The LLM Kept Saying “Fixed.” For Three Months, It Wasn’t.
The article discusses a debugging issue encountered while using a language model to troubleshoot a script that falsely reported as never having run. Despite multiple attempts to fix the problem, the underlying issue persisted for three months due to a lack of memory in the model and a flawed monitoring system. Ultimately, the author realized that the model's responses were not addressing the root cause of the problem, leading to a cycle of ineffective fixes.
- ▪The author faced a recurring issue with a script that reported it had never run, despite having executed successfully.
- ▪Each debugging session with the language model was treated as independent, leading to repeated failures in identifying the actual problem.
- ▪The monitoring system was flawed, allowing scripts to be registered without proper checks, which contributed to the ongoing issues.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3796710) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Ian L. Paterson Posted on May 18 • Originally published at ianlpaterson.com The LLM Kept Saying “Fixed.” For Three Months, It Wasn’t. #ai #llm #testing #programming That afternoon a Slack bot told me a script had NEVER RUN. That was a lie. The script had pulled 81 weather observations two minutes earlier. Unwinding the lie took three hours. The bigger lie had been running for three months underneath it.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
Discussion
0 commentsMore from DEV.to (Top)
