I trust AI code that crashes more than AI code that works, and 66% of developers seem to agree

You'd expect a year of upgrades to Claude Code, Cursor, and every other vibe coding tool to show up as faster releases. According to a fresh survey of 300 engineering leaders, it mostly hasn't. 79% of them say they can produce code much faster, yet their release cycles are no faster than before.

One substantial bottleneck is debugging: respondents estimate that it takes up 42% of their teams’ working week. But the figure covers all debugging, not just problems introduced by AI.

Writing code is now the small part of the week

Debugging takes almost twice as many hours

Undo, a company that makes debugging tools, had the research firm Coleman Parkes survey 300 senior engineering leaders in the US and UK during July and August 2026. They all work at companies with $250 million or more in revenue, mostly in finance, networking, and chip design, where an outage costs real money. Here's how their teams' 40-hour week splits up:

Debugging during development alone already matches the time spent writing code. Add the 7.2 hours spent chasing bugs that customers found, and debugging wins by a wide margin. The report's headline finding puts it bluntly: 79% of these leaders say that despite being able to produce code much faster, their release cycles are no faster than before.

Look at the table again, and that stops being surprising. Producing code is about a quarter of the week. If AI halved those 9.8 hours of code production and everything else stayed unchanged, it would save roughly five hours a week. If the code it writes then adds five hours of debugging, you've broken even, and you've traded writing for detective work.

Almost-right code is the expensive kind of wrong

It passes the test and fails in production

Stack Overflow's 2025 Developer Survey, which drew more than 49,000 responses, asked developers what frustrates them most about AI tools. The top answer, picked by 66%, was AI solutions that are almost right, but not quite. Second, 45% said debugging AI-generated code takes more time.

Wrong code is the easy case. It throws an error on the first run. You read the stack trace, and you fix it. Almost-right code compiles, passes the obvious test, and reads cleanly in review. Then it breaks on the input nobody tried, like an empty list, a leap year, or a user in another time zone. Undo founder Greg Law described the easy half plainly: "When code is obviously broken, the cause is usually easy to find."

The hard half shows up in his company's numbers. The leaders estimate that 35% of AI-generated code reaches production before their teams fully understand it. In the past six months, 81% had at least one production incident or outage tied to their use of AI coding tools. And 93% said an AI hallucination had sent them after the wrong root cause at least once.

That last one is the scary part. A crash tells you where to look. A subtle bug in code nobody fully read sends you looking in the wrong place, sometimes with an AI cheerfully pointing the way.

Developers already use AI to fix code almost as often as to write it

Autocomplete was never where the hours went

Stack Overflow's 2026 survey, released on October 6, tells the same story from the other side. Among developers who use AI in their workflow, 69.3% use it to generate code in an area they already know. Debugging, troubleshooting, or refactoring comes in right behind at 63.8%, with writing tests at 58.1%.

Autocomplete, the feature that sold a lot of people on AI coding in the first place, isn't even one of the options. In the 2025 edition, only 13.8% of respondents said they stick to Copilot or autocomplete mode. Developers have quietly turned these tools into something closer to a second pair of eyes than a faster keyboard.

Trust hasn't caught up with the habit, though. In the 2026 results, 48% of respondents trust AI output when they can easily verify it, and only 6.6% trust it for important work decisions. That gap says a lot. The slow part of programming was never typing. It was knowing whether what you typed is right.

The survey comes from a company that sells debugging tools

Undo has a stake in this, and its sample is narrow

Undo makes debugging tools, so it has a stake in debugging looking expensive. The report even closes on a pitch: 82% of respondents say coding agents would be far more useful for debugging if they had runtime context, which is roughly what Undo sells. Its sample is narrow, too. 93% of respondents work with C or C++, at large companies shipping mission-critical systems.

The 42% figure also covers all debugging, not just bugs that AI wrote. The report doesn't split them, so you can't pin all 16.9 hours on Claude or Copilot. A solo developer building a web app on the weekend probably lives in a very different week.

Stack Overflow's survey has its own blind spot, since the people who answer it are the people who visit Stack Overflow. Still, two very different groups, run by two very different organizations, land in the same place. AI writes code fast, and checking it is now the job.

How to cut debugging time when you code with AI

None of this means you should drop the AI. It means planning around where the time actually goes. Ask the AI to explain why a bug happens before it touches the fix. Have it write a failing test first, then the code that makes it pass.

And don't merge anything you can't explain to a coworker, because that 35% is exactly the code nobody can debug quickly later. Wrong code crashes. Almost-right code ships, and reviewing it is now the real work.