Agent failures in healthcare often come down to bad data and code lists
urbanistrage · reddit · 2026-07-21
Data problems and agents get messy fast in production
The author works at a startup deploying AI into health systems for early disease detection. Their main issue is not the model, but the pipeline around it: transformed data reaches production and then behaves strangely.
Two recurring failure modes stand out:
- LLMs used to map free-text fields into coding systems sometimes choose the wrong code.
- The root cause often appears to be the set of codes available to the agent rather than the model alone.
The post is essentially a request for best practices: how teams trace agent failures back to changing data or API-collected inputs in dynamic environments, and what the hardest debugging problems are in practice.
Related event: Medical AI Agent Failures Often Root in Data and API Inputs(2 posts)→
More from coding & agent
- Plasma AI Open-Sources Fractal: A Tool for Hierarchical Agent Loops — rohanpaul_ai · 2026-07-22
- Anthropic says Claude Code helped its developers migrate 10 code packages in one month — trq212 · 2026-07-22
- Gemini 3.5 Flash Outperforms GPT-5.6 in Light Coding Tasks — Shick_hydro · 2026-07-22
- DIYing a Flight Stick into an AI Keyboard: A Hardcore Coding Agent Workflow — thorax · 2026-07-22
- Building a Secure AI Agent Gateway: Self-Hosting OAuth for Multiple SaaS Apps — Defiant_Cod_2654 · 2026-07-22
- Rowboat launches as an open-source, local-first AI coworker with memory — ycombinator · 2026-07-22