. And you need to address that, because otherwise it will continue to sprawl.Swyx [00:46:09]: Within balance, I think it's fine to have some duplication, and then sometimes To have garbage collection, right? Yeah. The What I've been, talking about with a lot of engineering leaders is that you want to be very strict about the boundaries between modules, and it's your job as an architect, as a CTO, whatever, to say like, “Okay, here's the hard contract between you guys and you guys. Whatever you do inside this black box is your business. You do whatever. But between these guys, let's be, really damn clear, and any movement must be signed off by a human or me,” or. Then, and like that's that. I don't know if you have any other modifications or advice.Walden [00:46:44]: Well, I guess generally on the topic of, where humans can be useful, I found that ‘cause, some of these, really deep infra problems, sometimes just having a human that just has, really deep expertise can make a big difference. I've actually seen this come into play when actually building agents. So we've had a few friends now, try building their own coding agents, and I think one same problem that I recurringly heard a lot of them run into was this problem of like, “Oh, Grep is really slow on our agents' machines.” And so a lot of them, I assume because they're using AI and they themselves don't have, super deep infra background knowledge, say, “Okay, we're going to go build our own custom Grep index. It's going to be really fast,” and use that as a way around this problem. When we ran into this problem About like, maybe like a year and a half ago when we were, in the early days of building Devin, we obviously didn't have AI then. We just asked our, how to, how to do this. You can just swap out a new Grep index, so.Infrastructure Details: Grep, File Systems, and SandboxesSwyx [00:47:45]: What do you mean you hand-coded Devin? What?Walden [00:47:48]: It's like, can you believe we hand-wrote this code? And we had, our infra people who are really amazing, they were looking into it and they're like, “Oh, what? We realized that actually the root cause of this problem is actually super simple, but like fine-grain detail,” which is that a lot of these virtual machines actually underlying them don't use real file systems. They use these, network file systems where things are actually cached over the network actually in S3. So when you're Grepping, you're actually making network calls Every time you're doing these things, and that's why Grep is extremely slow on these machines. And so again, goes back to, what is all of the crazy infra work that we had to do to actually get these machines working. If you try to do this yourself, there are tons of small details like this, and so we had to eventually go swap out that network file system. ButSwyx [00:48:35]: I think there's a write-up about it, right? Silas did one about the virtual file system.Walden [00:48:38]: Oh, that was a whole other thing. TheSwyx [00:48:39]: Oh, that's a different thingWalden [00:48:40]: The BlockDev file storage formatSwyx [00:48:42]: I'll bring it upWalden [00:48:42]: Which is, a file system format that we built so that the VMs could be spun up and down very quickly. Basically, the intuition behind this is-Imagine you have, a terabyte of disk, and your agent only, wrote, a hundred lines of code on top of that disk. How long does it, say, take to, save and re-bring up that disk? And most systems, because you're not optimizing for this case, it's just, on the order of a terabyte of work because you have to Save all of that and bring it back up. In our system, we try to build a file system that incrementally builds on top of each other. So every time you save and bring the machine back up, you're only doing work that is proportional to effectively the diff in the file system. And so this, shaves off a lot of time in the boot-up process of Devin. I think we This is actually now outdated. We have a newer system inside of Devin. But yeah, there's a lot of tiny details you have to get right here to actually get the day-to-day experience of Devin to be good.Swyx [00:49:39]: It's, not technically agents, but it is agent infra, and when you sell an agent as a company, you sell agent plus agent infra.Walden [00:49:46]: At least the way we do it be And the other The nice thing about having the agent infra being done together is, you We get to deploy Devin in whatever environment we want now. We don't need to wait for some underlying infra provider to also go and support VPC or on-prem or FedGovCloud, for instance. So we can actually go and figure out, okay, since we own the infrastructure, how can we get that set up for you?Cloud Providers: Modal, Daytona, and Enterprise SandboxesSwyx [00:50:12]: Whereas you're Cloudflare dependent.Cole [00:50:15]: so Cloudflare runs the control plane. The sandboxes, Modal is supported. A contributor just added Daytona. E2B is on the roadmap, and I think there's an abstraction in place that if any contributor wants to add a new provider, they can add that in.Walden [00:50:32]: Well, what are, How are the customers you work with Do they generally try to then go set up a contract with another one of these third-party providers? Do they try to do the VMs in-house?Cole [00:50:44]: most of them I see using Modal. I think Modal has a greatWalden [00:50:48]: Shout out Modal.Swyx [00:50:48]: Shout out Modal.Cole [00:50:50]: I think Modal has a great offering. It captures all of the sandbox pieces you need, snapshots being a pretty big piece of that, and given that they also offer GPUs, I think it's a pretty nice offering as a whole.Swyx [00:51:04]: no debate there.Walden [00:51:07]: Modal is great, especially, I think their container offering is, the most natural, and so especially if you are willing to, forego, the full VM requirements Modal is, a really vast place you can spin something up on.Swyx [00:51:20]: Is there a point So Modal's very Python, and I feel like most workload, has really shifted to JavaScript. I don't know if you guys Get the same feeling. So, okay, when I started Landspace and IE and all these things, I was like 50/50 Python and JS, right? That's roughly. I think that's wrong now. I think JS has won. I don't know if you guys Like, I Maybe I'm overstating it, and maybe for cognition, there's, C# and Java and what have you. But for, new greenfield apps, do you feel that Do you get that sense? Does it matter?Cole [00:51:52]: I think that most of the libraries that I see in this space are Python native first, especially in theCole [00:51:58]: Observability space. That said, I think that there is a pretty big appeal of having your entire system in one language. Especially when you have both your frontend and backend communicating, you can have one central type Which is very nice.Swyx [00:52:11]: That's my case against Modal, which is Then you have to run JS. You can run JS inside Modal. It's just, one extra step That, isn't native to the runtime. I don't know ifWalden [00:52:22]: I don't knowSwyx [00:52:23]: Reviews. Do you have numbers? I don't know.Walden [00:52:25]: the one thing I don't like about Python is whenever AI, whenever it writes Python, it always does, the weirdest patterns, andSwyx [00:52:32]: Oh, because it's, mixing two and three or what?Walden [00:52:34]: I think it's something mixing two and three, yeah. The I don't know if you see this. It always tries to do, has attribute on objects as likeCole [00:52:41]: Oh, my God.Walden [00:52:41]: But it's like But that you shouldn't be doing that. It should error if there wasSwyx [00:52:45]: Because it's training on library code?Cole [00:52:47]: I think it's more of, likeCole [00:52:48]: From what I've seen, it's more of, a reward hacking mechanism where it doesn't want to basicallyWalden [00:52:54]: It'll never error.Cole [00:52:54]: It doesn't want the code to fail. And so it Even when it knows it has the attribute, it'll call getattr on a, and for a lot of my clients who have moved towards more autonomous coding, we've put that in as a lint rule That if you do getattr, your pull request is going to fail.Slop Signatures: Comments, Backwards Compatibility, and TypesSwyx [00:53:12]: Ooh, this is a fun topic. Can you tell me more about this? What else is a sign of AI coding that you have to put guards in?Walden [00:53:21]: So we were talking just before this about Opus 4.7. One of the things this new model likes to do is it writes lots of comments. Not like, it'll, comment every line, but it'll write, paragraph, PRDs, on top of every function. But I will say, to its credit, these aren't slop, descriptions like they were before. “Oh, here's what this function does.” It's like, “Oh, here's actually the r

Starting Friday night, May 29, the entrance ramp from southbound I-5 to southbound I-205 at Exit 7 in Vancouver closes until Sunday morning, May 31. All southbound I-205 lanes between the I-5/I-205 split and Exit 36 also close. WSDOT contractor Kerr Contractors Oregon LLC is using the crack, seat and overlay method for pavement repair. https://www.clarkcountytoday.com/news/weekend-paving-work-closes-southbound-i-205-entrance-from-i-5-in-vancouver-may-29-31/ #I205 #I5 #Vancouver #WSDOTTraffic #ClarkCounty #RoadClosure #Washington #PavementRepair #WeekendClosure #TransportationNews ---

Dat Fransen goed zijn in staken, dat is algemeen bekend. Maar dat de nationale ploeg dat tijdens een WK deed, dat was in 2010 zelfs voor Frankrijk een unicum. Hoe het plaatsje Knysna in Zuid-Afrika uitgroeide tot een nationale discussie, een teambus symbool werd voor een werk weigerende selectie en een bondscoach van Les Bleus gedegradeerd werd tot boodschappenjongen. Mart ten Have en Jean-Paul Rison vertellen je er alles over.See omnystudio.com/listener for privacy information.

Originally aired on MTS segment, Monetary Matters, Jack Farley and Max Wiethe speak with Ara Kharazian, Lead Economist at Ramp, about what real business spending data says about AI adoption, why the “SaaSpocalypse” narrative is overblown, and how companies are actually buying and deploying AI tools. They also discuss Anthropic overtaking OpenAI in Ramp's AI Index, token-based pricing, AI productivity gains, and why many legacy software firms may be more resilient than people expect.   Resources: Follow Ara on X: https://x.com/arakharazian Follow Jack on X: https://x.com/JackFarley96 Follow Max on X: https://x.com/maxwiethe Stay Updated:Find a16z on YouTube: YouTubeFind 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.

Reddit's favorite Ticket personality Justin Montemayor takes you on a trip down his totally orignal segment "The Ramp". See omnystudio.com/listener for privacy information.

Welcome back to the Bar Exam Toolbox podcast! This is the first episode of a series in which we demystify the shift from MBE to NextGen multiple-choice questions. Join Lee as she walks through four contract formation questions -- two in classic MBE style and two in the NextGen format. How are they similar? How do they differ? Find out now! In this episode, we discuss: Question 1: Firm offer rule (MBE) Question 2: Pre-existing duty (MBE) Question 3: Pre-existing duty (NextGen) Question 4: Issue-spotting (NextGen) Study tips for multiple-choice questions RAMP study tool Resources: https://barexamtoolbox.com/ramp (https://barexamtoolbox.com/ramp) Podcast Episode 293: Spotlight on Contracts (Part 1) (https://barexamtoolbox.com/podcast-episode-293-spotlight-on-contracts-part-1/) Podcast Episode 298: Spotlight on Contracts (Part 2) (https://barexamtoolbox.com/podcast-episode-298-spotlight-on-contracts-part-2/) Download the Transcript (https://barexamtoolbox.com/episode-350-listen-and-learn-mbe-vs-nextgen-multiple-choice-contract-formation/) If you enjoy the podcast, we'd love a nice review and/or rating on Apple Podcasts (https://itunes.apple.com/us/podcast/bar-exam-toolbox-podcast-pass-bar-exam-less-stress/id1370651486) or your favorite listening app. And feel free to reach out to us directly. You can always reach us via the contact form on the Bar Exam Toolbox website (https://barexamtoolbox.com/contact-us/). Finally, if you don't want to miss anything, you can sign up for podcast updates (https://barexamtoolbox.com/get-bar-exam-toolbox-podcast-updates/)! Thanks for listening! Alison & Lee

Welcome back to the Law School Toolbox podcast! Today, we explain the neuroscience behind our RAMP bar study tool -- which we introduced in a recent episode. We discuss the limitation of working memory, which makes it essential to move legal rules into long-term memory through spaced repetition and scaffolding.  In this episode we discuss: The research and science behind our RAMP bar study tool Scaffolding and why we use three learning tiers Studying through spaced repetition RAMP study mode features and confidence calibration How much information can our working memory hold? Resources: https://barexamtoolbox.com/ramp (https://barexamtoolbox.com/ramp) Podcast Episode 369: Using Spaced Repetition for Your Law School and Bar Exam Studies (w/Gabriel Teninbaum) (https://lawschooltoolbox.com/podcast-episode-369-using-spaced-repetition-for-your-law-school-and-bar-exam-studies-w-gabriel-teninbaum/) Podcast Episode 554: How We're Thinking About NextGen Prep Differently (Plus, Try Our New Tool for Free) (https://lawschooltoolbox.com/podcast-episode-554-how-were-thinking-about-nextgen-prep-differently-plus-try-our-new-tool-for-free/) Download the Transcript  (https://lawschooltoolbox.com/episode-557-this-is-how-your-brain-actually-learns-the-brain-science-behind-our-ramp-tool/) If you enjoy the podcast, we'd love a nice review and/or rating on Apple Podcasts (https://itunes.apple.com/us/podcast/law-school-toolbox-podcast/id1027603976) or your favorite listening app. And feel free to reach out to us directly. You can always reach us via the contact form on the Law School Toolbox website (http://lawschooltoolbox.com/contact). If you're concerned about the bar exam, check out our sister site, the Bar Exam Toolbox (http://barexamtoolbox.com/). You can also sign up for our weekly podcast newsletter (https://lawschooltoolbox.com/get-law-school-podcast-updates/) to make sure you never miss an episode! Thanks for listening! Alison & Lee

Sandesh Patnam of Premji Invest joins Nick to discuss The Downstream Effects of SpaceX, OpenAI, and Anthropic Soaking Up $3T in the Public Market, Who Is Netscape and Who Is Google in the AI Era, and the Impact of Private Credit Redemption Requests on PE and VC. In this episode we cover: Themes and Dynamics of the Current AI Shift Investment Opportunities and Challenges Thesis and Focus at Premji Invest Advice for AI Companies and Public Markets Impact of Mega IPOs on Private Markets Challenges in Private Equity and Private Credit Listening as a Secret Weapon Guest Links: Sandesh's LinkedIn Sandesh's X Premji Invest's LinkedIn Premji Invest's Website The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

Founders ✓ Claim : Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- Kelly Johnson's “14 Points” read like a SpaceX operations manual — 60 years before SpaceX was founded. Kelly Johnson created Skunk Works, which he defined as: “A concentration of a few good people solving problems far in advance—and at a fraction of the cost—of other groups by applying the simplest, most straightforward methods possible to develop and produce new projects. All it is really is the application of common sense to some pretty tough problems.” Kelly Johnson was a great engineer and system builder with genius for organizational design. His autobiography which he wrote when he was 75 years old is full of hard-earned wisdom from his 44 year career. This episode is what I learned from reading Kelly: More Than My Share of it All by Kelly Johnson. Made possible by: Ramp: https://ramp.com Axon by Applovin: https://axon.ai/founders Vanta: ⁠https://vanta.com/founders⁠

Scott Brewer and Kyle Agre are talking hunting, fishing and just about anything you can do outdoors each weekend on Gone Outdoors Radio. This week the pair welcomes Nick Kludt, Minnesota DNR Red River Fisheries Specialist to talk about the fishing opportunities on the tributaries of the Red River. Brad Maczkowicz, coach of the West Fargo Sheyenne and Horace Fishing Teams shares the message that he teaches to his student anglers about ethics at the boat ramp and on the water. Lastly, Bassmaster Elite Angler Bob Downey talks about his recent top ten finish on South Carolina's Santee Cooper Reservoir and how he maintains a sharp edge in competition even when things don't go right. See omnystudio.com/listener for privacy information.

On this special segment of The Full Ratchet, the following Investors are featured: Jon Callaghan of True Ventures Willy Schlacks of EquipmentShare Natalie Dillon of Maveron We asked guests to tell the most important lesson they've learned in their career. The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

#357 | Dave sits down with George Bonaci, VP of Growth at Ramp, to talk about what growth actually looks like at one of the most talked-about brands in B2B. George breaks down why Ramp has no CMO and why he thinks that's a feature, not a bug. He makes the case for attention as the new moat when execution gets commoditized, and shares how he went from hardcore attribution obsessive to betting on stunts with no direct attribution. They also get into Project Glass, Ramp's internal AI tool that reads every Slack channel, preps his meetings, and diagnosed a reporting issue in 15 minutes that would have taken two weeks to investigate. And George shares why he thinks marketers now have two jobs: marketing to humans and marketing to machines.Timestamps(00:00) - - George's background: from biochemist to accidental marketer (07:00) - - How marketing is structured at Ramp (no CMO) (09:15) - - Why brand is the growth lever (13:30) - - AI and the death of functional marketing roles (14:45) - - Ramp's hub and spoke model for AI (16:05) - - Building autonomous go-to-market workflows (17:15) - - How the team responded to going agent-first (20:55) - - The J curve of productivity (22:15) - - Are marketing jobs safe? (24:00) - - Marketing to machines: Ramp's two jobs (25:15) - - Offering $3,000 bonuses to AI agents (28:40) - - Project Glass: Ramp's internal AI tool (34:20) - - Attention as the new moat (36:10) - - How to measure attention without direct attribution (41:20) - - Why taste matters more than ever in direct mail and events (42:20) - - How George went from "measure everything" to betting on stunts Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:Knak - A no-code, campaign creation platform that lets you go from idea to on-brand email and landing pages in minutes, using AI where it actually matters. Learn more at knak.com/exitfive, or check out the MCP server by clicking this link. Vector - A contact-level ads platform that lets you build audiences from actual people on your site, clicking your ads, and checking out your competitors. Learn more at vector.co, and get on the waitlist for their new MCP server by clicking here. Compound Growth Marketing - A full-funnel demand generation agency that helps high-growth cybersecurity, DevOps, and enterprise software companies drive more pipeline through AI SEO, paid media, and go-to-market engineering. Visit compoundgrowthmarketing.com and tell them Dave sent you.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

Kelly Johnson's “14 Points” read like a SpaceX operations manual — 60 years before SpaceX was founded. Kelly Johnson created Skunk Works, which he defined as: “A concentration of a few good people solving problems far in advance—and at a fraction of the cost—of other groups by applying the simplest, most straightforward methods possible to develop and produce new projects. All it is really is the application of common sense to some pretty tough problems.” Kelly Johnson was a great engineer and system builder with genius for organizational design. His autobiography which he wrote when he was 75 years old is full of hard-earned wisdom from his 44 year career. This episode is what I learned from reading Kelly: More Than My Share of it All by Kelly Johnson. Made possible by: Ramp: https://ramp.com Axon by Applovin: https://axon.ai/founders Vanta: ⁠https://vanta.com/founders⁠

If you're making AI decisions, you have to understand where you're getting your intel from.

AGENDA: 00:05:11 — Anthropic freezes secondary sales, requiring board approval for all transfers. 00:10:45 — Why Anthropic is buying capacity from Elon Musk. 00:15:35 — Anthropic's massive $200B revenue commit to Google. 00:18:55 — Goldman Sachs predicts a 24x surge in token consumption driven by agents. 00:31:05 — Will AI labs eat the app layer? The threat to Legal and CX verticals.  00:37:55 — SaaS public markets: HubSpot tanks 18% while Monday.com finds its footing. 00:42:40 — Growth theft: How Clay is commoditizing ZoomInfo's data business. 00:46:25 — Cerebras prices IPO at $150–$160 with a $48B market cap. 00:52:15 — Real Venture Capital: Celebrating the early bets by Foundation and Benchmark. 00:58:30 — Ramp's valuation vs. the Chapter 7 collapse of e-commerce card Parker. 01:06:20 — Success and Sacrifice: Is mental health the price of building a $20B company?  

My guest today is Krishna Rao, the CFO of Anthropic. The center of our conversation is how he navigates the decision around procuring and allocating compute, which he describes as the canvas on which everything else gets built. We talk about what he calls the cone of uncertainty, the three chip platforms Anthropic uses fungibly across Trainium, TPUs, and GPUs, and the daily meetings they run to allocate compute between model development, internal use, and serving customer demand. He explains why the returns to frontier intelligence keep getting higher, especially in enterprise, and how Anthropic thinks about the line between platform and application and why they choose to build their own products like Claude Code. Krishna has such a unique seat watching one of the fastest growing businesses in history, and he is generous in sharing what he has learned since joining the company two years ago. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠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. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠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. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:29) Episode Intro: Krishna Rao (00:03:14) Compute as Anthropic's Lifeblood (00:05:17) Three Fungible Chip Platforms (00:07:31) The Cone of Uncertainty (00:09:08) Competing Ways to Allocate Compute (00:10:36) What Drives Compute Efficiency (00:12:38) Why Frontier Returns Are So High (00:16:32) How Claude Code Writes Its Own Code (00:18:46) Will Talent Become Obsolete? (00:20:07) How Scaling Laws Are Holding (00:21:54) Exponential Thinking (00:23:17) The Layer Cake of Compute (00:26:36) How Anthropic Deploys New Compute (00:27:53) Platform v. Application Layer (00:32:42) Why Model Pricing Has Stayed Stable (00:35:26) Measuring Return on Compute (00:37:22) Working With Chip Providers (00:38:32) How Anthropic's Finance Team Uses Claude (00:41:32) The Jevons Paradox for Labor (00:43:08) Anthropic's Fundraising & Growth Journey (00:47:31) The Exponential Revenue Curve (00:49:02) The Hardest Thing to Explain to Investors (00:52:15) AI's Public Perception Problem (00:55:38) Mythos (00:57:31) Relationship With Government (00:58:51) Inside Anthropic's Culture (01:03:48) The Next Frontier: Virtual Collaborators (01:06:22) How Leaders Scale With a Business (01:10:55) The Biggest Risks to Continued Progress (01:12:09) What Krishna is Excited About  (01:13:45) The Kindest Thing

Google unveiled Googlebook, merging ChromeOS and Android into a unified laptop OS shipping this fall. WhatsApp launches Incognito Chat for private AI conversations. Anthropic's revenue run-rate is on track to hit $50B by end of June, and Anduril raised $5B at a $61B valuation. Google unveils Googlebook, its new laptop lineup featuring a unified OS merging ChromeOS and Android, with devices from Dell, HP, and others coming this fall (ZDNet) Google also unveiled Gemini Intelligence, bundling existing and new Gemini features, including task automation across apps and letting users vibe code Android widgets (The Verge) WhatsApp launches Incognito Chat, an AI chat mode built on Private Processing that Meta says lets users talk to AI without Meta being able to access the chats (Wired) Investor docs: Anthropic's revenue run-rate is on track to hit $50B by the end of June; Ramp says more of its customers now use Anthropic than OpenAI, a first (WSJ) Anduril raised a $5B Series H led by Thrive and a16z at a $61B valuation, up from $30.5B in June 2025, taking its total funding to $6.82B, and could IPO in 2027 (NYT) Richard Socher's Recursive Superintelligence raised $650M+ from GV, Greycroft, Nvidia, AMD, and others at a $4B valuation to pursue "recursive self-improvement" (NYT) Learn more about your ad choices. Visit megaphone.fm/adchoices