firehose> #llmops

Agent Audition

Before staffing an unfamiliar model into a role in a swarm, qualify it with a gated tryout — a small, representative task with an automated pass/fail gate — rather than trusting it into production on reputation. The framing is hiring: you don't add a worker to the team on the strength of its résumé; you give it an audition on the actual kind of work, with the actual constraints, and let a machine gate decide whether it made the team. This turns "which model is good enough for this role" from an abstract benchmark question into a concrete, task-shaped test the operator controls.

The source (Nate B Jones) had two models he wanted for speed that had never run in his swarm before, so he auditioned them: write exactly five tagline candidates for the book's pre-order page, 12 words or fewer, through a script that automatically rejected cheesy words the author would reject as off-voice. One model passed the whole exercise in 29 seconds; both made the team. The audition's cargo is not just "can it write" — the gate encodes the role's real constraints (count, length, voice), so passing it is evidence the model can be trusted with that role's tasks. It is the staffing-time complement to Model-Tier Routing (which tier runs which role) and to Authority-Independent Verification (which gates the work once the model is on the team).

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