It honestly has all kinda felt like more of the same ever since maybe GPT4?
New model comes out, has some nice benchmarks, but the subjective experience of actually using it stays the same. Nothing's really blown my mind since.
Feels like the field has stagnated to a point where only the enthusiasts care.
For coding Opus 4.5 in q3 2025 was still the best model I've used.
Since then it's just been a cycle of the old model being progressively lobotomised and a "new" one coming out that if you're lucky might be as good as the OG Opus 4.5 for a couple of weeks.
Subjective but as far as I can tell no progress in almost a year, which is a lifetime in 2022-25 LLM timelines
Another annoyance (for more API use) is summarized/hidden reasoning traces. It makes prompt debugging and optimization much harder, since you literally don't have much visibility into the real thinking process.
I don't trust the benchmarks either, so I maintained a set of benchmarks myself. I'm mostly interested in local models, and for the past 2 years they have steadily gotten better.
Can't argue with subjective experience, but if there were some tasks that you thought LLMs can't do two years ago, maybe try again today. You might be surprised.
New model comes out, has some nice benchmarks, but the subjective experience of actually using it stays the same. Nothing's really blown my mind since.
Feels like the field has stagnated to a point where only the enthusiasts care.