Claude Sonnet 4 now supports 1 million tokens of context on the Anthropic API—a 5x increase. Process over 75,000 lines of code or hundreds of documents in a single request.

A bit sad how the GPT-5 launch is going so far, especially after the long wait and high expectations - The automatic switching between models (the router) seems partly broken/unreliable - It's unclear exactly which model you're actually interacting with (standard or mini, reasoning level, old/new) - Router issues probably contribute to many negative first impressions ("GPT-5 is bad"), especially when you can't easily tell which model is handling your requests - e.g. GPT-5 Thinking performs better at writing compared to standard GPT-5 ("think harder" prompts might also help) - I'm seeing lots of complaints about legacy models being removed and usage limits for Plus (and also Free) accounts ("bring back 4o, o3, ...") - Context window lengths aren't clear, nor how many and which exact GPT-5 models ChatGPT uses (standard, mini, new, old) - no indicator of which model is active at any moment - The gradual rollout and current capacity constraints add to confusion, because not everyone can access the new models yet - Mixed-up charts during the livestream provided plenty of free material for chart-crime and vibe-charting posts, which hasn't helped build trust or confidence - And of course, the community had extremely high expectations across all fronts and modalities, as usual I'm hoping improvements in the next hours/days, and today's AMA, can clarify some of these open issues and questions

Anthropic is one of the fastest-growing businesses of all time. @DarioAmodei and I chatted about flying past $5b in ARR, Anthropic's focus on B2B, payback economics of individual models, talent wars, AI market structure, and lots more. And you all said that you all want longer episodes, so this is an hour! Timestamps 00:00 Intro 00:51 What’s it like to start a company with your sibling? 01:43 Building Anthropic with 7 cofounders 02:53 $5 billion in ARR; vertical applications 07:18 Developing a platform-first company 10:09 Working with the DoD 11:13 Proving skeptics wrong about revenue projections 13:14 Capitalistic impulses of AI models 15:44 AI market structure and players 16:56 AI models as standalone P&Ls 20:48 The data wall and styles of learning 22:20 AI talent wars 26:04 Pitching Anthropic’s API business to investors 27:49 Cloud providers vs AI labs 29:06 AI customization and Claude for enterprise 33:01 Dwarkesh’s take on limitations 36:12 19th-century notion of vitalism 37:28 AI in medicine, customer service, and taxes 41:00 How to solve for hallucinations 42:41 The double-standard for AI mistakes 44:14 Evolving from researcher to CEO 46:59 Designing AGI-pilled products 47:57 AI-native UIs 50:10 Model progress and building products 52:23 Open-source models 54:43 Keeping Anthropic AGI-pilled 57:11 AI advancements vs safety regulations 01:02:04 How Dario uses AI