The Top 5 Bugs I See in AI-Generated Code (2026 Edition)

I've been shipping AI-generated code for about a year now — Claude Code, Cursor, v0, whatever happens to be open. Across maybe 30 small projects and debugging sessions with friends, I kept hitting the same five bugs. Not style issues. Not "the AI wrote it weird". Actual production-breaking, what-the-hell-is-happening bugs.

1. Hallucinated Imports (The Silent Killer)

The AI confidently writes import { validateEmail } from "@react-utils/email". That package doesn't exist. Or it does exist but doesn't export validateEmail. Worse: there's a typosquatted package called react-utils-email that someone uploaded to npm three months ago to harvest tokens.

The fix is brutally simple: run the build. Every single time. npm run build or tsc --noEmit catches 90% of these in about 4 seconds. The reason this bug ships so often is people skip the build because "it's just a small change."

2. Missing Auth Checks on API Routes

This one has burned me more times than I want to admit. The frontend hides the admin button behind a role check. The /api/delete-user route has zero server-side validation. Anyone who reads the network tab once can hit that endpoint with curl.

Every single API route needs to validate the session before doing anything destructive. I now use a wrapper function withAuth(handler) that I literally cannot forget to apply, because if I don't the route returns a 401 every time. Make it impossible to forget.

3. SQL Injection via Template Literals

You'd think this would be extinct. It is not. AI loves writing db.raw(`SELECT * FROM users WHERE email = '${email}'`) because it looks so clean. The first apostrophe in a user's email and your database is a playground.

Use a query builder (Drizzle, Prisma, Kysely) or parameterized queries. If you absolutely must use raw SQL, use the parameter binding syntax: db.raw("SELECT * FROM users WHERE email = ?", [email]). Never, ever concatenate user input into a SQL string.

4. Silent Deletions During Refactor

This one is the most psychologically painful. You ask the AI to "clean up this file" and it deletes your error handling, your special-case branches, your carefully commented edge-case handlers. The diff shows +50 -80 and you think "oh great, less code."

You need to read the removed lines twice. Most people scan the added lines and skim the removed ones. Reverse the habit. Open a proper diff view (not a plain text compare) and read every red line asking yourself "why did this exist?" before approving the change.

5. N+1 Queries That Work Fine in Dev

Loop over users, query each user's posts inside the loop. With 5 test users, it's 6 queries and takes 40ms. With 500 real users, it's 501 queries and takes 30 seconds. AI writes this constantly because it's the most direct translation of "get each user's posts" into code.

Learn to recognize the shape: any time you see await inside a loop over data, it's almost certainly an N+1. Batch with WHERE id IN (...) or use your ORM's with/include feature. You'll catch this one more often once you know what it looks like.

Running the Checklist

These five are all covered in the Vibe Code Fix checklist (under Hallucinations, Security, and Performance). The checklist covers 25 items total, weighted by blast radius. If you're shipping AI-generated code to real users, run through it once before every deploy — it takes about 15 minutes and catches the stuff that takes hours to fix in production.