🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then proactively suggests action items (code changes, evaluators to add) Try it today:

Claude Code and @suno have more in common than you might think: "It's fun to build things, and it's fun to use what you build." AI lets people be creative in almost any domain, from coding to making music. Today on Training Data, @MikeyShulman shares his thesis for why generative AI is the newest form of active entertainment (the next 'gaming'), music as a cultural phenomenon vs creative expression platform, and more. My favorite part was Mikey's explanation of why Suno learns music theory implicitly vs explicitly: "In Western music, there are 12 tones. If you tell the model there are 12 tones, it will only ever produce those 12 tones. You will be forever limited. And if you tell the model there's 200 instruments, those are the only sounds that you'll ever be able to make." The more you constrain a model with what humans already know, the less capable it becomes. By treating everything as pure sound, Suno built what Mikey calls a totally generalized "music-making machine." Such is the power of neural nets.

The quality of animation you can create on your own is truly amazing. We really are just limited by our imaginations at this point. Go tell your story! Made in @runwayml in a few hours and a handful of gens.

Our crowd favorite from last year’s AI Ascent is back for round 2… this time: Robotics The Endgame ♟️ thank you for dazzling us @DrJimFan ! You can see the forest from the trees and are quite the entertaining speaker — a mini Jensen in the making :)

🚀 Introducing the genmedia CLI, generative media directly from the command line. Generate images, video, 3D and audio from your terminal, alongside Claude and other AI agents. • Native terminal workflows • Easy to plug into scripts + pipelines • No dashboards or tab-switching • Installable skills for consistent styles + workflows

Seems plausible people will eventually periodize AI history into: - pre/post AlphaGo (waking up China re: AI + researchers re: deep learning) - pre/post ChatGPT (waking up capital + accelerating commercial competition) - pre/post Mythos (waking up the US federal government)

I think of @SpaceX as having 5 layers Layer 1: Launch Layer 2: Connectivity Layer 3: Compute / hyperscaler Layer 4: Applications / models Layer 5: Other bets (Terafab, Moon, pt to pt, etc) This partnership with @claudeai instantly derisks Layer 3

Yesterday @ElevenLabs announced they'd crossed >$500M ARR. Here's my interview with @matiii from @sequoia AI Ascent a few weeks ago. Mati is a founder who really inspires me. He shares stories about ElevenLabs' history (🇵🇱🇵🇱🇵🇱), the current AI landscape, and his vision for voice and agents (and robots) in the future. 00:00 Introduction 00:49 Poland Dubbing Problem 02:10 Why Audio? 03:52 Monetizing Early 05:17 Building the Audio Stack 07:15 Mati's Wow Moments 10:14 Voice Agents Beyond Support 14:26 Operating an AI Leader at Scale 17:43 Audience Q&A - Future of Voice 24:12 Closing

Narrative violation and great insight from the latest Citadel Securities banger by Frank Flight: "We illustrated back in February that demand for software engineers, the most AI exposed occupation was accelerating higher, which we argued violates the displacement narrative. Indeed the acceleration in software job postings has continued, now up 18% from the inflection point in May last year."

At @sequoia’s AI Ascent last week, @gdb told me something that stuck: in late 2024, AI wrote ~20% of @OpenAI's code. That number is now 80%. We also got into why human attention, not compute, is the real bottleneck in AI-augmented work, plus what it might mean to run an org of 100,000 agents. We’re grateful to Greg for joining us and many of the top founders/builders in AI. You can watch the full video here: 00:00 Intro 00:49 Compute Hunger Explained 02:13 Scaling Laws Mystery 03:31 New Architectures Ahead 04:42 How Close to AGI 06:46 Startup Playbook for AI 09:24 Inside OpenAI with Codex 11:11 Teams and Governance Shift 14:52 Security and Responsible Deployment 25:33 Science Frontiers and Wrap Up

@si_pbc @sonyatweetybird @MikowaiA @YasminRazavi @tszzl @_milankovac_ VPT ( blew my mind back in 2022 so I was very excited to see SI scale up the idea with FDM1, but for knowledge work / computer use. Excited and looking forward to more!

Instead of predicting text tokens, @si_pbc learns to use a computer from raw screen data, predicting the next mouse movement, click, and keystroke from the pixels in front of it. This is the @Tesla FSD approach applied to knowledge work on computer screens. Excited to have not one but two @Tesla_AI goats @_milankovac_ and @karpathy join us on the cap table!

Every year for AI Ascent, @gradypb, @Konstantine and I get to share some perspectives on AI and where things are headed. This year's talk was about the arrival of agents and the race to deploy them across the application layer, and how founders can compete in this crazy intense market ("Get MAD!" Moats, Affordance, Diffusion). 00:00 Introduction 01:10 AI Wave Calibration 01:56 Three Differences of AI 04:28 Inflection Points to AGI 07:06 Building on Top Strategy 07:29 MAD Moats Framework 09:33 Affordance and Diffusion 12:07 Agents Are Here Now 13:46 Agent Stack and Trajectory 21:12 Future of Work and Meaning