Speed vs Understanding: The Tradeoff in AI-Assisted Code

Recently, CloudFlare garnered some attention by building and publishing an OAuth library with Claude. You can find the HackerNews discussion here.

The author wrote

“It took me a few days to build the library with AI. I estimate it would have taken a few weeks, maybe months to write by hand.”

Usefully, the commits included the prompts used. Here are two good examples.

Look closer

Does this mean we’ve crossed a new line in software development, where anyone can develop production-ready libraries with AI? Not quite.

It won’t surprise anyone to learn that the code wasn’t perfect off the bat. Seeing how it went wrong and what skills were required to fix it is revealing.

In one example, the engineer asks whether a backup key defeats the purpose of end-to-end encryption. Great question. But it requires expertise to ask this question in the first place, to then describe appropriate changes.

Another time, Claude simply couldn’t fix a bug. The library author ended up fixing it himself.

“Fix Claude’s bug manually. Claude had a bug in the previous commit. I prompted it multiple times to fix the bug but it kept doing the wrong thing. So this change is manually written by a human…”

But there was a bigger hidden cost.

Another HackerNews commenter reflected that reading someone else’s code is exhausting. When you write code yourself, you develop a familiarity with its moving parts. Each change incrementally builds on what went before. But when 100 lines of code appear out of the ether, it takes much more cognitive effort to follow the flow.

Other commenters agreed that speed comes at the cost of cognitive load. At the end of the day, we still need to understand what’s going on, and that’s much harder when you haven’t written the code yourself.

Your takeaways

  1. If you know what you’re doing, AI can help you move a lot faster.
  2. Effective, clear prompting is required, and this requires domain expertise in the first place.
  3. You’re also going to need that expertise to fix random issues that AI is currently unable to.
  4. AI might be more useful for incremental additions, rather than creating something from scratch. Otherwise, you trade speed for an unsustainable cognitive load.

So yes, AI can help you move faster. But like any power tool, it’s only as effective as the hand that guide it. If you don’t know how to build, debug, and reason about systems, speed just gets you lost quicker.