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AI makes the easy part easier and the hard part harder

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201–210 of 382 posts

Re: AI makes the easy part easier and the hard part harder

#201
post #186
post #18

I think it makes the annoying part less annoying? Also re: "I spent longer arguing with the agent and recovering the file than I would have spent writing the test myself." In my humble experience arguing with an LLM is a waste of time, and no-one should be spending time recovering files. Just do small changes one at a time, commit when you get something working, and discard your changes and try again if it doesn't. I…

Once you start arguing, it's time to start a new prompt with new instructions

Or, as I prefer, go back in the conversation and edit / add more context so that it wouldn’t go off the wrong track in the first place.

Re: AI makes the easy part easier and the hard part harder

#202
post #24

Earlier quoted context omitted.

I call these "embarrassingly solved problems". There are plenty of examples of emulators on GitHub, therefore emulators exist in the latent spaces of LLMs. You can have them spit one out whenever you want. It's embarrassingly solved. There are no examples of what you tried to do.

Stop repeating this trope. It can spit out something you've never built before this is utterly clear and demonstrated and no longer really up for debate. Claude code has never been built before claude code. Yet all of claude is being built by claude code. Why are people clinging to these useless trivial examples and using it to degrade AI? Like literally in front of our very eyes it can build things that aren't just…

I think we are in violent agreement and I hope that after reading this you think so too.

I don't disagree that LLMs can produce novel products, but let's decompose Claude Code into its subproblems.

Since (IIRC) Claude Code's own author admits he built it entirely with Claude, I imagine the initial prompt was something like "I need a terminal based program that takes in user input, posts it to a webserver, and receives text responses from the webserver. On the backend, we're going to feed their input to a chatbot, which will determine what commands to run on that user's machine to get itself more context, and output code, so we need to take in strings (and they'll be pretty long ones), sanitize them, feed them to the chatbot, and send its response back over the wire."

Everything here except the LLM has been done a thousand times before. It composed those building blocks in novel ways, that's what makes it so good. But I would argue that it's not going to generate new building blocks, and I really mean for my term to sit at the level of these subproblems, not at the level of a shipped product.

I didn't mean to denigrate LLMs or minimize their usefulness in my original message, I just think my proposed term is a nice way to say "a problem that is so well represented in the training data that it is trivial for LLMs". And, if every subproblem is an embarrassingly solved problem, as in the case of an emulator, then the superproblem is also an ESP (but, for emulators, only for repeatedly emulated machines, like GameBoy -- A PS5 emulator is certainly not an ESP).

Take this example: I wanted CC to add Flying Edges to my codebase. It knew where to integrate its solution. It adapted it to my codebase beautifully. But it didn't write Flying Edges because it fundamentally doesn't know what Flying Edges is. It wrote an implementation of Marching Cubes that was only shaped like Flying Edges. Novel algorithms aren't ESPs. I had to give it access to a copy of VTK's implementation (BSD license) for it to really get it, then it worked.

Generating isosurfaces specifically with Flying Edges is not an ESP yet. But you could probably get Claude to one shot a toy graphics engine that displays Suzanne right now, so setting up a window, loading some gltf data, and displaying it definitely are ESPs.

Re: AI makes the easy part easier and the hard part harder

#203

> Reading and understanding other people's code is much harder than writing code. I keep seeing this sentiment repeated in discussions around LLM coding, and I'm baffled by it. For the kind of function that takes me a morning to research and write, it takes me probably 10 or 15 minutes to read and review. It's obviously easier to verify something is correct than come up with the correct thing in the first place. And…

[deleted]

Re: AI makes the easy part easier and the hard part harder

#204
post #147

Earlier quoted context omitted.

> But in order to write the code, you might have to try 4 different top-level approaches until you figure out the one that works , try integrating with a function from 3 different packages until you find the one that works properly If you haven’t spent the time to try the different approaches yourself, tried the different packages etc., you can’t really judge if the code you’re reading is really the appropriate thing…

The goal isn't usually to determine whether the function is the perfect optimal version of the function that could ever exist, if the package it integrates with the the best possible package out of the 4 mainstream options, or to become totally and intimately familiar with them to ensure it's as idiomatic as possible or whatever. You're just making sure it works correctly and that you understand how. Not superficiall…

> What you're describing sounds closer to studying the Talmud than to reading and reviewing most code.

https://www.joelonsoftware.com/2000/05/26/reading-code-is-li...

Most human written code has 0 (ZERO!) docs. And if it has them, they're inaccurate or out of date or both.

Lots of code is simple and boring but a fair amount isn't and reading it is non trivial, you basically need to run it in your head or do step by step debugging in multiple scenarios.

Re: AI makes the easy part easier and the hard part harder

#205
> My friend's panel raised a point I keep coming back to: if we sprint to deliver something, the expectation becomes to keep sprinting. Always. Tired engineers miss edge cases, skip tests, ship bugs. More incidents, more pressure, more sprinting. It feeds itself.

Sorry but this is the whole point of software engineering in a company. The aim is to deliver value to customers at a consistent pace.

If a team cannot manage their own burnout or expectations with their stakeholders then this is a weak team.

It has nothing to do with using ai to make you go faster. Ai does not cause this at all.

Re: AI makes the easy part easier and the hard part harder

#206
I think this is the wrong mental model. The correct one is:

'AI makes everything easier, but it's a skill in itself, and learning that skill is just as hard as learning any other skill.'

For a more complete understand, you also have to add: 'we're in the ENIAC era of AI. The equivalents of high-level languages and operating systems haven't yet been invented.'

I have no doubt the next few years will birth a "context engineering" academic field, and everything we're doing currently will seem hopelessly primitive.

My mind changed on this after attempting complex projects—with the right structure, the capabilities appear unbounded in practice.

But, of course, there is baked-in mean reversion. Doing the most popular and uncomplicated things is obviously easier. That's just the nature of these models.

Re: AI makes the easy part easier and the hard part harder

#207
post #206

I think this is the wrong mental model. The correct one is: 'AI makes everything easier, but it's a skill in itself, and learning that skill is just as hard as learning any other skill.' For a more complete understand, you also have to add: 'we're in the ENIAC era of AI. The equivalents of high-level languages and operating systems haven't yet been invented.' I have no doubt the next few years will birth a "context e…

Funny how people only looks at the easy part, but not the cost part.

"I did it with AI" = "I did it with an army of CPU burning considerable resources and owned by a foreign company."

Give me an AI agent that I own and operate 100%, and the comparison will be fair. Otherwise it's not progress, but rather a theft at planetary scale.

Re: AI makes the easy part easier and the hard part harder

#208

Earlier quoted context omitted.

Its license washing. The code is great because its already a problem solved by someone else. The AI can spit out the solution with no license and no attribution and somehow its legal. I hope American tech legislation holds that same energy once others start taking American IP and spitting it back out with no license or attribution.

I've seen many discussions stating patent hoarding has gone too far, and also that copyright for companies have gone way too far (even so much that Amazon can remove items from your purchase library if they lose their license to it). Then AI begins to offer a method around this over litigious system, and this becomes a core anti-AI argument. I do think it's silly to think public code (as in, code published to the pub…

I don't think people would care as much about AI reusing code or images or text so directly if people were allowed to do so too. The big problem I think comes in when AI is allowed to do things that humans can't. Right now if I publish a book that is 70% somebody else's book but slightly rehashed with certain key phrases and sentences or more as perfect copies, I would get sued and I would lose. Right now though if an AI does it not only is it unlikely to get litigated at all, but even if it does most of the time it will come down to "whoops AI did it, but neither the publisher nor the AI developer is individually responsible enough to recover any significant loses from."

Re: AI makes the easy part easier and the hard part harder

#209
post #36

Earlier quoted context omitted.

The wrinkle is that the AI doesn't have a truly global view, and so it slowly degrades even good structure, especially if run without human feedback and review. But you're right that good structure really helps.

Yet it still fumbles even when limiting context. Asked it to spot check a simple rate limiter I wrote in TS. Super basic algorithm: let one action through every 250ms at least, sleeping if necessary. It found bogus errors in my code 3 times because it failed to see that I was using a mutex to prevent reentrancy. This was about 12 lines of code in total. My rubber duck debugging session was insightful only because I h…

I would love to see that code.

Re: AI makes the easy part easier and the hard part harder

#210
post #181

Earlier quoted context omitted.

Its license washing. The code is great because its already a problem solved by someone else. The AI can spit out the solution with no license and no attribution and somehow its legal. I hope American tech legislation holds that same energy once others start taking American IP and spitting it back out with no license or attribution.

This is why its astonishing to me that AI has passed any legal department. I regularly see AI output large chunks of code that are 100% plagiarised from a project - its often not hard to find the original source by just looking up snippets of it. 100s of lines of code just completely stolen Ai doesn't actually wash licenses, it literally can't. Companies are just assuming they're above the law

This is oft-repeated but never backed up by evidence. Can you share the snippet that was plagiarized?
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