For day to day coding, I've found Anthropic to be killing it with Sonnet 3.7 and now Sonnet 4, and Claude Code feeling like it has even bigger advantages over when it's used in Cursor (And I can't explain why).
I don't even try to use the OpenAI models because it's felt like night and day.
Hopefully GPT-5 helps them catch up. Although I'm sure there are 100 people that have their own personal "hopefully GPT-5 fixes my personal issue with GPT4"
Whatever the benchmarks might say, there's something about Claude that seems to deliver consistently (although not always perfect) quite reliable outputs across various coding tasks. I wonder what that 'secret sauce' might be and whether GPT-5 has figured it out too.
Agreed, I always give my one pager product briefs to AI to break down into phases and tasks, and then progress trackers. I explicitly prompt for verbose phases, tasks and test plans.
Yesterday without much promoting Claude 4.1 gave me 10 phases, each with 5-12 tasks that could genuinely be used to kanban out a product step by step.
Claude 3.7 sonnet was effectively the same with fewer granular suggestions for programming strategies.
Gemini 2.5 gave me a one pager back with some trivial bullet points in 3 phases, no tasks at all.
My experience has been that Claude Code is exceptional at tool use (and thus working with agentic IDEs) but... not the smartest coder. It will happy re-invent the wheel, create silos, or generate terrible code that you'll only discover weeks or months later. I've had to rollback weeks of code to discover major edge regressions that Claude had introduced.
Now, someone will say 'add more tests'. Sure. But that's a bandaid.
I find that the 'smarter' models like Gemini and o3 output better quality code overall and if you can afford to send them the entire context in a non-agentic way .. then they'll generate something dramatically superior to the agentic code artifacts.
That said, sometimes you just want speed to proof a concept and Claude is exceptional there. Unfortunately, proof of concepts often... become productionized rather than developers taking a step back to "do it right".
I disagree that tests are bandaids. Humans needs tests to avoid doing regressions. If you avoid tests you are giving the AI a much harder task than what human programmers usually have.
That's been my experience too. Even though Gemini also does seem to do the fancy one-shot demo code well, in day to day coding, Claude seems to do a much better job of just understanding how programming actually works, what to do, what not to do, etc.
Colleagues were saying that horizon alpha and beta were looking better than claude4 for frontend stuff, especially newer frameworks. I think the idea of having full + mini + nano is really good, as long as the smaller ones can reasonably handle small-ish tasks. You'd have your architect / plan whatever sessions with the large one, scoping out regular tasks for the -mini version and then the really easy ones to -nano.
4.1 was almost usable in that fashion. I had 4.1-nano working in cline with really trivial stuff (add logging, take this example and adapt it in this file, etc) and it worked pretty well most of the time.
Well, since (like you pointed out) using the Anthropic models in different settings is not that exciting anymore, the difference is what Claude Code does. It's a good product.
Refactors, building non-trivial features (you can first write out a spec and have it follow that), understanding my code, writing tests, writing good quality documentation. Reasoning about my existing data model and where to plug into it.
On and on and on. Coming up with test plans, edge cases, accounting for the edge cases in its programming. Programming defensively. Fixing bugs.
I don't even try to use the OpenAI models because it's felt like night and day.
Hopefully GPT-5 helps them catch up. Although I'm sure there are 100 people that have their own personal "hopefully GPT-5 fixes my personal issue with GPT4"