One pattern: let Claude perform long-horizon autonomous work with…
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One pattern: let Claude perform long-horizon autonomous work with self-correction. Claude Managed Agents supports this with outcomes: give Claude a rubric for task completion and let Claude loop until the rubric is satisfied.
Context
Anthropic's Claude Managed Agents can use explicit completion criteria to drive revisions. The developer post describes outcomes as a way to give Claude a rubric and have it keep working toward satisfaction of that rubric.
The platform documentation explains the mechanism: a grader with a separate checks the artifact and sends an explanation of passed and failed criteria back to the working . Revisions continue until success or the iteration limit. Concrete, checkable requirements therefore become feedback for the next attempt, while vague requirements make the grading less reliable.
- context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
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