Simon Willison, co-creator of Django and Datasette, is sounding the alarm on AI’s impact on software engineers. Instead of easing workloads, he says advanced AI coding agents are pushing engineers to their breaking point.

AI Agents Speed Work, But Drain Mental Energy

Simon Willison has been in software engineering for over 25 years. Yet he says that using AI coding agents to accelerate his work has left him more exhausted than ever. By mid-morning, he’s already wiped out.

On "Lenny’s Podcast," Willison explained that running multiple AI agents in parallel to tackle different coding problems demands every bit of his experience and focus. It’s not a simple hands-off relief — it’s a mental marathon.

"I can fire up four agents at once," Willison said. "But by 11 a.m., I am wiped out for the day." The fatigue is a new challenge that’s crept in as agentic AI systems have become more powerful and accessible since late 2023.

Pressure Mounts as AI Tools Multiply

Willison’s story isn’t unique. Many engineers report a rising pressure to constantly monitor and manage AI workflows.

While these tools promise to save time, the reality is a more intense work experience.

Some engineers admit they sacrifice sleep, feeling compelled to stay up longer because their AI agents could be making progress. Willison calls it a “new skill” to discover personal limits, but it’s a tough adjustment.

Researchers and critics have also flagged this risk. Harvard Business Review authors and NYU’s Gary Marcus have warned about AI stretching workers too thin. Accelerated output comes with a hidden cost — constant vigilance and mental strain.

Tension Between AI Hype and Reality

The AI industry often paints a future where autonomous agents dramatically reduce human effort. Vinod Khosla, a major OpenAI investor, recently predicted many kids today won’t need traditional jobs. Anthropic’s Boris Cherny even suggested software engineering roles could vanish this year.

Willison pushes back. He’s defending engineers caught in this fast-paced AI revolution. The obsessive, compulsive dynamic around AI workflows can be unhealthy, he says.

Still, he keeps using AI tools because they amplify what he can do. "I’m getting more time," he said, "but I’m exhausted."

What This Means for Tech and Finance

Willison’s experience sheds light on a major tension in AI’s financial impact. Companies invest billions expecting productivity surges. But if workers burn out faster, those gains could be short-lived.

Tech firms betting on AI-driven automation need to rethink how they integrate these tools. The goal is less about cranking out more work non-stop and more about sustainable productivity.

For investors and executives, the question is how to balance AI’s power with human limits. Fatigued engineers risk mistakes, lower innovation, and higher turnover. None of that helps a company’s bottom line.

On top of that, the cultural shift toward working alongside AI agents could reshape workplace norms. Will engineers become supervisors of AI instead of hands-on creators? And what financial structures will support that transition?

Willison’s warning is clear: AI tools don’t automatically lighten the load. They can make work faster but more draining. The next challenge will be managing human limits as AI powers up.