Study: Developers are addicted to AI, and managers are making it worse

AI is addictive, and managers are rewarding those who use it the most (even though they are shipping stuff they don’t understand). What a tangled mess. Let’s unpack findings from the AI Coding Addiction Report, what it says about the wayward use of AI coding tools, and how behavior differs based on whether you use Claude Code, Google Gemini, OpenAI Codex, or GitHub Copilot.

The survey targeted developers who use AI at least once a week, and the report is based on over 300 responses from developers of varying seniority levels and using different tools.

Animal mistreatment, applied to humans

A branch of psychology called behaviorism is based on trial-and-error learning. Edward Thorndike noticed that cats could learn skills to escape from puzzle boxes, but B.F. Skinner took it further. Skinner invented the “operant conditioning chamber”, a box that could be used to manipulate animal behavior by forcing it to respond to signals to earn rewards. If a rat or pigeon in the chamber hits a button when the light comes on, it gets food. If they fail to press the button, the electric grid in the floor delivers a punishment.

Skinner Box diagram by AndreasJS.

The ultimate result of this line of research was the creation of push-button slot machines, arranged in long rows, with flashing lights and occasional rewards for humans who drop coins in and press the button. In a business context, it shows up in gamification techniques, where managers treat employees like lab animals and are surprised when employees respond by acting like they are.

Intentionally or otherwise, AI coding tools seem wired like a Skinner Box. With coding loops delivering frequent flashing lights and rewards, 43% of developers hit home time but can’t tear themselves away from the reward-generation process. Overall, 80% of developers describe their relationship with AI as “more like a dependence than an advantage.” In fact, it’s harder to give up AI coding tools than to give up social media or video games, which are often colloquially described as “addictive.” This is why developers report skipping or delaying breaks, meals, and even bedtime.

What developers skip or delay during AI coding sessions. Source Coddy.

This leads us to ask some serious questions, like how much of the “AI productivity gain” comes from the behaviorism of keeping developers at the keyboard for longer hours with fewer breaks and less rest?

Differences by tooling

One interesting finding is that AI coding tool choice may influence at least some behaviors. Codex had the highest after-hours coding rate (62%), compared with lower rates for Gemini (45%), Claude Code (40%), and GitHub Copilot (36%). This could indicate that Codex most deeply embodies the stimulus/reward cycle of the Skinner box.

It could be illuminating to identify which specific aspects of these tools increase the likelihood of addictive coding loops spilling into the workday so that we can moderate their impact on personal time and crucial rest. As senior developers are most likely to work longer hours, organizations will end up with tired people making important decisions. This hustle has serious consequences, and none of them are good for the organization.

You’ll get more of what you reward

Meanwhile, managers quickly reward those who are most addicted. The heaviest AI users were more likely to get raises and promotions, even though 71% of developers shipped code they didn’t fully understand. Before AI, a developer copying and pasting code from Stack Overflow into their codebase was expected to understand and adapt the examples as part of the work. But now, managers are throwing cash at the developers glued so hard to the slot machine they can’t pause to visit the restroom, let alone assess the code they are committing.

With these heavy AI users getting the rewards, other developers are left to mimic the dysfunctional behavior, or at least give the impression of it. There’s a famous scene in the movie Shaun of the Dead where the band of misfit protagonists must cross a road infested with zombies. They achieve this by emulating the jerky movements and slurred speech of the infected. Developers who want to understand the code they commit will feel pressure to compromise when they see rewards going to the flippant.

Organizations must realize that software value comes from a series of good decisions. Hustle mode rapidly diminishes the rate at which decisions cross the threshold of “good”. The value is in gracefully solving user problems, but too many managers value software by the volume of features, code, or hours spent with their hands on the keyboard.

Look around you. The world is in a state of excess. There’s an avalanche of content, code, and crunch. We don’t need more; we need better.

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