> using LLMs is learning how to manage your context.

This is the most important thing in my opinion. This is why I switched to showing tokens in my chat app.

https://beta.gitsense.com/?chat=b8c4b221-55e5-4ed6-860e-12f0...

I treat tokens like the tachometer for a car's engine. The higher you go, the more gas you will consume, and the greater the chance you will blow up your engine. Different LLMs will have different redlines and the more tokens you have, the more costly every conversation will become and the greater the chance it will just start spitting gibberish.

So far, my redline for all models is 25,000 tokens, but I really do not want to go above 20,000. If I hit 16,000 tokens, I will start to think about summarizing the conversation and starting a new one based on the summary.

The initial token count is also important in my opinion. If you are trying to solve a complex problem that is not well known by the LLM and if you are only starting with 1000 or less tokens, you will almost certainly not get a good answer. I personally think 7,000 to 16,000 is the sweet spot. For most problems, I won't have the LLM generate any code until I reach about 7,000 since it means it has enough files in context to properly take a shot at producing code.

I'm doing ok using the latest Gemini which is (apparently) ok with 1 million tokens.

all that fiddling and copy pasting takes me longer than just writing the code most of the time

And for any project that's been around long enough, you find yourself mostly copy-pasting or searching for the one line you have to edit.

Exactly, while not learning anything along the way.

Only if you assume one is blindly copy/pasting without reading anything, or is already a domain expert. Otherwise you’ve absolutely got the ability to learn from the process, but it’s an active process you’ve got to engage with. Hell, ask questions along the way that interest you, as you would any other teacher. Just verify the important bits of course.

No, learning means failing, scratching your head, banging your head against the wall.

Learning takes time.

I’d agree that’s one definition of learning, but there exists entire subsets of learning that don’t require you to be stuck on a problem. You can pick up simple, and related concepts without first needing to struggle with them. Incrementally building on those moments is as true a form of learning as any other I’d argue. I’d go as far as saying you can also have the moments you’re describing while using an LLM, again with intentionality, not passively.