The common failure mode on teams working with AI agents isn’t that the agents produce bad work. It’s that every teammate ends up arguing from a different summary of what the agents actually did — each summary lossy in a different way — and the resulting debate is about the summaries, not the work.
Shared, full-fidelity context dissolves that failure mode. When everyone is reading from the same record of how the work actually happened, disagreement becomes productive again: we’re pointing at the same artifact and disagreeing about what it means, not disagreeing about what it was.
What we mean by full-fidelity
Not a transcript. Not a summary. A structured, queryable record of:
- Every prompt, every tool call, every artifact the agents produced.
- The decisions humans made between agent turns — and the reasoning attached.
- The branches that didn’t ship, with enough of their context preserved that re-entering them later is cheap.
The thing you lose when context is lossy is the ability to disagree well. We’re trying to get that back.