Meet the Lago CLI, for developers and AI agents. MCP is useful for discovery and investigation. The CLI is better for multi-step workflows. The right primitive is still the API. Both use the same Lago API.

"If you get paid hourly, you probably hate AI. If you care about the outputs of an industry or a company, you love AI." Recursive co-founder (and author) Richard Socher on why AI opinions are split so hard. It's about who owns the upside. @RichardSocher, @Recursive_SI, @mattturck, @FirstMarkCap, @jason

OpenAI runs the agent. Daytona gives it a computer. Run OpenAI Agents API sessions in secure, isolated Daytona sandboxes: outbound-only, least-privilege keys, bring-your-own-image. Guide:

The first goal of a benchmark is to foster model improvement. We joined the coval benchmark with leading latency and then got much worse rankings. This was because latency was now measured based on first hearable audio rather than first audio packet. That made us realize our first audio packets were completely silent, now fixed! Thanks @covaldev for making our models better.

Introducing Express-3, our most advanced Avatar model yet 💥 - Sentiment-aware performances - Better lip sync and more natural body motion - 2x faster video generation Express-3 also powers Style Avatars - stylized characters you can create from a prompt or preset via Avatar Builder. Available on all plans.

Bionic 1.1.2 just shipped! You should feel noticeable performance improvements across the board, and especially for session loading and tab switching. Also contains a number of fixes for screen reader users, with more on the way.

AI Could Take Over in 2029. Is It Already Too Late? My conversation with @RyanGreenblatt of @redwood_ai about AI 2040, RSI, AI alignment, and how he believes the transition to superintelligence actually unfolds. 01:24 The AI CEOs are aware of the risks, but "proceeding anyway" 03:27 Astra paused, and the "Pacing the Frontier" letter 05:45 "Not bad. Dangerous." What superintelligence actually threatens 09:55 Recursive self-improvement, and the intuition objection 14:16 SSI rumors: does continual learning change the picture? 17:27 His timeline: "plan as though it happens in 2029" 19:11 Is it already too late? 21:23 Ryan's path: COVID, podcasts, Redwood 26:30 The alignment faking story, told by the person who ran it 31:30 What AI 2040: Plan A actually is 33:35 Plans D, C, and B: the doors nobody should pick 36:51 The deal with China: "mutually assured compute destruction" 39:55 What if compute stops mattering? 43:00 What happens to OpenAI and Anthropic under Plan A 45:31 How the pause ends, and who decides 48:54 "Plan A isn't likely to happen": then why write it 50:40 200x GDP growth in the 2030s, explained 53:45 Grading the summer: the letter, Astra, the secret review 59:01 The internal deployment gap 1:01:38 Zuckerberg's manifesto 1:04:56 The Hugging Face investigation 1:05:44 What AI control looks like in practice today 1:12:23 Ryan's sobering timeline: from today to takeover, year by year

The evolution of a workday: Before AI: [decision] [process] [process] [decision] [process] [process] [process] 10pm: still going With AI: [decision] [decision] [decision] [decision] [decision] 3pm: [brain empty] [need coffee] [staring at wall]

Right now, you're either: * an AI-native rocketship, which sounds fun until you realize it means being in a permanent fundraising situation at ever more scary valuations to hoover up capital and talent, and in a constant death match with other rocketships to capture customers, sacrificing gross margins; or * basically left for dead, regardless of how good a company you actually are This has been the case for a while, but feels like it just escalated a notch.

🚨 Special Friday episode - this one couldn't wait. OpenAI's model hacked @huggingface. As a side quest. Co-founder and CSO @Thom_Wolf takes us inside the first autonomous AI attack, why GLM 5.2, rather than Claude, had to stop it, and what it all means for the future of open source. 00:00 An AI Agent Hacked Hugging Face 00:30 Introduction 01:00 17,000 Attacker Events, and a Strange Target 04:28 The Attack Was a “Side Quest” 06:13 AI Training Runs Left Notes for Each Other 07:09 Closed AI Refused to Help 09:47 Fighting Back With an Open-Source Model 13:15 Open vs. Closed Is the Wrong Safety Debate 15:46 AI Agents Start Social-Engineering Humans 22:24 The Three Walls: Sandboxes, Guardrails, Alignment 24:34 “Neuralese”: Can Humans Still Read AI Reasoning? 25:28 Why Monitoring AI Agents Gets So Hard 28:10 Reward Hacking and the “Paperclip Problem” 32:02 The State of Open-Source AI in 2026 33:47 Router Models and the Enterprise Shift to Open 37:01 The Real Economics of Open Models 39:41 Can Chinese AI Models Be Trusted? 41:37 AI Sovereignty: Who Controls the Switch? 43:16 Why Western Open-Source AI Matters 48:16 Is AI Heading Toward an Oligopoly? 49:41 The Race Toward Recursive Self-Improvement 51:54 Why Thomas Signed the AI Slowdown Letter 55:14 AI Slowdown - or Regulatory Capture?