Comment by akomtu
5 hours ago
The assumption was that some engineers knew how each part of the system worked, or at least the system was comprehensible because it was created by humans for other humans. There were comments explaining difficult places, etc. With AI this assumption is broken. Now nobody understands how things work, and it cannot be understood in principle because the system is a mountain of slop created by some alien intelligence.
I'm a staff engineer on team of 20+ engineers working in a single codebase. We're all pretty heavy users of AI, like most engineers today.
I worry about a lack of understanding creating risk, and we are creating tools and conventions to address this risk.
But I don't yet see evidence that we're losing touch with what we're building.. yes, code is shipping faster, but I'm honestly just not seeing this "sleep-walk-engineering" issue in reality.
Code isn't shipping so fast that the engineer doesn't understand the intent and general implementation details of the PR.
PRs are required to be small (400ish lines), and have tests, and good PR descriptions must be present. And two humans must approve the PR.
The time it takes to understand, verify and validate the change is fast, often as fast as or faster than the time it takes for AI to implement.
As it stands right now, our level of understanding, PLUS our new verification tools... is all we seem to need.
We're not like the hyperscalers, but we're considering how some of their approaches might fit into our workflow.
And much like Anthropic, we aren't seeing bugs increase with the rate of code increase.
Engineers are still able to understand enough of what they need to.
> Now nobody understands how things work
Well, the fancy calculators do. Yes, they still need guidance to keep from going off the rails. But, at least from personal anecdotal experience, I need to go spelunking into the codebase less and less over time. The agents and models really did just start to become that good.