LLM coding workflow adds a review gate to stop every retrieved method from being implemented

hypergraphr · reddit · 2026-07-29

The author says an MCP-based workflow for decomposing, researching, specifying, and implementing deep-learning systems worked well until the implementation step: the LLM kept combining every method it found.

To fix that, they added a mandatory editing gate between research and code generation. The new step makes retrieved research reviewable, lets humans or the system exclude irrelevant approaches, clarify assumptions, and produce a final spec that reflects the original engineering plan instead of every alternative the model discovered. The takeaway: gating outputs may be essential for reliable AI engineering workflows.

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