[sunir]

Humans have hard skills and abilities the ais can’t reproduce yet like real time learning, spatial reasoning, cheap parallelism, Qualia so we can identity QWAN (quality without a name) because we feel in real time what the code is.

AIs have skills humans aren’t good at like nerding out on technical details.

That’s not a perfect map because I’m spitballing. However there is a symbiosis.

I am not sure I am productive anymore with AI as I am up to 125 repos and agents most of which are tools for managing AIs and things break frequently that it feels like spinning plates.

I spent two months in November and December last year writing by hand a fundamental library to constrain how the AIs build clis. That did make things move a lot faster but for those two months I felt the slowness.

I think it will always be like this. It’s the nature of paradigm shift to shift.

[iwiwk]

The way I think of it is, computer memory is superior to human memory because it can store anything and re-call on demand when requested. This is great for the human because we no longer have to remember every tiny detail - just enough to recall the object and thus opening up room for space in the brain for other stuff.

What is the llm equivalent?

[sunir]

The current algorithms have a limited context window and work linearly and are extremely expensive to change and energy intensive to run.

The human brain has a wide parallel multisystem real-time low-wattage execution layer that has way more modes than a large language model.

More importantly, because our brains are real-time, our qualia plus spatial and visual reasoning is superior to an LLM at understanding "elegance", "code smells", and overall system design because we can imagine ourselves as being the code or the system and we don't necessarily need to think in language. Well, at least that's how I experience coding in my mind; I imagine other developers similarly bring large parts of themselves into coding.

Feeling the code seems to be much more efficient at reducing complexity than any static analysis I've yet seen.

Finally, humans also empathize with other humans who have all the money. We know what works and doesn't work for humans in the here and now, not 2 years ago when the model training data was last collected. The value of Qualia is not to be discounted.

That being said, Sonnet 4.0 was the best model I've used that could express how the code felt, so who knows. If the emotionality wasn't tamped down, and the spatial reasoning improved, and the new algorithms for context engineering and parallelism make it to market, these advantages can be erased.