I find it freaky how you notice the language change between models. Some words which pop up now all the time, that I don't remember reacting to with previous models, such as "honest(ly)" and "load-bearing". Feels like a new AI smell, like em-dashes or "it's not just x, it's y".
I’ve never asked Claude to re explain things so many times with this. The language it chooses is bizarre, not quite technical enough to be precise, and too hand wavy to be useful.
There also seems to be other issues with the sub agents and not inheriting memory.
E.g. I’m working on an analysis, absence of row implies a zero (it’s sparse).
Every time it checks the results it presents this missing data bug, but it’s not a bug, and I’ve explained it 10 times.
I mean, at finding issues it’s been great. I can ask it to look in other repos and its finding cross repo behaviour or subtleties much faster.
But it’s wasting more tokens reporting caveats I’ve already explained. And it’s suggesting stopping analysis when there’s still work to be done.
So overall I’d say it’s mixed. Feels better at code but worse at my explicit preferences and objective analysis.
