The rush to adopt agentic coding often looks successful initially because pull requests are merged at a rapid pace. However, the sheer volume of code forces engineers to rush reviews, allowing hidden quality issues to slip into production. Over time, reliance on automated generation erodes human understanding of core data structures and leads to more frequent production incidents.
Key points
Rapid automated code generation forces engineers to rush pull request reviews, letting sm…: Rapid automated code generation forces engineers to rush pull request reviews, letting small flaws accumulate.
Overreliance on automated coding tools diminishes the human expertise needed to identify…: Overreliance on automated coding tools diminishes the human expertise needed to identify flawed abstractions.
Initial development speed gains ultimately lead to unstable systems and a higher frequenc…: Initial development speed gains ultimately lead to unstable systems and a higher frequency of production incidents.
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I can only speculate as to the reasons why I was laid off from Meta in May, but I suspect that one of the reasons is that I was a little bit more resistant to adopting AI/LLMs as coding tools than some of my peers. Don't get me wrong, I generated at least 90% of my code using AI in my last few months there, which was the minimum for a decent rating. But AI didn't 10X the amount of code I was writing. It didn't even 2X it.
I was focused on code quality. I saw the code being pushed by some of my peers who were heavily reliant on AI, and I saw that it was brittle code. There were many subtle issues that would lead to tech debt in the long term, and even some glaring issues were ignored by very good programmers. For instance, I saw one of the best programmers on my team try to merge code that used javascript events for mouseover CSS effects rather than using the :hover selector, which is a totally…
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