Programmers refuse to work without AI, and this may affect them

Researchers have discovered that in 2026, you can’t take AI coding tools out of developers’ hands.

But while AI undoubtedly helps programmers produce code faster, it may not produce better code, other researchers warn. This could cause problems for them in the future.

Specifically, in February 2026, the respected artificial intelligence research laboratory METR She posted a surprising revelation: Most developers will not be able to work, even on a limited number of tasks, without AI anymore.

METR was hoping to provide an update to some Groundbreaking research has been published A few months ago, in 2025, on the productivity of artificial intelligence encryption. In this study, researchers measured the amount of time it takes open source developers to do tasks manually versus the time it takes artificial intelligence.

While the developers in that study said that AI made them more productive, they were shocked to learn that it actually slowed them down. Sure, they generated code faster, but they spent extra time finding and fixing bugs, directing the AI ​​and waiting for it to complete tasks.

When METR set out to replicate the experiment to measure progress in artificial intelligence and programming efficiency, it couldn’t.

The researchers admitted that developers were not willing to participate “because they did not want to work without the AI” even just for the sake of study.

Alternatively, meters Posted a survey In May, this allowed technical staff to self-report their AI productivity gains. Not surprisingly, they realized that AI made them doubly valuable to their organizations.

But recent headlines about The runaway cost of so-called tokenmaxxingalong with a smattering of recent research, makes such self-perceptions questionable.

Tokenmaxxing, or using the number of tokens a person uses as a proxy for productivity using AI, has been the trend in 2026 so far. It may already be over.

Amazon shut down its internal leaderboard for tracking tokens called Kirorank after employees were manipulating it with artificial intelligence agents excessively, leading to high costs, Amazon said. The Financial Times reported this week. Employees have proven that using AI does not automatically lead to increased productivity.

Uber exceeded its 2026 AI budget during the first four months of the year. Information I mentioned. COO Andrew McDonald recently said on a podcast that this is the case Spending did not lead to a measurable increase In projects or productivity.

And AI-generated code does not necessarily reduce ongoing code maintenance needs, and may even increase them, as programmer and author James Schur elegantly argued in Blog post Which went viral on Hacker News.

“Are you writing code twice as fast now? You might as well have cut your maintenance costs in half,” he wrote. “Otherwise you’re in a bad situation. You’re trading a temporary increase in speed for a permanent contract.”

There is other evidence that AI can increase code maintenance problems.

A Viral tweet From Aiswarya Sankar, founder and CEO of reliability engineering agent startup Entelligence AI, announced that companies are spending 44% of their tokens on fixes for bugs generated by their AI. Meanwhile, code review tools company Rabbit code It says it analyzed open source pull requests and found that AI generated 1.7 times more problems than human code.

Admittedly, these are self-serving statistics from those trying to sell AI code review tools.

However, independent researchers have also found such problems. Researchers from the prestigious Singapore Management University It published a report in April “AI-generated code can lead to long-term maintenance costs in real software projects,” he warns.

Since programmers love AI assistants, what’s the solution?

Well, those who want to sell AI coding agents say that developers can only use AI coding agents to do the cumbersome tasks of fixing code as quickly as the AI ​​deploys it. Here’s what Cognition founder and CEO Scott Wu — maker of the AI ​​coding agent Devin — had to say: suggests.

But even he admits that while Devin can work independently, he currently rates his skill between beginner and intermediate programmers, depending on the task. This is not a just hand it over and forget about it solution.

SMU researchers suggest a more humane approach. Programmers should know what AI does and doesn’t do as well as they know their favorite programming languages. They need robust quality assurance systems designed for AI, and they are stuck carefully reviewing the AI’s work as if it were a junior developer.

Meanwhile, the researchers say (and Wu agrees), humans should keep doing the big work like software engineering and security design.