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Meta-reasoning as a way for AI agents to plan their own computation
A thread sharing “Thinking Before Thinking” proposes separating task-solving from decisions about where to spend compute: exploring, building on earlier work, verifying it or stopping.
TLDR
A thread linking to the arXiv work “Thinking Before Thinking” describes meta-reasoning as a way for an AI agent to decide how to use compute while solving a task. It describes a controller that can assess intermediate work and retrieve relevant stored artifacts instead of replaying the full history. The poster claims this approach leads to stronger final outcomes across different models and task domains.
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