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Comment by jeremyjh | Hacker News Reader

I think Sol is already good enough though.

I don't think this is true at all. I use opus 5 to build a small project. It bothers me that people simply handwave away concerns so easily.

The context size is still not nearly as big as it needs to be to store all the code an enterprise needs. And apparently as you increase the context size, there are more defects. So none of this is a solved problem. We are still in early days and there is a lot to be done.

I'm sure there are marketing people who will say "coding is solved" and other such snake oil but none of this is done, far from it!

That being said there is still enormous value in older models especially with tool calling which will let them access the latest data. I feel like we need to be a little more careful and the tools should cache in a smart way to avoid rework but clearly if we could have opus 4.8 level of work for like a one time payment of a system for local LLM it will have value for years into the future.

So I agree in a weird way that sol is good enough for certain tasks but really there is a long road ahead.

"640k (token context) should be enough for anyone."

I know what you're saying, but modulo things like losing track of what year it is as time passes by, a current frontier model is going to continue to be useful for many tasks for many years, even moreso if it's 5-10x faster due to the chip architecture.

It's not that it would be the best forever, it's that it would be useful for plenty long enough to be worthwhile, even if there was better stuff available. In exactly the same way that this computer I'm typing this message on is not the latest and hottest cutting edge stuff. A 7 year old CPU, 7 year old Intel integrated graphics, an older NVMe disk, a mere 32GB of RAM... ok, that's one spec that's still pretty modern although it is slower RAM... but it's still plenty fast enough to comment on HN, even these seven years after it was cutting edge.

> but it's still plenty fast enough to comment on HN, even these seven years after it was cutting edge

While it’s still too early to tell, I don’t think that’s how intelligence scales. Better models get you better solutions even to trivial problems. The ceiling for getting it done better is very high even if you’re not doing anything complicated. And difficulty isn’t uniformly distributed anyway - it seems to me that “mostly simple” tasks often have annoying 1% tails that low-intelligence models struggle with. I think we’ll see people chasing the top models for quite a while, or indefinitely - depending on the cost curve.

exactly, but the "goes out of date" is bad when we talk about software.. but this isnt software, its hardware.

the youd have to buy a new one to get a better model is a FEATURE not a bug.

like if im apple... and i can put a sol level llm in an iphone, market it as privacy first you own your data personal assistant, integrate it all over the os... and then when there is a better model/siri make all the users buy a new phone... thats how they "win" ai.

the old standbys of better screens thinner cameras and batteries arent enough anymore. its basically tapped out. all modern phones are as thin as they need as big as they need as fast as they need and last all day on a battery...

apple needs a new number to up thing that people can actually feel/see. model generations could be it... every year faster, smarter, more capbilities and integrations.

Well, with proper compaction algorithm (like in Codex), it could indeed be useful for majority of tasks even in the future. The context length in Codex is just 272k, but it can reason well about much larger codebases due to good exploration and compaction algorithm.

I have yet to saturate the 1M context of Gemini, for example.

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