[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-reflection-pattern::en":3,"gloss-cluster-reflection-pattern::en":26,"gloss-next-reflection-pattern::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"reflection-pattern","agents","Reflection Pattern","The reflection pattern has an agent evaluate its own output and revise it before finishing, rather than returning the first draft. After generating a result, the agent (or a separate critic model) checks it against the goal or explicit criteria — 'does this code compile, does this answer cite sources, did I miss a requirement?' — and if it falls short, feeds the critique back in and tries again. This self-critique-and-retry loop, popularized as 'Reflexion,' measurably improves quality on coding, reasoning, and writing tasks because a second pass catches mistakes the first pass makes under pressure. For builders, reflection is a cheap lever: often a single extra 'review your answer against these criteria' step beats reaching for a bigger model. The cost is more tokens and latency per task, so cap the number of reflection rounds and use concrete, checkable criteria — vague 'make it better' prompts tend to spin without converging.","The reflection pattern has an agent check its own output against the goal or explicit criteria and revise before finishing, instead of shipping the first draft.",null,[11,14,17,20,23],{"slug":12,"name":13},"agent","Agent",{"slug":15,"name":16},"chain-of-verification","Chain-of-Verification",{"slug":18,"name":19},"llm-as-judge","LLM-as-Judge",{"slug":21,"name":22},"plan-and-solve-prompting","Plan-and-Solve Prompting",{"slug":24,"name":25},"react-prompting","ReAct Prompting",[27,31,35,38,41,44,47,50,53,56,59,62],{"slug":28,"category":5,"name":29,"updated_at":30},"agent-budget","Agent Budget","2026-08-24T02:46:37+00:00",{"slug":32,"category":5,"name":33,"updated_at":34},"agent-checkpointing","Agent Checkpointing","2026-08-24T02:46:38+00:00",{"slug":36,"category":5,"name":37,"updated_at":30},"agent-handoff","Agent Handoff",{"slug":39,"category":5,"name":40,"updated_at":30},"agent-loop","Agent Loop",{"slug":42,"category":5,"name":43,"updated_at":30},"agent-memory","Agent Memory",{"slug":45,"category":5,"name":46,"updated_at":34},"agent-sandbox","Agent Sandbox",{"slug":48,"category":5,"name":49,"updated_at":34},"agent-trajectory","Agent Trajectory",{"slug":51,"category":5,"name":52,"updated_at":30},"agentic-rag","Agentic RAG",{"slug":54,"category":5,"name":55,"updated_at":34},"computer-use","Computer Use",{"slug":57,"category":5,"name":58,"updated_at":30},"context-engineering","Context Engineering",{"slug":60,"category":5,"name":61,"updated_at":34},"dry-run","Dry Run",{"slug":63,"category":5,"name":64,"updated_at":65},"escalation-path","Escalation Path","2026-08-24T03:30:02+00:00"]