Whenever I have a model fix something new I ask it to update the markdown implementation guides I have in the docs folder in my projects. I add these files to context as needed. I have one for implementing routes and one for implementing backend tests and so on.

They then know how to do stuff in the future in my projects.

Key words are these.

> They then know how to do stuff in the future in my projects.

No. No, they don't. Every new session is a blank slate, and you have to feed those markdown files manually to their context.

The AI hype folks write massive fan fiction style novellas that don't have any impact.

But there's middle ground where you tell the agent the specific things about your repo that it doesn't know based on its training. Like if your application has a specific way to run tests headless or it's compiled a certain way that's not the default average.

Unless, of course, the phase of the moon is wrong and Claude itself is stupid beyond all reason

AGENTS.md exists, Codex and Crush support it directly. Copilot, Gemini and Claude have their own variants and their /init commands look at AGENTS.md automatically to initialise the project.

Nobody is feeding aything "manually" to Agents. Only people who think "AI" is a web page do that.

All of them often can't even find/read relevant docs in a new session without prompting

And of course it's up to the developer to keep the documentation up to date. Just like when working with humans. Stuff don't magically document itself.

Yes "good code is self-documenting", but it still takes ages to find anything without docs to tell you the approximate direction.

It's literally a text file the agent can create and update itself. Not hard. Try it.

Humans actually learn from codebases they work with. They don't start with a clean slate every time they wake up in the morning. They know where to find information and how to search for them. They don't need someone to constantly update docs to point to changes.

> but it still takes ages to find anything without docs to tell you the approximate direction.

Which humans, unsurprisingly, can do without wiping their memory every time.

That sounds a lot like '50 First Dates' but for programming.

Yes, this is something people using LLMs for coding probably pick up on the first day. They're not "learning" as humans do obviously. Instead, the process is that you figure out what was missing from the first message you sent where they got something wrong, change it, and then restart from beginning. The "learning" is you keeping track of what you need to include in the context, how that process exactly works, is up to you. For some it's very automatic, and you don't add/remove things yourself, for others is keeping a text file around they copy-paste into a chat UI.

This is what people mean when they say "you can kind of do "learning" (not literally) for LLMs"

It's functionally working the same as learning.

If you look at it like a black box, then you can't tell the difference from the input and output.

For example, let's say LLMs did not have examples of chess gameplay examples in their training data. Would one be able to have an LLM play chess by listing the rules and examples in the context? Perhaps, to some extent, but I believe it would be much worse than if it was part of the training (which of course isn't great either).

We'll fix that, eventually.

- don't have career growth that you can feel good about having contributed to

Humans are on the verge of building machines that are smarter than we are. I feel pretty goddamned awesome about that. It's what we're supposed to be doing.

- don't have a genuine interest in accomplishment or team goals

Easy to train for, if it turns out to be necessary. I'd always assumed that a competitive drive would be necessary in order to achieve or at least simulate human-level intelligence, but things don't seem to be playing out that way.

- have no past and no future. When you change companies, they won't recognize you in the hall.

Or on the picket line.

- no ownership over results. If they make a mistake, they won't suffer.

Good deal. Less human suffering is usually worth striving for.

It's also the premise of The Matrix. I feel pretty goddamned uneasy about that.

In any case, the matrix wasn't my inspiration here, but it is a pithy way to describe the concept. It's hard to imagine how humans maintain relevancy if we really do manage to invent something smarter than us. It could be that my imagination is limited though. I've been accused of that before.

Have you ever spent any time around children? How about people who think they're accomplishing a great mission by releasing truly noxious ones on the world?

You just dismissed the entire notion of accountability as an unnecessary form of suffering, which is right up there with the most nihilistic ideas ever said by, idk, Dostoevsky's underground man or Raskolnikov.

Don't waste your life on being the Joker.

> Humans are on the verge of building machines that are smarter than we are.

You're not describing a system that exists. You're describing a system that might exist in some sci-fi fantasy future. You might as well be saying "there's no point learning to code because soon the rapture will come".

Most AI experts not heavily invested in the stocks of inflated tech companies seem to agree that current architectures cannot reach AGI. It's a sci-fi dream, but hyping it is real profitable. We can destroy ourselves plenty with the tech we already have, but it won't be a robot revolution that does it.

What I really need to ask an LLM for is a pointer to a forum that doesn't cultivate proud exhibitions of ignorance, Luddism, and general stupidity at the level exhibited by commenters in this entire HN story, and in this subthread in particular.

We already had one Reddit, we didn't need two.

Why?

It's a tool, not an intelligent being

Next year there will be AI screwdriver your employer force you to use.

Then I realised that this will actually happen, and was sadly reminded we’re now in the post-sarcasm era.