How AI Assists in Debugging Code

Debugging with AI is an A+ experience! Here is what I do, in very simple terms: 1. Ask the model to generate a few hypotheses Instead of asking directly for a fix, I ask the model to generate a few hypotheses of what could be happening and a proposed solution. Often, models attempt to fix the wrong thing or write excessive code that's unnecessary to solve the problem. Asking for hypotheses and potential solutions shows me what they are thinking and how they plan to solve it. 2. Ask for a reason, not a fix I'd rather ask, "What is causing this error?" than "What's the fix for this error." The former forces the model to provide a complete explanation I can review (and understand). The latter puts the model in "slop-code-generation" mode. 3. Always paste error logs I never say, "My code doesn't work." Instead, I drop the full traceback, test failures, or log output. The more, the merrier. Models are really good at parsing through all of this. 4. Explain what you've already tried This helps the model skip obvious dead ends. The more context you provide, the better the model suggestions will be. 5. Iterate, but be smart about it It's common to get stuck in a loop with a model that tries one solution, then another, and then back to the previous solution. The best way I've found to break out of these loops is to continually update the context and help the model with new clues. Another trick is to change models but share the entire context with the debugging session. Sometimes, one model can see what the other can't.

I spent 200+ hours testing AI coding tools. Most were disappointing. But I discovered 7 techniques that actually deliver the "10x productivity" everyone promises. Here's technique #3 that’s saved me countless hours: The Debug Detective Method Instead of spending 2 hours debugging, I now solve most issues in 5 minutes. The key? Stop asking AI "why doesn't this work?" Start with: "Debug this error: [exact error]. Context: [environment]. Code: [snippet]. What I tried: [attempts]" The AI gives you: → Root cause → Quick fix → Proper solution → Prevention strategy Last week, this technique saved me 6 hours on a production bug. I've compiled all 7 techniques into a free guide. Each one saves 5-10 hours per week. No fluff. No theory. Just practical techniques I use daily. Want the guide? Drop “AI” below and I'll send it directly to you. What's your biggest frustration with AI coding tools? Happy to try and help find a solution.

"The Prompt Engineering Playbook for Programmers" My latest free write-up: https://lnkd.in/g9Kxa7hG ✍️ The difference between a vague "fix my code" request and a well-crafted prompt can mean the difference between generic, unhelpful advice and precise, actionable solutions that accelerate your development workflow. My "Prompt Engineering Playbook" has actionable strategies to help you get the most out of AI coding assistants. If you missed it, or need a refresher on crafting prompts that deliver real results, now's a great time to dive in. Inside, you'll find: ✅ Effective patterns (role-playing, rich context, iterative refinement) ✅ Smart debugging strategies with AI ✅ AI-assisted refactoring for better code ✅ Building new features step-by-step with your AI pair programmer ✅ Common anti-patterns to avoid (and how to fix them) Here's what separates developers who struggle with AI from those who use it effectively: 🎯 The Foundation Rich context: Never just say "fix my code" - specify language, framework, error messages, and expected behavior Clear goals: Replace "this doesn't work" with "this function should return a sorted array but returns undefined" Break it down: Don't ask for entire features - iterate from skeleton → logic → optimization ⚡ Refactoring game-changer ❌ Vague: "Refactor getCombinedData function" ✅ Specific: "Refactor to eliminate duplicate fetch logic, parallelize requests, and optimize data merging. Preserve individual error messages." Result: AI delivers parallel fetching, efficient data structures, and maintains debugging capability. 🎭 Secret weapon: role playing "Act as a senior React developer reviewing this code for performance issues..." "You're a TypeScript expert - refactor following modern best practices..." This simple technique dramatically improves response quality and specificity. ⚠️ Avoid these anti-patterns - Overloaded prompts ("build a complete app") - Vague success criteria ("optimize code" vs "reduce memory usage") - Ignoring AI clarifying questions - Inconsistent style across conversations 💡 Bottom line With AI, the more context and direction you provide, the better your results. I hope it's a helpful read. #ai #programming #softwareengineering