The AI Paradox: Why Developers Are Working More, Not Less

Aurora Goods — Thu, 14 May 2026 10:00:27 +0000

A recent discussion on r/webdev has revealed a surprising and somewhat unsettling truth about AI in software development: while productivity tools like Claude and ChatGPT promise efficiency, developers are overwhelmingly reporting that they're working more than ever before.

The Productivity Trap

The data paints a concerning picture. Companies are witnessing productivity gains—with some claiming developers are 70% more efficient—but rather than translating this into reduced workloads, management is simply raising expectations. One developer reported receiving explicit threats: "use AI aggressively or get laid off," with deadlines slashed in half despite demands for perfect testing and code quality.

This reflects a fundamental misunderstanding about how productivity gains should work. When agricultural automation made farming more efficient, we didn't see farmers working less—we saw GDP allocation shift elsewhere. The same pattern is repeating in tech, where AI-driven efficiency is being captured by employers rather than improving work-life balance.

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The Mental Toll of Context Switching

Perhaps the most revealing insight from the discussion concerns how AI has fundamentally changed the nature of development work. Multiple developers describe their work shifting from deep, focused coding sessions to constant context switching—juggling multiple Claude instances, reviewing AI-generated code, and bouncing between tasks while waiting for responses.

One developer described being expected to run two Claude instances simultaneously: one for their main task and another working through the backlog. Another painted a vivid picture of an "AI-enhanced fugue state," rapidly switching between laptops, VR headsets, and AI assistants across multiple projects. The consensus? The loss of "flow state"—that deep concentration zone where developers do their best work—has made the job less satisfying and more exhausting.

The Code Review Crisis

A particularly troubling trend emerging from the discussion is the explosion of code that needs human review. Senior developers report spending significantly less time writing code but exponentially more time reviewing AI-generated pull requests. Research mentioned in the thread indicates that while junior developers see 25-40% speed increases, senior developers actually slow down by 18% due to reviewing AI code that sits in PRs four times longer than human-written code.

The quality concerns are real. One team laid off their entire manual QA department and senior leadership, replacing oversight with AI—only to find themselves "shipping bugs and subsequent fixes for bugs". Another developer at a major bank expressed concern about what happens "when the cracks start forming" in systems built under these pressured timelines.

The Economic Reality

Beyond the developer experience, there's a larger economic question at play. While companies are seeing productivity gains, those gains are largely being captured by AI companies like Anthropic and OpenAI through subscription costs. One comment referenced Baumol's cost disease, explaining how when productivity gains don't translate to worker salaries but instead go to external services, it can actually worsen economic inequality and strain necessary services.

The financial sustainability is also questionable. Despite Anthropic being on track for $30 billion in revenue in 2026, the company would need to make that amount in profit ten times over just to break even on their investments. LLMs as a service remain unprofitable, with massive infrastructure costs funded by hyperscalers who are themselves investors.

A Few Bright Spots

Not all feedback was negative. Some developers found AI helpful for handling hybrid roles, running background bug fixes while managing customer support. Others appreciated automation of mundane tasks, freeing up time for work that traditionally received insufficient attention. A few described the work as "more fun," enjoying the dopamine hits of rapid feature engineering despite increased context switching.

The Future We're Building

The discussion reveals a profession at a crossroads. Developers are becoming "code shepherds" rather than code writers—managing, reviewing, and quality-checking AI output rather than crafting solutions themselves. Many report feeling "stupider" and less capable of thinking through problems independently. One developer's admission was particularly stark: "I get way more done, but I also don't understand what's going on".

What do you think? Is AI making your work better or just faster? Have you noticed similar patterns in your industry? Share your experience in the comments below.