AI tooling must be disclosed for contributions

I’m loving today. HN’s front page is filled with some good sources today. No nonsense sensationalism or preaching AI doom, but more realistic experiences.

I’ve completely turned off AI assist on my personal computer and only use AI assist sparingly on my work computer. It is so bad at compound work. AI assist is great at atomic work. The rest should be handled by humans and use AI wisely. It all boils down back to human intelligence. AI is only as smart as the human handling it. That’s the bottom line.

> AI is only as smart as the human handling it.

I think I'm slowly coming around to this viewpoint too. I really just couldn't understand how so many people were having widely different experiences. AI isn't magic; how could I have expected all the people I've worked with who struggle to explain stuff to team members, who have near perfect context, to manage to get anything valuable across to an AI?

I was original pretty optimistic that AI would allow most engineers to operate at a higher level but it really seems like instead it's going to massively exacerbate the difference between an ok engineer and a great engineer. Not really sure how I feel about that yet but at-least I understand now why some people think the stuff is useless.

I've been struggling to apply AI on any large scale at work. I was beginning to wonder if it was me.

But then my wife sort of handed me a project that previously I would have just said no to, a particular Android app for the family. I have instances of all the various Android technologies under my belt, that is, I've used GUI toolkits, I've used general purpose programming languages, I've used databases, etc, but with the possible exception of SQLite (which even that is accessed through an ORM), I don't know any of the specific technologies involved with Android now. I have never used Kotlin; I've got enough experience that I can pretty much piece it together when I'm reading it but I can't write it. Never used the Android UI toolkit, services, permissions, media APIs, ORMs, build system, etc.

I know from many previous experiences that A: I could definitely learn how to do this but B: it would be a many-week project and in the end I wouldn't really be able to leverage any of the Android knowledge I would get for much else.

So I figured this was a good chance to take this stuff for a spin in a really hard way.

I'm about eight hours in and nearly done enough for the family; I need about another 2 hours to hit that mark, maybe 4 to really polish it. Probably another 8-12 hours and I'd have it brushed up to a rough commercial product level for a simple, single-purpose app. It's really impressive.

And I'm now convinced it's not just that I'm too old a fogey to pick it up, which is, you know, a bit of a relief.

It's just that it works really well in some domains, and not so much in others. My current work project is working through decades of organically-grown cruft owned by 5 different teams, most of which don't even have a person on them that understands the cruft in question, and trying to pull it all together into one system where it belongs. I've been able to use AI here and there for some stuff that is still pretty impressive, like translating some stuff into psuedocode for my reference, and AI-powered autocomplete is definitely impressive when it correctly guesses the next 10 lines I was going to type effectively letter-for-letter. But I haven't gotten that large-scale win where I just type a tiny prompt in and see the outsized results from it.

I think that's because I'm working in a domain where the code I'm writing is already roughly the size of the prompt I'd have to give, at least in terms of the "payload" of the work I'm trying to do, because of the level of detail and maturity of the code base. There's no single sentence I can type that an AI can essentially decompress into 250 lines of code, pulling in the correct 4 new libraries, and adding it all to the build system the way that Gemini in Android Studio could decompress "I would like to store user settings with a UI to set the user's name, and then display it on the home page".

I think I recommend this approach to anyone who wants to give this approach a fair shake - try it in a language and environment you know nothing about and so aren't tempted to keep taking the wheel. The AI is almost the only tool I have in that environment, certainly the only one for writing code, so I'm forced to really exercise the AI.

It's a matter of the tools not getting there though. If there was a summarization system that could compress down the structure and history of the system you are working on in a way that could then extract out a half-filled context window of the relevant bits of the code base and architecture for the task (in other words, generate that massive prompt for you), then you might see the same results that you get with Android apps.

The reason being that the boilerplate Android stuff is effectively given for free and not part of the context as it is so heavily represented in the training set, whereas the unique details of your work project is not. But finding a way to provide that context, or better yet fine-tune the model on your codebase, would put you in the same situation and there's no reason for it to not deliver the same results.

That it is not working for you now at your complex work projects is a limitation of tooling, not something fundamental about how AI works.

Aside: Your recommendation is right on. It clicked for me when I took a project that I had spent months of full-time work creating in C++, and rewrote it in idiomatic Go, a language I had never used and knew nothing about. It took only a weekend, and at the end of the project I had reviewed and understood every line of generated code & was now competent enough to write my own simple Go projects without AI help. I went from skeptic to convert right then and there.

I agree that the level of complexity of task it can do is likely to rise over time. I often talk about the "next generation" of AI that will actually be what we were promised LLMs would be, but LLMs architecturally are just not suited for. I think the time is coming when AIs "truly" (for some definition of truly) will understand architecture and systems in a way that LLMs don't and really can't, and will be able to do a lot more things than they can now, though when that will be is hard to guess. Could be next year, or AI could stall out now where it is now for the next 10. Nobody knows.

However, the information-theoretic limitation of expressing what you want and how anyone, AI or otherwise, could turn that into commits, is going to be quite the barrier, because that's fundamental to communication itself. I don't think the skill of "having a very, very precise and detailed understanding of the actual problem" is going anywhere any time soon.

Yes, but:

(1) The process of creating "a very, very precise and detailed understanding of the actual problem" is something AI is really good at, when partnered with a human. My use of AI tools got immensely better when I figured out that I should be prompting the AI to turn my vague short request into a detailed prompt, and then I spend a few iteration cycles fixing up before asking the agent to do it.

(2) The other problem of managing context is a search and indexing problem, which we are really, really good at and have lots of tools for, but AI is just so new that these tools haven't been adapted or seen wide use yet. If the limitation of the AI was its internal reasoning or training or something, I would be more skeptical. But the limitation seems to be managing, indexing, compressing, searching, and distilling appropriate context. Which is firmly in the domain of solvable, albeit nontrivial problems.

I don't see the information theoretic barrier you refer to. The amount of information an AI can keep in its context window far exceeds what I have easily accessible to my working memory.

The information theoretic barrier is in the information content of your prompt, not the ability of the AI to expand it.

But then I suppose I should learn from my own experiences and not try to make information theoretic arguments on HN, since it is in that most terrible state where everyone thinks they understand it because they use "bits" all the time, but in fact the average HN denizen knows less than nothing about it because even their definition of "bit" actively misleads them and that's about all they know.