can, but usually when stuff gets slightly more complex, being a fast typewriter is usually more efficient and results in better code.
I guess it really depends on the aspiration for code-quality, complexity (yes it’s good at generating boilerplate). If I don’t care about a one-time use script that is quickly written in a prompt I’ll use it.
Working on a big codebase, I don’t even get the idea to ask an AI, you just can’t feed enough context to the AI that it’s really able to generate meaningful code…
Working on a big codebase, I don’t even get the idea to ask an AI, you just can’t feed enough context to the AI that it’s really able to generate meaningful code…
That’s not a hard limit, for example google’s models can handle 2-million-token context window.
Ughh I tried the gemini model and I’m not too happy with the code it came up with, there’s a lot of intrinsities and concepts that the model doesn’t grasp enough IMO. That said I’ll reevaluate this continuously converting large chunks of code often works ok…
Well, it wasn’t a comment on the quality of the model, just that the context limitation has already been largely overcome by one company, and others will probably follow (and improve on it further) over time. Especially as “AI Coding” gets more marketable.
That said, was this the new gemini 2.5 pro you tried, or the old one? I haven’t tried the new model myself, but I’ve heard good things about it.
can, but usually when stuff gets slightly more complex, being a fast typewriter is usually more efficient and results in better code.
I guess it really depends on the aspiration for code-quality, complexity (yes it’s good at generating boilerplate). If I don’t care about a one-time use script that is quickly written in a prompt I’ll use it.
Working on a big codebase, I don’t even get the idea to ask an AI, you just can’t feed enough context to the AI that it’s really able to generate meaningful code…
That’s not a hard limit, for example google’s models can handle 2-million-token context window.
https://ai.google.dev/gemini-api/docs/long-context
Ughh I tried the gemini model and I’m not too happy with the code it came up with, there’s a lot of intrinsities and concepts that the model doesn’t grasp enough IMO. That said I’ll reevaluate this continuously converting large chunks of code often works ok…
Well, it wasn’t a comment on the quality of the model, just that the context limitation has already been largely overcome by one company, and others will probably follow (and improve on it further) over time. Especially as “AI Coding” gets more marketable.
That said, was this the new gemini 2.5 pro you tried, or the old one? I haven’t tried the new model myself, but I’ve heard good things about it.