Agent Teams Need an Operating System
The durable product-builder skill is no longer prompting a single strong agent. It is designing a small operating system for agent work: role split, wakeup logic, shared context, and human review.
The strongest July 3 signal was the cluster forming around multi-agent Codex workflows. Digg surfaced OpenAI commentary on sub-agents, threads, and automations as the practical unlocks. The primary docs make the product direction explicit: Codex can spawn specialized subagents in parallel, reuse thread context across automations, and keep work moving across longer-running tasks. This lines up with the broader market shift from “ask one agent” products to supervised agent workspaces.
Once work spans research, implementation, verification, and follow-up, one giant thread becomes a liability. Context gets muddy, review gets harder, and failure states blur together. Teams that define agent roles and wakeup rules can parallelize safely without losing traceability.
Turn one recurring workflow into a managed agent team. Trigger: backlog item, support issue, deploy regression, or scheduled check. Context: shared objective, repo or artifact scope, acceptance criteria, and prior run notes. Tools: one planner, one executor, one verifier, and one summarizer or handoff agent. Verifier: tests, screenshots, rubric, or policy check. Budget: per-agent runtime, token ceiling, write scope, and max fan-out. Artifacts: branch or diff, run summary, evidence bundle, and next action. Stop condition: all required checks pass and a human can review, or the system stops with a named blocker.
Put it to work 12 minutes
Scored evaluation set
Pick one workflow that currently lives in a single chat and rewrite it as four roles this week: planner, executor, verifier, and reviewer. If you cannot explain why each role exists, you do not need a multi-agent loop yet.
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Use the task above. Record the result and anything you still need to check.
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