Agent design is still hard
Read OriginalArmin Ronacher shares lessons from building AI agents, arguing that current agent abstraction libraries aren't worth adopting due to model differences. He discusses challenges with testing/evaluation, introduces 'reinforcement' techniques, and explores how LLM APIs create synchronization problems that might benefit from local-first approaches.
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