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Hard Problem: Token Efficiency in Self-Improving Agents Letting an agent reflect on its...

Hard Problem: Token Efficiency in Self-Improving Agents

Letting an agent reflect on its own work sounds great until you see the API bill.

When an agent loops through thinking, critiquing, and fixing its own code, token usage explodes.

If you don't control this at the architecture layer, you're building a science project, not a product.

Self-improving agents need hard guardrails.

Smarter agents aren't just about better answers—they have to make economic sense to run.

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