201–210 of 384 posts
“Hey AI, clone yourself” We’re getting there..
“Hey Claude, you have a bunch of skills defined, some mcps, and memory filled with useful stuff. I want to use you on a machine accessible over SSH at , can you clone yourself over?”
Lost me at "I’m building something right now. I won’t get into the details. You don’t give away the idea."
Fair enough. I know how that reads. But when anyone with a laptop and a subscription can ship production software in a weekend, the architecture and the idea start to matter a lot more. The technical details in the post are real. I just can't share the what yet. Take it or leave it.
Earlier quoted context omitted.
I learn a lot faster now with LLMs. You could learn the windows APIs much faster if you wanted to learn them
How is this faster than just reading the documentation? Given that LLMs hallucinate, you have to double check everything it says against the docs anyway
The trick to learning with LLMs is to treat them as one of multiple sources of information, and work with those sources to build your own robust mental of how things work.
If you exclusively rely on official documentation you'll miss out on things that the documentation doesn't cover.
I'm glad I am no longer in tech because I just don't want to do this. This is not a dig at AI. If I take this article at face value, AI makes people more productive, assuming they have the taste and knowledge to steer their agents properly. And that's possibly a good thing even though it might have temporary negative side effects for the economy. >But the AI is writing the traversal logic, the hashing layers, the wat…
There's several factors which are super depressing:
1. Economic productivity, and what it means for a company to be successful have become detached from producing good high quality products. The stock market is the endgame now
2. AI is attempting to strongly reject the notion that developers understanding their code is good. This is objectively wrong, but its an intangible skill that makes developers hard to replace, which is why management is so desperate for it
3. Developers had too much individual power, and AI feels like a modern attempt at busting the power of the workforce rather than a genuine attempt at a productivity increase
4. It has always been possible to trade long term productivity for short term gains. Being a senior developer means understanding this tradeoff, and resisting management pressure to push something out NOW that will screw you over later
5. The only way AI saves time in the long term is if you don't review its output to understand it as well as if you'd written it yourself. Understanding the code, and the large scale architecture is critical. Its a negative time savings if you want to write high-long-term-productivity code, because we've introduced an extra step
6. Many developers simply do not care about writing good code unfortunately, you just crank out any ol' crap. As long as you don't get fired, you're doing your job well enough. Who cares about making a product anymore, it doesn't matter. AI lets you do a bad job with much less effort than before
7. None of this is working. AI is not causing projects to get pushed out faster. There are no good high quality AI projects. The quality of code is going down, not up. Open source software is getting screwed
Its an extension of the culture where performance doesn't matter. Windows is all made of react components which are each individually a web browser, because the quality of the end product no longer matters anymore. Software just becomes shittier, because none of these companies actually care about their products. AAA gaming is a good example of this, as is windows, discord, anything google makes, IBM, Intel, AMD's software etc
A lot of this is a US problem, because of the economic conditions over there and the prevalence of insane venture capitalism and union busting. I have a feeling that as the EU gets more independent and starts to become a software competitor, the US tech market is going to absolutely implode
"You can learn anything now. I mean anything." This was true before before LLMs. What's changed is how much work it is to get an "answer". If the LLM hands you that answer, you've foregone learning that you might otherwise have gotten by (painfully) working out the answer yourself. There is a trade-off: getting an answer now versus learning for the future. I recently used an LLM to translate a Linux program to Window…
I'm conflicted about this. On one hand, I think LLMs make it easier to discover explanations that, at least superficially, superficially "click" for you. Sure, they were available before, but maybe in textbooks you needed to pay for (how quaint), or on websites that appeared on the fifth page of search results. Whatever are the externalities of that, in the short term, that part may be a net positive for learners. On…
It's possible my brain is not as elastic now in my 40s. Or maybe there's no substitute for doing something yourself (practice problems) and that's the missing part.
"You can learn anything now. I mean anything." This was true before before LLMs. What's changed is how much work it is to get an "answer". If the LLM hands you that answer, you've foregone learning that you might otherwise have gotten by (painfully) working out the answer yourself. There is a trade-off: getting an answer now versus learning for the future. I recently used an LLM to translate a Linux program to Window…
I learn a lot faster now with LLMs. You could learn the windows APIs much faster if you wanted to learn them
> Building systems that supervise AI agents, training models, wiring up pipelines where the AI does the heavy lifting and I do the thinking. Honestly? I’m having more fun than ever. I'm sure some people are having fun that way. But I'm also sure some people don't like to play with systems that produce fuzzy outputs and break in unexpected moments, even though overall they are a net win. It's almost as if you're deali…
Earlier quoted context omitted.
How is this faster than just reading the documentation? Given that LLMs hallucinate, you have to double check everything it says against the docs anyway
Human teachers make mistakes too. If you aren't consuming information with a skeptical eye you're not learning as effectively as you could be no matter what the source is. The trick to learning with LLMs is to treat them as one of multiple sources of information, and work with those sources to build your own robust mental of how things work. If you exclusively rely on official documentation you'll miss out on things…
WinAPI docs are pretty accurate and up to date
Earlier quoted context omitted.
I learn a lot faster now with LLMs. You could learn the windows APIs much faster if you wanted to learn them
How is this faster than just reading the documentation? Given that LLMs hallucinate, you have to double check everything it says against the docs anyway
AIs allowed me to get on with Python MUCH faster than I was doing myself, and understand more of the arcane secrets of jq in 6 months than I was able in few years before.
And AIs mistakes are brilliant opportunity to debug, to analyse, and to go back to it saying "I beg you pardon, wth is this" :) pointing at the elementary mistakes you now see because you understand the flow better.
Recently I had a fantastic back and forth with Claude and one of my precious tools written in python - I was trying to understand the specifics of the particular function's behaviour, discussing typing, arguing about trade-offs and portability. The thing I really like in it that I always get a pushback or things to consider if I come up with something stupid.
It's a tailored team exercise and I'm enjoying it.
Not a day goes by that a fellow engineer doesn't text me a screenshot of something stupid an AI did in their codebase. But no one ever mentions the hundreds of times it quietly wrote code that is better than most engineers can write. The catch about the "guided" piece is that it requires an already-good engineer. I work with engineers around the world and the skill level varies a lot - AI has not been able to bridge…
One issue is that developers have been trained for the past few decades to look for solutions to problems online by just dumping a few relevant keywords into Google. But to get the most out of AI you should really be prompting as if you were writing a formal letter to the British throne explaining the background of your request. Basic English writing skills, and the ability to formulate your thoughts in a clear manne…
That's probably why spec driven development has taken off.
The developers who can't write prompts now get AI to help with their English, and with clarifying their thoughts, so that other AI can help write their code.