Large PRs could follow the practices that the Linux kernel dev lists follow. Sometimes large subsystem changes could be carried separately for a while by the submitter for testing and maintenance before being accepted in theory, reviewed, and if ready, then merged.
While the large code changes were maintained, they were often split up into a set of semantically meaningful commits for purposes of review and maintenance.
With AI blowing up the line counts on PRs, it's a skill set that more developers need to mature. It's good for their own review to take the mass changes, ask themselves how would they want to systematically review it in parts, then split the PR up into meaningful commits: e.g. interfaces, docs, subsets of changed implementations, etc.
Nobody wants to review AI-generated code (unless we are paid for doing so). Open source is fun, that's why people do it for free... adding AI to the mix is just insulting to some, and boring to others.
Like, why on earth would I spent hours reviewing your PR that you/Claude took 5 minutes to write? I couldn't care less if it improves (best case scenario) my open source codebase, I simply don't enjoy the imbalance.
Why do you care how much effort it took the engineer to make it? If there was a huge amount of tedium that they used Claude Code for, then reviewed and cleaned up so that it’s indistinguishable from whatever you’d expect from a human; what’s it to you?
Not everyone has the same motivations. I’ve done open source for fun, I’ve done it to unblock something at work, I’ve done it to fix something that annoys me.
If your project is gaining useful functionality, that seems like a win.
Because sometimes programming is an art and we want people to do it as if it was something they cared about. I play chess and this is a bit like that. Why do I play against humans? Because I want to face another person like me and see what strategies they can come up with.
Of course any chess bot is going to play better, but that's not the point
> With AI blowing up the line counts on PRs,
Well, the process you’re describing is mature and intentionally slows things down. The LLM push has almost the opposite philosophy. Everyone talks about going faster and no one believes it is about higher quality.
Go slow to go fast. Breaking up the PR this way also allows later humans and AI alike to understand the codebase. Slowing down the PR process with standards lets the project move faster overall.
If there is some bug that slips by review, having the PR broken down semantically allows quicker analysis and recovery later for one case. Even if you have AI reviewing new Node.js releases for if you want to take in the new version - the commit log will be more analyzable by the AI with semantic commits.
Treating the code as throwaway is valid in a few small contexts, but that is not the case for PRs going into maintained projects like Node.js.
TBF, most of the AI code I've reviewed isn't significantly different than code I've seen from people... in fact, I've seen significantly worse from real people.
The fact is, it's useful as a tool, but you still should review what's going on/in. That isn't always easy though, and I get that. I've been working on a TS/JS driver for MS-SQL so I can use some features not in other libraries, mostly bridging a Rust driver (first Tiberious, then mssql-client), the clean abstraction made the switch pretty quick... a fairly thorough test suite for Deno/Node/Bun kapt the sanity in check. Rust C-style library with FFI access in TS/JS server environment.
My hardest part, is actually having to setup a Windows Server to test the passswordless auth path (basically a connection string with integrated windows auth). I've got about 80 hours of real time into this project so far. And I'll probably be doing 2 followups.. one with be a generic ODBC adapter with a similar set of interfaces. And a final third adapter that will privide the same methods, but using the native SQLite underneath but smothing over the differences.
I'm leveraging using/dispose (async) instead of explicit close/rollback patterns, similar to .Net as well as Dapper-like methods for "Typed" results, though no actual type validation... I'd considered trying to adapt Zod to check at least the first record or all records, and may still add the option.
All said though, I wouldn't have been able to do so much with so relatively little time without the use of AI. You don't have to sacrifice quality to gain efficiency with AI, but you do need to take the time to do it.