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The AI Signal

3 November 2026

TechCrunch AIArticleClaude Watch32m ago

Anthropic warns that it’s very close to RSI capability, aka self-building AI

This isn't speculation or doom talk from outside observers. Anthropic is signaling they've hit measurable progress on capability self-amplification and are flagging the implications now. RSI is the point where the scaling laws that got us here stop applying in linear ways. For builders: this changes how you think about moat and window. For investors: this is the timeline frame for either serious defensibility or commoditization of the model layer. For everyone: this is worth taking seriously as a capability inflection, not as apocalypse.

claude labs rsi

Latent SpaceArticle32m ago

Building Legal Agents When You Can't See the Data - Jacob Lauritzen, CTO of Legora

This is the same piece as Item 2 under a slightly different framing. Legora's core problem is a feature, not a bug: they need eval strategies that work without observing agent behavior. That's a hard technical constraint that applies to any agent handling sensitive data. The techniques they developed probably translate to healthcare, fintech, and government AI work. Worth reading if you're shipping agents in regulated contexts.

agents legora legal-ai

Latent SpaceArticle32m ago

Building AI for Lawyers - Jacob Lauritzen, CTO of Legora

The interesting tension here is between what makes agents valuable in law (domain-specific reasoning over messy data) and what makes them hard to build (you can't see half the work because of client confidentiality). This is a real constraint in regulated verticals that most agent tutorials ignore. If you're building agents for finance, healthcare, or law, this conversation covers the evals and blind-spot problems you'll hit.

agents legora legal-ai

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