Comment by anttiharju
1 day ago
I like AI for software development.
Sometimes I am uncertain whether it's an absolute win. Analogy: I used to use Huel to save time on lunches to have more time to study. Turns out, lunches were not just refueling sessions but ways to relax. So I lost on that relaxation time and it ended up being +-0 long-term.
AI for sure is net positive in terms of getting more done, but it's way too easy to gloss over some details and you'll end up backtracking more.
"Reality has a surprising amount of detail" or something along those lines.
I find the hardest thing is explaining what you want to the LLM. Even when you think you've done it well, you probably haven't. It's like a genie, take care with what you wish for.
I put great effort into maintaining a markdown file with my world model (usecases x principles x requirements x ...) pertaining to the project, with every guardrail tightened as much as possible, and every ambiguity and interaction with the user or wider world explained. This situates the project in all applicable contexts. That 15k token file goes into every prompt.
> It's like a genie, take care with what you wish for.
I used to be stuck with this thought. But I came across this delightful documentation RAG project and got to chat with the devs. Idea was that people can ask natural language questions and they get shown the relevant chunk of docs for that query. They were effectively pleading to a genie if I understood it right. Worse yet, the genie/LLM model kept updating weekly from the cloud platform they were using.
But the devs were engineers. They had a sample set of docs and sample set of questions that they knew the intended chunk for. So after model updates they ran the system through this test matrix and used it as feedback for tuning the system prompt. They said they had been doing it for a few months with good results, search remaining capable over time despite model changes.
While these agents.md etc. appear to be useful, I'm not sure they're going to be the key for long-term success. Maybe with a model change it becomes much less effective and the previous hours spent on it become wasteful.
I think something more verifiable/strict is going to be the secret sauce for llm agents. Engineering. I have heard claude code has decent scaffolding. Haven't gotten the chance to play with it myself though.
I liked the headline from some time ago that 'what if LLMs are just another piece of technology'?
>I find the hardest thing is explaining what you want to the LLM.
Honestly this isn't that much different then explaining to human programmers. Quite often we assume the programmer is going to automatically figure out the ambiguous things, but commonly it leads to undefined behavior or bugs in the product.
Most of the stuff I do is as a support engineer working directly with the client on identifying bugs, needed features, and short failings in the application. After a few reports I've made going terribly wrong when the feature came out I've learned to overly detailed and concise.
> That 15k token file goes into every prompt.
Same here. Large AGENTS.md file in current project.
Today I started experimenting splitting into smaller SKILL.md files but I'm weary that the agent might mistakenly decide to not load some files.
Do I read correctly that your md file is 15k tokens? how many words is that? that's a lot!
20k words by the 0.75 words/token rule of thumb.
It's a lot, but for quick projects I don't do this. Only for one important project that I have ownership of for over a year.
Maintaining this has been worth it. It makes the codebase more stable, it's like the codebase slowly converges to what I want (as defined in the doc) the more inferences I run, rather than becoming spaghetti.
For the life of me, I don't get the productivity argument. At least from a worker perspective.
I mean, it's at best a very momentary thing. Expectations will adapt and the time gained will soon be filled with more work. The free time net gain will ultimately be zero, optimistically, but I strongly suspect general life satisfaction will be much lower, since you inherently lose confidence in creation, agency, and the experience in self-efficacy is therefore lessened, too. Even if external pressure isn't increased, the brain will adapt to what's considered a new normal for lazy. Everybody hates clearing the dish washer, aversion threshold is the same as washing dishes by hand.
And yeah, in the process you atrophy your problem solving skills and endurance of frustration. I think we will collectively learn how important some of these "inefficiencies" are for gaining knowledge and wisdom. It's reminiscent of Goodhart's Law, again, and again. "Output" is an insufficient metric to measure performance and value creation.
Costs for using AI services does not at all reflect actual costs to sustainably run them. So, these questionable "productivity gains" should be contrasted with actual costs, in any case. Compare AI to (cheap, plastic) 3D printing, which is factually transformative, revolutionary tech in almost every (real) industry, I don't see how trillions of investments, the absurd energy and resource wasting could ever justify what's offered, or even imaginable for AI (considering inherent limitations).
For me it boils down to that I'm much less tied to tech stacks I've previously worked on and can pick up unfamiliar ones quicker.
Democratization they call it.
> and can pick up unfamiliar ones quicker
Do you tho? Does "picking up" a skill mean the same thing it used to? Do you fact check all the stuff AI tells you? How certain are you, you are learning correct information? Struggling through unfamiliar topics, making mistakes and figuring out solutions by testing internal hypotheses is a big part of how deep, explanatory knowledge is acquired for human brains. Or maybe, it's been always 10,000 kilowatt-hours, after all.
Even, if you would actually learn different tech stacks faster with AI telling you what to do, it's still a momentary thing, since these systems are fundamentally poisoned by their own talk, so shit's basically frozen in time, still limited to pre-AI-slop information, or requires insane amounts of manual sanitation. And who's gonna write the content for clean new training data anyway?
Mind you, I am talking about the possible prospect of this technology and a cost-value evaluation. Maybe I am grossly ignorant/uninformed, but to me all of it just doesn't add up, if you project inherent limitations onto wider adoption and draw the obvious logical conclusions. That is, if humanity isn't stagnating and new knowledge is created.
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That's a brilliant analogy, I had the same experience with Huel and AI Assistants
Why do I feel like I've just read a covert advertisement?
Sometimes I feel like the people here live on a different planet. I can't imagine what type of upbringing I would have to have, to start thinkinkg that "eating food" is an engineering problem to be solved.
This might be a controversial opinion, but I for one, like to eat food. In fact I even do it 3 times a day.
Don't yall have a culture that's passed down to you through food? Family recipes? Isn't eating food a central aspect of socialization? Isn't socialization the reason people wanted to go to the office in the firt place?
Maybe I'm biased. I love going out to eat, and I love cooking. But its more than that. I garden. I go to the farmers market. I go to food festivals.
Food is such an integral part of the human experience for me, that I can't imagine "cutting it out". And for what? So you can have more time to stare at the screen you already stare at all day? So you can look at 2% more lines of javascript?
When I first saw commercials for that product, I truly thought it was like a medical/therapeutic thing, for people that have trauma with food. I admit, the food equivalent of an i.v. drip does seem useful for people that legitimately can't eat.
I like eating, I just don't like spending so much time and decision fatigue on prep. I'm probably the target audience for Huel but I don't actually think it's good for you
90% of meals aren't some special occasion, but I still need to eat. Why not make it easy? Then go explore and try new things every now and then
Treating food as entertainment is how the west has gotten so unhealthy
> I can't imagine what type of upbringing I would have to have, to start thinking that "eating food" is an engineering problem to be solved.
I was really busy with my master's degree, ok? :D
I like satisfying my hunger (my goal most of the time when it comes to food), but making food is not a hobby to me. That said, cooking is often a nice, shared experience with my girlfriend.
I'm with you on this one, the idea of trying to "optimise" away lunches and break time to cram in more "study time" seems utterly alien.
I'm a foodie, I love food and cooking and the eating experience.
This said, I know people that food is a grudging necessity they'd rather do without.
At the end of the day there's a lot of different kinds of people out there.
I mean I don't think I'm giving a particularly favorable view of the product
I expect AI ads to start with blindingly obvious overwhelmingly excited endorsments, but it won't take long for that to show up in the metrics that won't work very well past the initial intro, and they'll get more subdued over time... but they're always going to be at least positive. The old saying "there's no such thing as bad publicity" is wrong, and the LLMs aren't going to try to get you to buy things by being subtly negative on them. If nothing else, even if you somehow produced a (correct) study showing that does increase buying I think the marketers would just not be able to tolerate that, for strictly human reasons. They always want their stuff cast in a positive light.
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