Software developers use AI more than ever, but trust it less

Cal Jeffrey

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The big picture: Software developers are increasingly weaving AI tools into their work, but such rapid adoption hasn't come without confusion or conflict. They and their managers are still trying to work out when these tools help, when they hurt, and how to integrate them without creating more problems than they solve.

In its annual poll of 49,000 professional developers, Stack Overflow found that 80 percent use AI tools in their work in 2025, a share that has surged in recent years. Despite this wide and rapid adoption, trust in those tools is falling. The survey shows that only 29 percent of respondents say they trust AI's accuracy, down from 40 percent in past surveys.

That gap – widespread adoption alongside growing skepticism – reflects the complex impact of AI-powered coding assistants like GitHub Copilot or Cursor. While few developers question their usefulness, many are still learning how to apply these tools effectively and understand their limits.

When asked about their biggest frustration, 45 percent pointed to AI-generated solutions that seem mostly correct but contain subtle flaws. Unlike clearly incorrect code, these near-misses can introduce hidden bugs and logic errors that take hours to untangle – especially for junior developers who accept AI suggestions too readily.

The fallout often circles back to Stack Overflow itself. More than a third of developers said they visit the site because of AI-related issues, meaning code generated by tools they trusted created problems they couldn't solve on their own.

Recent advances in reasoning-focused models have improved reliability. Still, the survey suggests that AI's "close-but-not-quite" problem is here to stay – it's tied to how predictive text generation works. That's one reason 72 percent of developers reject the idea of "vibe coding," or casually pasting in AI-suggested code for production use.

Even with those frustrations, few are abandoning these tools. In some cases, managers push teams to adopt them. More often, developers themselves see clear benefits – so long as they use the tools carefully.

Industry experts say the key is training and mindset. Developers should treat autocomplete tools powered by AI as a "sparring partner," not a silent copilot. Those who simply tab through GitHub Copilot's suggestions risk embedding flaws; those who use it to spot issues or refine ideas get the most value.

The tools also offer an educational upside. Artificial intelligence can flatten the learning curve for new languages or frameworks, offering targeted answers that complement traditional documentation searches – a function Stack Overflow has filled for years.

Chief Product and Technology Officer Jody Bailey told Venture Beat that Stack Overflow is rethinking its role as AI changes how developers seek help and share knowledge. She acknowledged that the company has seen fewer visits but warned that many people overstate the narrative around that trend.

"Although we have seen a decline in traffic, in no way is it as dramatic as some would indicate," she said, adding, "That shift is causing Stack Overflow to critically reassess how it gauges success in the modern digital age."

Image credit: Sergiy Galyonkin

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This is the worst AI will be.
The majority see AI, if at all, as a better assistant, AI videos and scams. Businesses have seen what it can really do, even if it will take some time to get there. I'm pretty confident we'll get there.
 
I am astounded by the power of AI generated video. In 10 years, it will be so amazing that movie making and video gaming will be nothing like we see now.
 
They way this article phrases "growing skepticism" can easily also be framed as people being more aware of AI's limitations as they get more familiar with using it. Clearly AI's adoption rate isn't slowing down so this is just a result of people taking off their rose colored glasses and just using AI for what it's actually good at right now.
 
I am astounded by the power of AI generated video. In 10 years, it will be so amazing that movie making and video gaming will be nothing like we see now.
They'll have to match the features sets from games from 10 year's ago. Once you get the immersive behavior of each object to match all previous games and then you can start to build games that can scale exponentially better than what we have today imo. Once we have an ai overhaul that debugs the system and assists the artists build their vision on how to develope a cohesive enjoyable experience; that will potentially make game development synergistically better. Until then game development is digressing in quality features that fail to match decade age games.
 
Those who simply tab through GitHub Copilot's suggestions risk embedding flaws; those who use it to spot issues or refine ideas get the most value.

Yeah, the 'vibe coding' nonsense leads to buggy non functional code in my experience. However if you feed it what you have and ask how to do x or y it can be quite useful. Or ask if something can be done more efficiently/cleaner.

Ironically I would rate copilot as the worst of the bunch as well. You'd think with full access to all of GitHub it would lead to the best model. I'd say Gemini is slightly better although not by much and Claude is far ahead. Don't get much for free with Claude though so I only use it as a last resort when the other two get stuck. Have had it a few times where the other two just keep circling trying the same wrong things where as Claude immediately nails the answer.

This is with C#/Avalonia code mostly. Claude seems to be much better at sticking to Avalonia code rather than randomly injecting a whole bunch of WPF code.
I've been doing some code generation code lately as well through building an analyzer using Roslyn. The experience is very much the same, Claude seems to know what it is doing compared to the other two
 
I've meddled using AI for Python , since its new language for me. So far AI does better with python than snowflake or SQL...apples and oranges but still. Problem is young devs are just going to AI to write code and not learning the why/how.
 
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