alt Hacker NewsTo be fair we've gone from barely capable at writing code to what we have today in barely 3 years. I wouldn't put money on the counter bet that they won't get beyond this hump.
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The product and UX of the tool is distinct from the raw ability of the tool.
The current approach of the big companies is to keep increasing the number of parameters (there was a report that recent Claude models are on the 4T parameter scale). Even recent SOTA open weight models are in the 1T-2T range.
This is partly due to the multiplicative scaling factor -- the number of tokens; the number of transformer layers; the number of features; etc.
I suspect that for models to have a step upgrade either/both of 1) a new/improved architecture model; and 2) better training of smaller parameter models are needed. I say the latter as I think that with the larger weights there is a lot of unused/redundant parameters.
I dont think the quality has gotten that much better. Take claude 4.5, the probability of getting usable outputs was less likely than with opus 5.5, and the usuable outputs weren't great.
I think newer models are more likely to produce the usuable output, almost always, but its still not great. The frequency in which you get usable results leads one to believe that quality is improving.. No usability is improving but the result is still meh.
Also put an llm in an environment without an lsp or compiler to check against and let me know how capable you think they are on their own. The "loop" is doing a lot of heavy lifting here.
If we’re learning anything from the past 15 years it’s probably not to extrapolate AI progress in a straight line.
https://finance.yahoo.com/sectors/healthcare/articles/godfat...
Progress is spiky and not guaranteed. The capital costs have also ballooned to the point where the rate has to level out
Time doesn't solve bad designs. We still have lots of buffer overflows in C.
We don't see any indication that the LLM companies are slowing down and go for better code.
Instead it just looks like a cash grab until the AI bubble bursts.
I wouldn’t assume that progress is linear. Maybe I’m wrong and it will be! But I’m reminded of early developments with self driving cars, it felt like manual driving would be a thing of the past within a decade. But progress has been much slower than that.