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20:58ENVinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.
13:21ENAdrian Twarog: Giving Enterprise Vibe Coding a Governed Path to ProductionAdrian TwarogA Superblocks walkthrough shows how shared integrations, isolated databases, policy agents and audit logs can bring business-built AI apps under IT oversight.
1:10:12ENOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell AnywayAnime : Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
1:35:29ENUber Burned a Year of Tokens in 13 Weeks. Retrieval Is How Agents WinAnime : Nathan LabenzMongoDB Field CTO of AI Pete Johnson argues that agent performance now hinges on retrieval quality, not on stuffing million-token context windows.
1:13:48ENCarriers Spend $200 Billion a Year. The Money Went Up the StackAnime : Jacob EffronBenedict Evans tells Jacob Effron why analogizing AI to past platforms is a dead end, and why looking at how those platforms actually made money is not.
1:45:59EN87% of Workers Use AI. Only 13% Say the Company Got Better.Anime : Nathan LabenzGlean’s Work AI Index names the missing hours: botsitting, botshitting, and a hamster wheel of polished nonsense.
1:57:56ENA Hundred Million Lines at Twenty Cents Each: Inside Blitzy's Enterprise Coding PipelineAnime : Nathan LabenzCEO Brian Elliott and CTO Sid Pardeshi tell Nathan Labenz how Blitzy turns a giant codebase into a map, then lets thousands of dynamically generated agents ship most of a multi-month project in days.
1:39:17ENAI Already Beats the Median Lawyer. Top Firms Bought the Tools and Left Them UnusedAnime : Nathan LabenzKevin Frazier and Alan Rozenshtein walk through how frontier models are changing legal practice, why billable hours stall adoption, and which new rights and government limits they want next.
1:40:51ENReasoning Models Just Made the Other 80–90% of Enterprise Data UsableAnime : Nathan LabenzSnowflake VP of AI Baris Gultekin on text-to-SQL, RAG, agent design, and why inference has to run next to governed data.
57:37ENThe hot-swap era for models is over, OpenAI's enterprise product chief saysAnime : Jacob EffronOlivier Godement on GPT-5.1, Codex, enterprise harnesses, and the three practices that actually make AI land inside large companies.
1:13:24ENRed Teams Still Land 25% of Attacks. Insurance Is the Brake.Anime : Nathan LabenzAI Underwriting Company co-founders Rune Kvist and Rajiv Dattani tell Nathan Labenz how standards, audits, and insurance could unlock enterprise agents without waiting for a nuclear-style freeze.
50:08EN1Mind's AI Superhuman Now Sources 76% of the PipelineAnime : Nathan LabenzAmanda Kahlow tells Zapier CEO Wade Foster why she tore up the sales org — and why a face on an agent is mostly a trick to get buyers talking.
1:41:34ENChat Is the Universal Interface—and Often the Worst OneAnime : Nathan LabenzAtlassian's head of AI on fighting slop with taste, knowledge, and workflow, and why chat is a terminal, not a product.
1:45:00ENAmerica Holds 45% of the World's Data Centers. Everyone Else Must Build, Buy, or AllyAnime : Nathan LabenzAnjney Midha of a16z maps what “sovereign AI” actually means for companies and for countries that will never own the talent, data, and compute frontier.
1:27:01ENThe $16 Trillion Services Market Is Being Bought, Not Sold ToAnime : Nathan LabenzMarc Bhargava of General Catalyst explains how AI-enabled rollups turn low-margin service firms into compounding, software-like businesses.
38:48ENTask Length Doubles Every Few Months. Nathan Labenz Still Wants Humans in ChargeAnime : Nathan LabenzAt Imagine AI Live, the Cognitive Revolution host maps structured AI agents against autonomous agentic systems—and tells businesses to keep final control.
44:21ENMercor's CEO: Knowledge Work's Next Job Is Writing EvalsAnime : Jacob EffronBrendan Foody tells Redpoint how Mercor turned AI hiring and expert data into a $100 million round — and why he thinks a huge slice of white-collar work will become creating tests for models.
51:08ENThe Transformer Co-Author Who Says Scaling Hit a WallAnime : Jacob EffronCohere CEO Aidan Gomez tells Redpoint that a $100 million model is still an amnesiac genius, and that enterprise AI money is concentrating in support, research, and the back office.
1:05:11ENThe Fake Five-Second Hold: Voice AI Is Already Negotiating With TruckersAnime : Nathan Labenza16z partners Olivia Moore and Anish Acharya walk Nathan Labenz through what is working in voice AI — call centers, coaches, companions — and what still is not.
54:55ENNew Jersey Cut Phone Waits from 40 Minutes to 90 SecondsAnime : Nathan LabenzGovernor Phil Murphy on the state AI assistant, a Princeton hub, and why he wants the best catcher's mitt in the country when superhuman systems arrive.
1:29:02ENShe Never Sees a Row of Your Data. The Answers Still Clear 95%.Anime : Nathan LabenzIllumex CEO Inna Tokarev Sela tells Nathan Labenz how a Platonic industry ontology, trained only on metadata, collapses enterprise software into one conversation.
56:07ENBox Holds 100 Billion Files. Its CEO Says Enterprises Only Move for a 10xAnime : Nathan LabenzAaron Levie tells Nathan Labenz why AI excitement in the enterprise already outruns the early cloud — and why 98% reliability, seat-based SaaS, and incremental savings still will not ship.
1:29:00EN14,000 people applied. Thirty-three got in. The jobs are at Homeland Security.Anime : Nathan LabenzMichael Boyce, director of the DHS AI Corps, tells Nathan Labenz how the largest civilian AI team in the U.S. government is being built — and what it is already shipping.
1:04:54ENHe bet company equity that Transformer would last — then drew an AI map for 12,000 companiesAnime : Jacob EffronDatabricks chief AI scientist Jonathan Frankle tells enterprises when to prompt, fine-tune, or pre-train, and why he still refuses to forecast the next architecture.
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