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by bandrami 107 days ago
That's only certain if investments in tech infrastructure always led to productivity increases. But sometimes they just don't. Lots of firms spent a lot of money on blockchain five years ago, for instance, and that money is just gone now.
2 comments

I find it odd the universal assumption that AI is going to be good for productivity

The loss of skills, complete loss of visibility and experience with the codebase, and the complete lack of software architecture design, seems like a massive killer in the long term

I have a feeling that we're going to see productivity with AI drop through the floor

I'd claim the opposite. Better models design better software, and quickly better software than what most software developers were writing.

Just yesterday I asked Opus 4.6 what I could do to make an old macOS AppKit project more testable, too lazy to even encumber the question with my own preferences like I usually do, and it pitched a refactor into Elm architecture. And then it did the refactor while I took a piss.

The idea that AI writes bad software or can't improve existing software in substantial ways is really outdated. Just consider how most human-written software is untested despite everyone agreeing testing is a good idea simply because test-friendly arch takes a lot of thought and test maintenance slow you down. AI will do all of that, just mention something about 'testability' in AGENTS.md.

OK so this comes back to the question I started this subthread with: where is this better software? Why isn't someone selling it to me? I've been told for a year it's coming any day now (though invariably the next month I'm told last month's tools were in fact crap and useless compared to the new generation so I just have to wait for this round to kick in) and at some point I do have to actually see it if you expect me to believe it's real.
How would you know if all software written in the last six months shipped X% faster and was Y% better?

Why would you think you have your finger on the pulse of general software trends like that when you use the same, what, dozen apps every week?

Just looking at my own productivity, as mere sideprojects this month, I've shipped my own terminal app (replaced iTerm2), btrfs+luks NAS system manager, overhauled my macOS gamepad mapper for the app store, and more. All fully tested and really polished, yet I didn't write any code by hand. I would have done none of that this month without AI.

You'd need some real empirics to pick up productivity stories like mine across the software world, not vibes.

It's on the people pushing AI as the panacea that has changed things to show workings. Not someone saying "I've not seen evidence of it". Otherwise it's "vibes" as you put it.
Right, I'm sympathetic to the idea that LLMs facilitate the creation of software that people previously weren't willing to pay for, but then kind of by definition that's not going to have a big topline economic impact.
Well, we don't know - that's capturing 2 scenarios: software that whose impact is low as reflected by lack of investment and legitimately useful improvements that just weren't valued (fix slow code, reduce errors and increase uptime, address security concerns) because the cost was not appreciated / papered over by patches / company hasn't been bitten yet
Why did you add that "weren't willing to pay for" condition?

Most of the software I replaced was software I was paying for (iStat Menus, Wispr Flow, Synology/Unraid). That I was paying for a project I could trivially take on with AI was one of the main incentives to do it.

Here's an example: https://eudaimonia-project.netlify.app/

I'm happy to sell it to you, though it is also free. I guided Claude to write this in three weeks, after never having written a line of JavaScript or set up a server before. I'm sure a better JavaScript programmer than I could do this in three weeks, but there's no way I could. I just had a cool idea for making advertising a force for good, and now I have a working version in beta.

I'd say it is better software, but better is doing a lot of heavy lifting there. Claude's execution is average and always will be, that's a function of being a prediction engine. But I genuinely think the idea is better than how advertising works today, and this product would not exist at all if I had to write it myself. And I'm someone who has written code before, enough that I was probably a somewhat early adopter to this whole thing. Multiply that by all the people whose ideas get to live now, and I'm sure some ideas will prove to be better even with average execution. Like an llm, that's a function of statistics.

In glad you made something with it you wanted to make, and as a fan of Aristotle I'm always happy to see the word eudaimonia out there. Best of luck. That said I don't understand what this does or why I would want the tokens it mentions.
Yeah, I gotta make a video walkthrough. Its basically a goal tracker combined with an ad filter - write what you want out of life and block ads, it replaces them with ads that actually align with your long term goals instead of distracting from them. The tokens let you add ads to the network, though you also get some for using the goal tracker.
And now you have no idea how any of the code works

AI writes bad software by virtue of it being written by the AI, not you. No actual team member understands what's going on with the code. You can't interrogate the AI for its decision making. It doesn't understand the architecture its built. There's nobody you can ask about why anything is built the way it is - it just exists

Its interesting watching people forget that the #1 most important thing is developers who understand a codebase thoroughly. Institutional knowledge is absolutely key to maintaining a codebase, and making good decisions in the long term

Its always been possible to trade long term productivity for short term gains like this. But now you simply have no idea what's going on in your code, which is an absolute nightmare for long term productivity

You can read as much or as little of the code as you want.

The status quo was that I have no better understanding of code I haven't touched in a year, or code built by other people. Now I have the option to query the code with AI to bootstrap my understanding to exactly the level necessary.

But you're wrong on every claim about LLM capabilities. You can ask the AI exactly why it decided on a given design. You can ask it what the best options were and why it chose that option. You can ask it for the trade-offs.

In fact, this should be part of your Plan feedback loop before you move to Implementation.

You can ask the AI why, but its answer doesn't come from any kind of genuine reasoning. It doesn't know why it did anything, because it doesn't exist as a sentient being. It just makes something up that sounds good

If you choose to take AI reasoning at face value, you're choosing to accept pretty strong technical debt

My own observation is that the initial boost to productivity results in massive crippling technical debt.
That's just because everyone is misusing AI. If you ask AI to do a job and you have no idea what it did, you lost ownership, which means you're asking to be replaced. You need to own the task. If you fully delegate your task to anyone else or to AI, you no longer know what's going on. AI does not necessarily produce more tech debt, but AI might do things you don't expect because it lacks context and specificity to perform accurately.
Having the productivity "drop through the floor" is a bit hyperbolic, no? Humans are still reviewing the PRs before code merge at least at my company (for the most part, for now).
I don't know that it's likely but it's certainly a plausible outcome. If tooling keeps getting built for this and the financial music stops it's going to take a while for everybody to get back up to speed

Remember this famously happened before, in the 1970s

There's an actual working product now, albeit one which is currently loss leading. In software world at least there is definitely enough value for it to be used even if it's just better search engine. I'm not sure why it would disappear if the financial music stops as opposed to being commoditised.
Because there's cheaper ways to get an equally good search engine? But yes I imagine some amount of inference will continue even in an AI Winter 3.0 scenario.
Ironically, abstraction bloat eats away any infra gains. We trade more compute to allow people less in tune with the machine to get things done, usually at the cost of the implementation being eh... Suboptimal, shall we say.
I think there's a broad category error where people see that every gain has been an abstraction (true) but conclude from that that every abstraction will be a gain (dubious)