Rewriting multi-agent LLM prompts as pseudocode with assertions, replanning, and comments yields moderate accuracy gains and large token savings in the tests reported here, though some headline numbers are overstated.
smolagents: a smol library to build great agentic systems
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CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs
Rewriting multi-agent LLM prompts as pseudocode with assertions, replanning, and comments yields moderate accuracy gains and large token savings in the tests reported here, though some headline numbers are overstated.