Funny how the two top comments are contradictory. We need better than anecdotes to understand what the new models bring.
I didn’t mention my case since it’s quite esoteric, but I am working on an application using the Apple RoomPlan API, which is very powerful but very limited in customizability. Opus simply couldn’t alter the scanning view for me, it would try things over and over and eventually started making up parameters and passing them hoping it would work.
Completely failed, but I knew it was possible because a competitor app does it.
Fable also failed, then added log lines (as did Opus, but Opus failed to do anything useful with them) and then reversed engineered the API, and made it work.
Here’s one difference I have seen. I forgot I had a multi-session audio probe running while trying to repro audio glitches, and Fable came back with: “your pops are already on tape.”
Interesting choice of words. Phrased so casually. It picked a low-tech idiom that fit the situation instead of giving some sterile technical answer. That kind of language and context awareness never happened for me with Opus, or gpt 5.5.
you're living in the age of AI; not AGI. Also, there's pretty much zero moderation on HN, so astroturfing is likely streaming through just as bad as reddit. It' sjust noit as obvious because it's a smaller scoped website.
Since Fable, my legit infrastructure project has turned into the sort of thing I can do 95% on my phone. It’s reliable enough instead of doing big reviews, I’ve just been giving it smaller tasks, and dozens in parallel.
I created a skill that’s focused on getting PRs merge-ready, and now my attention is fully back where it should be, on deciding what changes will make the product better.
Our entire stack is Apache 2.0 open source, including the agent docs, so if you wanna try sitting at a higher level of abstraction, install the skill in your repo or just clone our whole project and start adding features: https://good.vibes.diy/blog/beast-mode-skill-for-claude-code