#1 - the tricky part there is in scenarios from a few AI Native teams. There often are a multiple agents rolling out linked changesets to a bunch of documents on behalf of controlling humans. Eg updating compliance policy, and references and change log and current procedures at the same time.

So changesets have to be atomic across multiple documents and semantic (so that agents can resolve the changes). Weak per-document versioning isn’t enough here.

#4. Nice! Same story, but also virtualizing ripgrep, find and tree (plus MD-aware outline mode). With that setup even agents with weaker local models (eg runnable on DGX Spark) can solve complex tasks in the Agentic Commerce domain.