The AI Workflow That Saved Me From a Debugging Spiral (And How to Replicate It)
The article discusses how the author improved their debugging process by changing the way they interact with AI tools. Instead of asking vague questions, they began providing context and specific prompts, leading to more effective assistance. This shift not only resolved a critical bug quickly but also enhanced their overall productivity in coding tasks.
- ▪The author initially lost significant time debugging a webhook integration issue due to ineffective use of AI.
- ▪By restructuring their prompts to include context and specific questions, they were able to identify the bug in just eleven minutes.
- ▪The author developed a pre-review prompt to catch potential logic errors before submitting code for review.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3914896) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Tal Vardi Posted on May 18 The AI Workflow That Saved Me From a Debugging Spiral (And How to Replicate It) #programming #ai #tutorial #career Last quarter I lost a full afternoon to a bug that, in hindsight, took 11 minutes to fix once I changed how I was talking to my AI assistant. Here's what actually happened. The Situation We were mid-sprint. A new webhook integration kept silently dropping events under specific payload conditions — no exception, no log line, just gone.
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