Your LLM Is Wrong. Your Codebase Is Why.
The article discusses the concept of comprehension debt in coding and how it affects AI coding assistants. It highlights that errors made by AI models often stem from issues within the codebase rather than flaws in the models themselves. By identifying these errors, developers can improve their code and make it more understandable for both humans and AI.
- ▪Comprehension debt refers to code that is difficult to understand, impacting both human developers and AI assistants.
- ▪Common errors made by AI models include inventing function names, getting parameter types wrong, and using deprecated patterns.
- ▪Developers can use AI confusion as a signal to audit their code and identify areas needing improvement.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3483324) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Mudassir Khan Posted on May 26 Your LLM Is Wrong. Your Codebase Is Why. #ai #llm #webdev #typescript It happened on a Tuesday. I asked my AI coding assistant to explain a function I'd written three months earlier. It described a function that doesn't exist. Not a total hallucination. The function did exist. Just not by that name, not with those parameters, not doing what the model confidently told me it was doing.
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