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Controlled passes improve a single artifact across revisions, often using explicit feedback from rules, tests, or users. Typical conditions for use: Result quality increases gradually and intermediate states must be preserved; External feedback is readily available. The central trade-off: Improved artifact quality is achieved at the expense of longer runtime…
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Theoretical construct: explains a term, principle, or mental model.
What organizes, connects, or makes decisions possible.
Iterative refinement improves an outcome through repeated passes guided by feedback, rules, or tests.
The idea follows iterative development and optimization methods from software engineering and machine learning. In agentic systems it has been operationalized as a loop of drafting, evaluating, and revising.
An agent or team creates a draft, evaluates it against criteria, and revises the identified weaknesses. The loop ends at sufficient quality, a budget limit, or a defined stopping condition.
Controlled passes improve a single artifact across revisions, often using explicit feedback from rules, tests, or users.
Typical conditions for use: Result quality increases gradually and intermediate states must be preserved; External feedback is readily available.
The central trade-off: Improved artifact quality is achieved at the expense of longer runtimes and potential thematic drift.
The pattern suits text, plans, code, and other testable artifacts. It improves quality with clear criteria, but weak feedback can reinforce errors and the loop needs time and cost limits.
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