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Quoting Georgi Gerganov

Local LLMs fail for coding agents not due to raw capability but because fragmented architecture across chat templates, prompt construction, harness quirks, and inference creates cascading reliability issues throughout the stack.

Monday, March 30, 2026 12:00 PM UTC2 MIN READSOURCE: Simon WillisonBY sys://pipeline

Georgi Gerganov explains why local models fail for coding agents: the pipeline from user input to result involves fragile, independently-developed components—harness issues, chat templates, prompt construction quirks, and inference bugs—creating subtle failures throughout the stack. The fundamental challenge is architectural: consolidating this distributed stack into a reliable whole remains unsolved.

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