alt Hacker NewsFrom "code" to "no-code" to "vibe coding" and back to "code".
What you are seeing here is that many are attempting to take shortcuts to building production-grade maintainable software with AI and now realizing that they have built their software on terrible architecture only to throw it away, rewriting it with now no-one truly understanding the code or can explain it.
We have a term for that already and it is called "comprehension debt". [0]
With the rise of over-reliance of agents, you will see "engineers" unable to explain technical decisions and will admit to having zero knowledge of what the agent has done.
This is exactly happening to engineers at AWS with Kiro causing outages [1] and now requiring engineers to manually review AI changes [2] (which slows them down even with AI).
[0] https://addyosmani.com/blog/comprehension-debt/
[1] https://www.theguardian.com/technology/2026/feb/20/amazon-cl...
[2] https://www.ft.com/content/7cab4ec7-4712-4137-b602-119a44f77...
Replies
While I agree with everything you said, Amazon’s problems aren’t just Kiro messing up. It’s a brain drain due to layoffs, and then people quitting because of the continuous layoff culture.
While publicly they might say this is AI driven, I think that’s mostly BS.
Anyway, that doesn’t take away from your point, just adds additional context to the outages.
> We have a term for that already and it is called "comprehension debt".
This isn't any different than the "person who wrote it already doesn't work here any more".
> now requiring engineers to manually review AI changes [2] (which slows them down even with AI).
What does this say about the "code review" process if people cant understand the things they didn't write?
Maybe we have had the wrong hiring criteria. The "leet code", brain teaser (FAANG style) write some code interview might not have been the best filter for the sorts of people you need working in your org today.
Reading code, tooling up (debuggers, profilers), durable testing (Simulation, not unit) are the skill changes that NO ONE is talking about, and we have not been honing or hiring for.
No one is talking about requirements, problem scoping, how you rationalize and think about building things.
No one is talking about how your choice of dev environment is going to impact all of the above processes.
I see a lot of hype, and a lot of hate, but not a lot of the pragmatic middle.
> With the rise of over-reliance of agents, you will see "engineers" unable to explain technical decisions and will admit to having zero knowledge of what the agent has done.
I've had to work on multiple legacy systems like this where the original devs are long gone, there's no documentation, and everyone at the company admits it's complete mess. They send you off with a sympathetic, "Good luck, just do the best you can!"
I call it "throwing dye in the water." It's the opposite of fun programming.
On the other hand, it often takes creativity and general cleverness to get the app to do what you want with minimally-invasive code changes. So it should be the hardest for AI.