Gergely Orosz · 9 min read · Productivity
Are AI agents actually slowing us down?
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The piece argues that AI agents can boost short-term output but may slow long-term progress by degrading product quality and maintainability. It highlights real-world cases from Anthropic, Amazon, and other players to illustrate how heavy AI reliance can impact user experience, outages, and code quality, and suggests stronger architectural discipline and formal validation as remedies.
Key Takeaways
- AI-enabled development can increase output in the moment (more PRs, faster code) while harming long-term quality and maintainability.
- Concrete examples (Anthropic's degraded site, Amazon outages) show that AI-assisted changes can introduce user experience flaws and reliability risks.
- There is cultural pressure to use AI aggressively, sometimes irrespective of the impact on quality or stability.
- Mitigation requires stronger architectural sense, formal validation methods, and revived QA practices to prevent tech debt and bloated code.
- Early velocity gains from AI can lead to slower long-term velocity if refactoring and quality work are neglected.
Excerpt
When it comes to AI agents and AI tooling, most of the discussion focuses on their potential boosts for efficiency, faster iteration, and the pushing out of more code, faster. Last week, we took an inside look into how Uber is adopting AI , internally. The rideshare giant has built close to a dozen internal systems to deal with code generated by AI agents. However, when quantifying the impact of AI, the focus was on how much output has increased, and how devs who use more AI also generate more pull requests; these are the “power user” devs who generate…