Gemini 2.5 Pro vs. Claude 3.7 Sonnet: Coding Comparison

I respectfully disagree with that. I think it's a solid UI framework, but...

>> It's openly hostile to not consider the upgrade path of existing users, and make things so difficult that it requires huge lifts just to upgrade versions of something like a UI framework.

I completely agree with you on that. We barely use any UI widgets so you'd think the port would be easy enough. I went through most of the checklist for changes you can make while still using GTK3 in prep for 4. "Don't access event structure members directly, use accessor functions." OK I made that change which made the code a little more verbose. But then they changed a lot of the accessor functions going from 3 to 4. Like WTF? I'm just trying to create a menu but menus don't exist any more - you make them out of something else. Oh and they're not windows they are surfaces. Like why?

I hope with some of the big architectural changes out of the way they can stabilize and become a nice boring piece of infrastructure. The talk of regular API changes every 3-5 years has me concerned. There's no reason for that.

Yes people claim that but everyone with a grain of salt in his mind know this is not true. Yes, in some cases an LLM can write from scratch a python or web demo-like application and that looks impressive but it is still far from really replacing a SWE. Real world is messy and requires to be careful. It requires to plan, do some modifications, get some feedback, proceed or go back to the previous step, think about it again. Even when a change works you still need to go back to the previous step, double check, make improvements, remove stuff, fix errors, treat corner cases.

The LLM doesn't do this, it tries to do everything in one single step. Yes, even when it is in "thinking" mode, in thinks ahead and explore a few possibilities but it doesn't do several iterations as it would be needed in many cases. It does a first write like a brilliant programmers may do in one attempt but it doesn't review its work. The idea of feeding back the error to the LLM so that it will fix it works in simple cases but in most common cases, where things are more complex, that leads to catastrophes.

Also when dealing with legacy code it is much more difficult for an LLM because it has to cope with the existing code with all its idiosincracies. One need in this case a deep understanding of what the code is doing and some well-thought planning to modify it without breaking everything and the LLM is usually bad as that.

In short, LLM are a wonderful technology but they are not yet the silver bullet someone pretends it to be. Use it like an assistant to help you on specific tasks where the scope is small the the requirements well-defined, this is the domain where it does excel and is actually useful. You can also use it to give you a good starting point in a domain you are nor familiar or it can give you some good help when you are stuck on some problem. Attempt to give the LLM a stack to big or complex are doomed to failure and you will be frustrated and lose your time.

When ChatGPT was the only game in town Microsoft was seen as a leader, thanks to their wise investment in Open AI. They relied on Open AI's model and didn't develop their own. As a result Microsoft has no interesting AI products. Copilot is a flop. Bing failed to take advantage of AI, Perplexity ate their lunch.

Satya Nadella last year: “Google should have been the default winner in the world of big tech’s AI race”.

Sundar Pichai's response: “I would love to do a side-by-side comparison of Microsoft’s own models and our models any day, any time. They are using someone else's model.”

See: https://www.msn.com/en-in/money/news/sundar-pichai-vs-satya-...