Bug reports arrive incomplete, ambiguous, or buried in noise. Before you can fix anything, you need to triage — figure out severity and ownership — and then reproduce, which is often the hardest part. AI won't magically reproduce a bug for you, but it will dramatically compress the time between "a user filed a ticket" and "I have a failing test case in front of me." Here's the exact workflow I use. Step 1: Feed the Raw Bug Report to the AI and Ask for a Triage Summary Paste the entire bug report — stack trace, user description, logs, whatever you have — and prompt: Here is a raw bug report. Summarize it with: 1. One-sentence description of what is failing 2. Likely severity (P1/P2/P3) with your reasoning 3. The component or service most likely responsible 4. What information is missing that would help reproduce this --- [PASTE RAW BUG REPORT HERE] This gives you a structured starting point in seconds, and the "missing information" output is gold — it's your follow-up checklist for the reporter. Step 2: Ask AI to Generate a Minimal Reproduction Scenario Once you have the triage summary, ask the AI to sketch a reproduction path. Provide any relevant code, schema, or config snippets alongside the report: Given this bug report and the following code snippet, write a step-by-step reproduction scenario. Format it as numbered steps a developer can follow from a clean environment. Flag any assumptions you're making. Bug summary: [paste Step 1 output] Code snippet: [paste relevant code] The "flag your assumptions" instruction is critical — it surfaces gaps you'd otherwise only discover after wasting 30 minutes on the wrong path. Step 3: Convert the Reproduction Steps into a Failing Test This is where the real leverage is. Take the reproduction scenario and prompt: Convert these reproduction steps into a failing unit or integration test in [language/framework]. The test should: - Set up the exact preconditions described - Call the code path that triggers the bug - Assert the incorrect behavior so the test fails until the bug is fixed Reproduction steps: [paste Step 2 output] You now have a regression test before you've written a single fix. That's the correct order. Step 4: Use AI to Hypothesize Root Causes With a reproducible case in hand, prompt for root cause candidates: Here is a bug description and a failing test. List the 3 most likely root causes, ranked by probability. For each, describe what code change would confirm or rule it out. Bug: [summary] Failing test: [paste test] This turns a blank-stare debugging session into a structured investigation with a clear order of operations. Putting It Together The four prompts form a repeatable pipeline: raw report → triage summary → reproduction steps → failing test → root cause hypotheses. Each step's output feeds the next, so the AI has the context it needs at every stage. On a recent project I ran a gnarly async race condition through this pipeline and had a failing test in under 20 minutes — a task that usually burns an hour or more. The key discipline: don't skip Step 1. A structured triage summary forces you to confirm you understand the bug before you start poking at code. I break down one workflow like this every week in The AI Leverage Weekly — practical, no fluff, free. Subscribe: https://theaileverageweekly.beehiiv.com/subscribe?utm_source=devto&utm_medium=article&utm_campaign=medium_w18