Verified65% confidenceFactTime unknown
Common methods for constructing Agent Tuning training data include trajectory distillation, self-play, and manual annotation correction
3
Sources
65%
Confidence
Long-term
Relevance
6/3/2026
First Seen
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UnverifiedThe typical development cycle for Agent Tuning is closed-loop: use a strong model such as GPT-4 to get the business workflow running, build training data based on prompts, fine-tune your own model, and finally replace the strong model with the trained model.79% similarUnverifiedPractical prompt engineering techniques in real products include system prompt layering, dynamic prompt injection, automatic selection of Few-shot examples, and using global constraint files such as AGENTS.md to define Agent behavior boundaries.77% similarUnverifiedAgent 遥测指的是运行时采集的模型调用轨迹数据，包括耗时、token 用量、工具调用序列、错误分布等，通常通过 OpenTelemetry 一类框架导出到可观测性平台。75% similar
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