Coding agents change what one experienced person can deliver. Over twelve months, a single operator shipped more than 400,000 lines across 1,000 pull requests on a real-time trading platform, with idea-to-merge measured in days rather than weeks. The lesson is not that agents write code. It is that the discipline around them decides whether the output is an asset or a liability.
The studio is a set of named, versioned skills — review round, pull-request review, experiment review, documentation sync — each written to a standard that states the failure it prevents, uses least privilege on tools, and excludes consequential actions from automation. Around the skills sit the gates: architecture decision records, an automated reviewer that re-reviews every commit until its findings converge to zero, CI-exact lint and tests, strict documentation builds, and a committee step for any change to an experiment’s conclusion.
Three things stay human, always: merging, resolving a review thread, and moving anything towards real money or real production. The agent prepares; the person decides. Review convergence per pull request — typically 8 findings, then 3, then 2, then 0 — is the metric that tells you whether the studio is working.
The same pattern transfers to enterprise data teams: agents as a governed gateway to the data platform, read-only by default, cost and row ceilings, journaling, rollback, and an autonomy scale written into every agent sheet — assistant, copilot, supervised, autonomous — so that the human check is a stage, not a sentence.
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