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A reflection agent is an AI agent that evaluates its own outputs and reasoning, identifies errors or improvements, and iteratively refines its work.
A reflection agent incorporates self-evaluation into its workflow. After producing an output — code, a document, an analysis — the agent reviews its own work with a critical eye, identifies potential issues, and iterates to improve quality. This self-correction mechanism dramatically improves output quality compared to single-pass generation.
Reflection can take several forms. Self-critique asks the agent to identify flaws in its own output. Verification uses tools to check correctness — running tests on generated code, fact-checking claims against sources, validating formatting against specifications. Comparative evaluation generates multiple approaches and selects the best one. Iterative refinement applies multiple rounds of critique and improvement, converging on a high-quality result.
The concept mirrors what effective human professionals do: a senior developer reviews their own code before submitting a pull request, a writer revises their draft before publishing. At Agentik {OS}, reflection is built into every agent's workflow. Development agents run and test their code, fix any issues, and verify the fix before marking a task complete. Content agents review their writing for clarity, accuracy, and brand alignment. Design agents evaluate their outputs against the design system. This multi-pass quality approach is a key reason our agents produce work that meets professional standards.
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