AI for Debugging & Troubleshooting
Master systematic debugging with AI — read error messages, isolate bugs, use debugging tools, recognize common patterns, and perform root cause analysis.
What You'll Learn
- Apply a systematic debugging process — reproduce, isolate, identify, fix, and verify — to any bug efficiently
- Interpret error messages and stack traces to locate the source of a bug without guessing
- Use AI to explain errors, generate hypotheses, and suggest fixes while maintaining your own understanding
- Recognize common bug patterns — off-by-one errors, null references, race conditions, and async issues
- Debug production issues using logging, error tracking, and AI-powered log analysis
- Perform root cause analysis using the 5 Whys technique to fix underlying problems instead of symptoms
Course Syllabus
Who Is This For?
- Developers who spend too long on debugging and want a systematic approach accelerated by AI
- Beginners who feel lost when facing error messages, stack traces, and unexpected behavior
- Experienced developers who want to use AI tools effectively for faster root cause analysis and bug resolution
Developers spend 30-50% of their time debugging. The difference between a junior developer who spends 4 hours on a bug and a senior who solves it in 15 minutes isn’t intelligence — it’s a systematic approach to finding root causes.
AI has transformed debugging: organizations report 60-75% reduction in bug resolution time when developers use AI effectively. But “paste the error into AI and hope for a fix” isn’t effective debugging — it’s guessing with extra steps.
This course teaches you the systematic debugging process that experienced developers use, then shows you how AI accelerates each step. You’ll learn to read error messages, isolate bugs, recognize common patterns, and fix root causes — not just symptoms.
What you’ll build: A personal debugging playbook — a systematic workflow for approaching any bug, with AI prompts for each step that turn hours of frustrated guessing into minutes of methodical investigation.
Related Skills
Frequently Asked Questions
Which programming language does this course use?
The debugging concepts apply to any language. Examples use Python, JavaScript, and general pseudocode. The systematic approach, error reading skills, and AI techniques transfer to any language or framework you work with.
I'm a complete beginner. Is this course right for me?
Yes. If you can write basic code (loops, functions, variables) but struggle when things go wrong, this course teaches you the missing skill: how to find and fix bugs systematically instead of changing random things and hoping it works.
How does AI help with debugging?
AI explains error messages in plain language, generates hypotheses about what might be wrong, suggests fixes, analyzes logs to find patterns, and acts as a rubber duck debugger — helping you think through problems methodically. Studies show AI can reduce bug resolution time by 60-75%.
Will this make me dependent on AI for debugging?
No. This course teaches the systematic debugging process first — the thinking framework that makes good debuggers. AI accelerates each step but doesn't replace the critical thinking. You'll learn when AI helps (explaining unfamiliar errors) and when to rely on your own analysis (understanding your specific codebase's behavior).