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Sub-agent loop to iterate a VLM prompt against ground truth

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Yun-Ta Tsai
Contributed byYun-Ta TsaiXSource

May 29, 2026

Sub-agent loop to iterate a VLM prompt against ground truth A meta-prompt that spins up sub-agents to iteratively tune a vision-language model's recall and precision against a ground-truth eval set, used for scaling Grok VLM tasks.

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Before running this, curate a small but diverse evaluation set that can be rapidly iterated on. Then use this prompt: "Make a plan to design and execute a task that a) takes input per entry from: <input>, b) generates output per entry to: <output>, c) the ground truth of output: <ground truth>. Launch sub-agents to iterate on strategy to optimize recall and precision against ground truth until both metrics reach <threshold>." Then watch your research agents do the work.

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References

Categories:coding| twitter| vlm-prompting| sub-agents

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