Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning
Quick summary
arXiv:2609.38147v1 Announce Type: new Abstract: As agents take on longer and more complex problems, controlling the execution becomes a task in its own right. Each step in the run brings new control choices, like which partial work to build on, whether to start fresh, or when to stop. We introduce agentic meta-reasoning, an inference-time harness that makes these choices an explicit and structured reasoning process. Workers carry out the task-level computation, while a controller consolidates what the run has established, explores next options, assesses what each option is worth under the rema
Key takeaways
- arXiv:2609.38147v1 Announce Type: new Abstract: As agents take on longer and more complex problems, controlling the execution becomes a task in its own right.
- Each step in the run brings new control choices, like which partial work to build on, whether to start fresh, or when to stop.
- We introduce agentic meta-reasoning, an inference-time harness that makes these choices an explicit and structured reasoning process.
Why it matters
This model development creates a new option for users and a new testing obligation for developers. A fixed evaluation set comparing quality, cost and failure behavior is more useful than launch claims.
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