very annoyed they aren't showing fable on the graph.
868 karma · joined August 14, 2011
That means, use LLMs to build whole sites and then dig in where you are curious. Look at the code, ask your LLM how it works and keep digging until you understand how the program is constructed. A benefit is that you're looking at a REAL program, not a toy example. And also, if your program stops working well (bugs or perf issues), you can debug it with the LLM and start asking it to teach you why things were slow and the concepts behind it.
I think you can basically build your own on-the-fly curriculum these days and do it with a real-world example WHILE you build cool stuff.
I think the biggest barrier will be motivation - many people don't want to be curious, and they just want it to work. they won't learn anything that way.
the view for the new house is insane! congrats, well earned!
and if you start simplifying the more complicated test later, you may not realize that you're accidentally deleting checks that don't exist anywhere else other than incidentally here. So it's less clear what's important without thinking it through each time.
now all that to say I don't think it's strictly that big of a deal either way - there's always tons of room for taste that can make one or the other way better in practice. But that was my gut-reaction when reading your comment.
1. AI is really helpful for a lot of things
2. to the extent that AI can do something perfectly for us, we probably shouldn't try to force people to "learn" it the hard way
3. people who don't want to learn won't, and will suffer naturally later
4. if the material didn't need to be learned anyway, then using AI to do it for them is a win. that's how the real world works anyway.
5. if AI makes some knowledge obsolete, we should stop trying to teach it.
i think the only thing for the teachers to do is to properly warn students of the consequences of using AI to skip learning ahead of time (because by the time the natural consequences hit, it's too late), and to do their best to devise tests that incentivize the right knowledge, while also showing how to use AI properly.
the problem is that the education system isn't set up to change this quickly so I don't really know how they are going to properly adjust every semester
it's the same as toll booth operators complaining about fastpass
So i wrote a program that just made it look like I cleared memory and it worked like a charm.
I don't remember if I even stored anything that could be constituted cheating but it was more about the satisfaction of knowing I outsmarted them, heh.
That said, it still feels like they are unnecessarily hobbling their project. LLMs are tools and they can help you think, research, and code. You can overuse them, yes, but you should embrace them where they help.
not accepting bun's PR for other reasons is totally fine (sounds like it's a core change where more thinking needs to be done), but simply banning all LLM authored PRs is unnecessarily restrictive. Just focus on the quality of the work.
sure, there's a lot of compliance/legal concerns, but AI is probably already better at reading all the relevant information and encoding that into a system than humans.
I don't think a non-technical person is going to one-shot it, but a technical person could today. The biggest issue would be marketing and maintenance (companies aren't going to buy from a single random person who might abandon the project at a moment's notice)
i like the idea of having an actual document because you could actually compare the before and after versions if you wanted to confirm things changed as intended when you gave feedback
if you really want to sell it, you should probably make sure that you have customers willing to pay, which means talking to potential customers and getting them on a waitlist. i think it's usually more likely that other people don't care about your software like you do (because you built it to be exactly what you want and know how it works) and even then, aren't willing to pay to use it (or pay very much)
if you're not very concerned about making money and mostly just want something nice for yourself that other people _might_ care about, then sure, go for it! i build software like that all the time
but also I think the interesting thing is that people didn't jump on MCP immediately after it launched - it seemed to go almost unnoticed until February. Very unusual for AI tech - I guess it took time for servers to get built, clients to support the protocol, and for the protocol itself to go through a few revisions before people really understood the value.
I wonder what the optimal form factor is. Like what if your AI could /suggest/ connecting with some service? Like your AI is browsing a site and can discover the "official" MCP server (like via llms.txt). It then shows a prompt to the user - "can I access your data via X provider?". you click "yes", then it does the OAuth redirect and can immediately access the necessary tools. Also being able to give specific permissions via the OAuth flow would be really nice.
LLMs seem pretty good at figuring out these things when given a good feedback loop, and if the DSL truly makes complex programs easier to express, then LLMs could benefit from it too. Fewer lines of code can mean less context to write the program and understand it. But it has to be a good DSL and I wouldn't be surprised if many are just not worth it.
Like, oil is insanely caloric and can accidentally add hundreds of calories, but it's nearly impossible to eat too many greens.
Once you learn this, then the tracking is just to keep you honest - your brain knows what to do but it lies to you when it wants to bend the rules and those little cheats add up enough to throw off the whole diet.