Why architecture matters here

Reflection fails without loop bounds (cost + latency), without verifier (self-affirming loop), and without eval (unmeasured value). Architecture matters because these guardrails convert reflection from research demo to product.

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The architecture: every piece explained

The top strip is the core loop. Initial answer generated. Self-critique identifies flaws. Verifier tool — external check like code runner. Revise produces new answer.

The middle row is safety. Loop bound caps iterations. Convergence check stops when stable. Diverse critics from multiple perspectives. Ranking picks best.

The lower rows are ops. Cost + latency — reflection uses more tokens. Eval — did it help? Ops — task fit + budget + governance.

Agent reflection — self-critique + verifier + revise + loop bound + evalagents that improve their own answersInitial answergenerationSelf-critiqueidentify flawsVerifier toolexternal checkReviseproduce new answerLoop boundmax N iterationsConvergence checkstop when stableDiverse criticsmultiple perspectivesRankingpick bestCost + latencyreflection tokens $$Evaldid it help?Ops — task fit + budget + governanceboundconvergediversifyrankbudgetmeasuremeasureoperateoperate
Agent reflection loop with critique + verify + revise.
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End-to-end flow

End-to-end: math problem answered. Verifier (calculator) checks arithmetic; error found. Self-critique identifies where. Revise. Verifier confirms. Return. Eval shows reflection lifts task F1 +8% at 3x cost.