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The book and the bench capture what was already known when you connected your sources. The knowledge hub captures what you learn after: every deep dive, every A/B test read, every new definition discovered while doing work. It is where knowledge stops evaporating and starts compounding. This is the surface you spend the most time on once knowledge is stood up, because it grows every time an agent or a teammate does something.

What lives in the hub

As work happens, its outputs are written back as durable artifacts:

Every finding carries its evidence

A finding in the hub is never just a claim. Each one links back through an evidence chain to the task and agent that produced it: the run, the queries, the plots, the reasoning. This is what makes a finding safe to reuse: the next person can see exactly how it was reached and decide whether it still holds.
Treat the evidence chain as the finding’s proof of work. A finding you can trace back to its run, you can build on; one you cannot, you have to redo.

Validation states

Not everything written back is equally settled. Each artifact carries a state, so you always know how much to lean on it:
  • Validated: checked and trusted.
  • Unvalidated: produced by work but not yet confirmed.
  • To verify: flagged as needing a look before anyone relies on it.
You can promote, edit, or retire any artifact, and see which agent and task created it and why it was kept.

Re-scanning knowledge

Work spreads across many tasks and sessions, and the useful result is easy to lose track of. Re-scan pulls findings out of past tasks and back into the hub, so when you remember “last week a run found the five metrics correlated with six-month retention,” you can recover it without hunting through a hundred open tabs.

How knowledge compounds

This is the payoff of the whole module. Because Agent Studio runs agents in parallel, a single effort can launch dozens of investigations at once, and each one produces knowledge. Fifty investigations become fifty findings. Your job shifts from doing every investigation to curating what the fleet produces: keep what matters, validate what is load-bearing, retire what was a dead end.
The hub rewards curation. A pile of unvalidated findings is noise; a curated, validated set is the base every future investigation starts from. Decide what is worth keeping while the context is fresh.
Each kept finding is available to the next engineer and the next agent, which is how the system gets smarter about itself over time, instead of relearning the same things.

Next steps

Best practices

How to curate what compounds without drowning in findings.

Overview

See how the hub closes the loop with the book and the bench.