Jude Everett

Something I have been thinking about in the AI governance space that I do not see discussed enough: provenance capture is not like most tooling categories.

With most observability or audit tooling, the reasoning is "we should have this so we're better positioned going forward." You can turn it on when the need becomes clear. You lose some history, but the tooling from that point forward is complete.

AI code provenance does not work this way.

The prompt a developer submits to Claude Code exists for a few hundred milliseconds in transit. After the model returns its response and the editor applies the change, that prompt is gone. Git records the diff. Nothing else records the origin by default. There is no reconstruct operation.

Anthropic released Claude Fable 5 today, and it's a bit different from the usual model bump.

It's not a bigger Opus - it's a new tier above Opus, built on the same underlying model as Mythos, the one Anthropic had locked behind a government cybersecurity program since April.

Here s its own version of what it does:

Hello makers, I m Niloy, Product Lead & Researcher at BurnLink. It s been amazing seeing the support and response from the community so far. Today, I wanted to share something interesting about the thinking behind our product what led us to build it in the first place from a psychological perspective and what's the future of BurnLink.