Developer Runs 48-Hour Self-Correcting LLM JSON Extraction Loop to Fix Schema Errors

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A developer built a two-pass pipeline to address a common problem where language models return nearly valid JSON that fails schema validation at runtime. The system first prompts the model to extract structured fields from plain-text webhook payloads, then automatically feeds any validation errors back to the model for a second correction attempt. Every attempt, including raw model output, is logged to a JSONL file for analysis. The loop ran continuously for 48 hours on a free server using no-cost model access to stress-test where failures occur. The article was disclosed as part of a product outreach effort for MonkeyCode, the platform used to host and run the experiment.

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