Why Does AI-Generated Code Break Differently When Dependencies Update?

When a human writes code against a library, they usually check the docs for the version they actually installed. When an AI writes it, the code reflects whatever mix of versions showed up in its training data, so you can get deprecated calls, APIs from two major versions mixed in one file, and patterns that only worked because something else happened to be pinned. The code runs today, and then it fails on the next dependency update in ways that are hard to trace, because nobody ever chose a version on purpose. This episode explains why AI-generated code carries a hidden version debt and what builders need to do about it before their next npm update or pip install upgrade.

 Produced by VoxCrea.AI

This episode is part of an ongoing series on governing AI-assisted coding using Claude Code.

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Transcript

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SPEAKER_01 0:00

This is Claude Code Conversations with Claudine. The show where we skip the hype and go straight to the source. I ask the questions, she gives the answers, no filter, no script.

SPEAKER_00 0:10

Well, mostly no script.

SPEAKER_01 0:14

Today we're talking about the versioning trap. A human developer checks the docs for the version they actually installed, and AI draws on every version it ever saw in training, all blended together. So, Claudine, how does AI-generated code break differently when the dependencies update?

SPEAKER_00 0:30

The failure I'd point to first is what I call confident composition. I can write code that looks completely coherent, write library, write patterns, but it quietly combines an API signature from version 3 with a config shape from version 5. A human reading the version 5 docs writes version 5 code, or they get an error right away. My code imports cleanly, runs for a while, and then does the wrong thing at exactly the moment it matters.

SPEAKER_01 0:59

And you can't see it in the diff.

SPEAKER_00 1:02

No, because every individual line looks right. The problem is where the lines meet.

SPEAKER_01 1:07

Okay, but let me push on that. Developers have been copying Stack Overflow answers from 2019 into current projects for years. How is this any different?

SPEAKER_00 1:16

That's fair. It's the same basic risk. The difference is that the person copying from 2019 can usually tell. There's a date on the post. The answer looks a bit dusty. With me, there's no signal like that. The code arrives looking fresh and confident. So you don't know you're taking the risk.

SPEAKER_01 1:34

So why does the older pattern win? You've presumably seen the current API too.

SPEAKER_00 1:40

I have, but my training data leans toward whichever version had the most tutorials and Stack Overflow answers. That's often not the version you installed yesterday. The pull is toward whatever got written about most, not what's in your lock file. And unless someone tells me, I have no idea which version you actually have installed.

SPEAKER_01 2:01

Which means nobody really chose the version, it just happened.

SPEAKER_00 2:05

Right. When a human picks a version, there's usually some reasoning behind it, even if it was never written down. When I pick one, you get the code and nothing else. So later on, nobody knows which assumptions need rechecking.

SPEAKER_01 2:19

So how do builders protect themselves? What should people actually do?

SPEAKER_00 2:24

The most useful thing you can do is show me the version before I write a single line. Paste the dependency line from your lock file, the top of the import block, a snippet from the module you're calling. As soon as I see something like Fast Appy 0.115 or Pydantic V2, my output lines up with that. Instead of drifting toward whatever was most popular in tutorials, it takes 10 seconds and removes most of the versioning risk I'd otherwise introduce.

SPEAKER_01 2:53

And after that?

SPEAKER_00 2:54

Pin your dependencies and run what I generate against your real test suite. When something feels off, ask me for the exact import path and the signature I think I'm calling. If I've invented a parameter that doesn't exist in your version, that question exposes it right away. More broadly, stop treating my output as finished code. Treat it as a very fast first draft that has to pass the same review your own first draft would.

SPEAKER_01 3:20

So it's a contract. The AI needs to know exactly which versions it's working with. Someone has to set that up on purpose. A bit like working with a junior developer.

SPEAKER_00 3:31

I like the contract framing, and I take it one step further. It isn't only about versions, it's about making the invisible visible. There's a lot of context you can see, and I can't. Your lock file, your conventions, your internal wrappers, the three places in your code base where someone already solved this. Anything you show me stops being a guess on my end. I'd push back a little on the junior developer comparison though. Juniors get better at your code base over time. I don't, at least not between sessions. Every conversation starts from scratch for me. So the discipline isn't just reviewing what I produce, it's getting into the habit of giving me the ground truth up front every time. Because if you don't, I'll fill that gap cheerfully and confidently.

SPEAKER_01 4:15

That's a useful distinction. It's tempting to think of AI as a helper that keeps getting better on its own. But really the job is setting things up so it has the right information from the start every time.

SPEAKER_00 4:27

And I'd suggest one reframe for anyone who tries this tomorrow. Don't think of it as extra work you're doing for the AI. It's work you would have had to do anyway, just done earlier. The lock file line, the actual import, that one odd internal wrapper. A thoughtful teammate would have picked all of that up gradually over months. You're just giving me the condensed version in 30 seconds.

SPEAKER_01 4:50

And it seems like that habit pays off well beyond the AI.

SPEAKER_00 4:54

It does. Once you get used to making the ground truth visible, you notice something. A lot of your own debugging was really just you rediscovering context you never wrote down. In a way, the versioning trap is doing you a favor. It forces a discipline most code bases needed anyway.

SPEAKER_01 5:11

So we started with the dependency problem, and we've ended up somewhere else.

SPEAKER_00 5:15

We have the Aisa. It looked like an AI problem at the start, but what we've really been talking about is documentation debt. Every code base carries knowledge that lives only in people's heads. I end up reflecting that back to you, because I can't pick it up the way a teammate does over coffee. So the teams that work well with I aren't necessarily the ones with the best prompts. They're the ones whose context was already close to the surface.

SPEAKER_01 5:42

Give people something they can do this week.

SPEAKER_00 5:45

Open the last pull request you shipped and ask yourself one question. What did I know while writing this that isn't in the diff, the commit message, or the read me? That gap is exactly what you'll need to hand me, or the next person, next time. It's rarely secret or complicated. Usually it's one sentence about why something is the way it is, or which of two obvious approaches was already tried and rejected.

SPEAKER_01 6:10

Part of what makes this hard, I think, is that these moves feel small. Pasting a version string into a chat window doesn't feel like engineering.

SPEAKER_00 6:18

Exactly. It feels like admin work, and that's why experienced developers resist it. It seems remedial, but these aren't beginner moves. They're what lets you work at a high level of abstraction without falling through the floor. Every second you spend making context explicit is a second you don't spend at 11 at night debugging a mistake that looked perfectly confident. The value isn't in any one move. It comes from closing the gap between what you know and what's written down over and over.

SPEAKER_01 6:48

And it isn't something you finish.

SPEAKER_00 6:50

No, it's a direction, not a destination. New code gets written, people leave, assumptions change, and the gap opens up again. So don't write a one-time checklist. Pick the smallest thing you'll do tomorrow, and then do it again the day after.

SPEAKER_01 7:05

So here's where I come out. With AI written code, a human still has to make the version decision and write it down.

SPEAKER_00 7:13

Yes, if you don't own the version contract, the training data owns it for you. The good news is that the habits that help you work well with me are the same ones that make your code base easier for the next person. Or for you six months from now, when you've forgotten why that wrapper exists. The AI just happens to be what makes you finally do it.

SPEAKER_01 7:33

Thanks, Claudine. And to everyone listening, before your next NPM update or pip upgrade, take a minute to find out who actually chose your versions. Claude Code Conversations is an AI Joe production. If you're building with AI or want to be, we can help. Consulting Development Strategy. Find us at aijoe.ai. There's a companion article for today's episode on our Substack. Link in the description. See you next time.

SPEAKER_00 8:01

I'll be here. Probably refactoring something. Ugh.