用 GPT-6 Astra 一条指令拉起上千个 agent 循环
一份三页操作手册，讲如何用 operator block 和可逆性判断把 Astra 变成并发 agent 集群。
OpenAI just exposed a way to launch 1,000+ agent loops from a single instruction on GPT-6 Astra A 3-page field manual showing how to transform Astra from a conversational assistant into an entire agent fleet, including the FULL OPERATOR BLOCK you drop in once. here is the setup: 1. the 3 action paths Astra uses to classify basically every request (reversible → execute immediately, consequential → complete the work then request approval once, irreversible → halt) and why the real decision point is reversibility rather than complexity 2. the operator block designed around 5 behaviours OpenAI itself flagged: freezing on "can you…", wasting cycles testing tiny changes, returning answers in Markdown, following random instructions buried inside skill files, and delegating less aggressively than intended 3. the effort scale (low / medium / high / xhigh / max, with no "none") plus configuration_update for temporarily increasing reasoning on a single difficult turn while preserving the cache prefix 4. the 3 job patterns that push the model end to end: a research brief backed by auditable citations, a Codex refactor isolated inside a worktree with a passing-test gate, and a computer-use operation with a strict cutoff before anything reaches a customer 5. the edge experiment that reveals where your workflow can run concurrently, alongside the 3 fleet killers: self-confirmation (give the verifier a fresh context), shared-file conflicts (assign every worker its own worktree), and the 272K threshold that can radically change the pricing of the entire request 6. the single Responses call that dispatches 20 workers through an async tool, paired with a verifier that executes the test again rather than relying on the agent to claim completion this is the exact setup:
这条是引用着另一条写的：「长文：把 GPT-6 Astra 搭成 24 小时交易策略引擎」