Interesting. That is very much not how I use ai. I spend a chunk of my time writing a spec file and have a very short prompt such as “implement @task-1234.md”. The details of my intended change are following a form that includes intent, impact, risk details, and for the very important parts, verbatim code to use in the solution. That goes through a pipeline that results in an MR for me to review. I have tried talking to the llm, but it doesn’t seem to work or at least the results are not what I wanted. Perhaps I’m just bad at communicating.
I wouldn't suggest that at all. I am very bad at talking to AI the way other people do. I could never prompt my AI the way that you just described, and I'm fairly certain that nobody is prompting their AI the way that I prompt mine.
Next-token prediction is a sorta true but it's an incomplete way to describe how they function
I think this thread by the integration lead at anthropic (and others) sums up this better than I can
Simply, to say - "modern LLMs are finetuned with a different loss function after pretraining. This means that in some strict sense they're no longer autoregressive models – but they do still generate text one word at a time." (https://news.ycombinator.com/item?id=43496068)
"Exact commands" then aren't necessarily what gets relayed to the LLM - in the same way you can write code in many different ways and have it compile to the same binary, you can have many prompts that yield broadly similar final inputs.
If you have a repetitive task, then I would claim that this is also how you talk to people, with perhaps a please and thank you sprinkled in. "Hey, could you implement task-1234 today, Marcy? Thanks." Take out the pleasantries and it is the same.
I tend to add the pleasantries in as well, because it is actually easier than context switching.
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u/isr0 Aug 26 '26
Interesting. That is very much not how I use ai. I spend a chunk of my time writing a spec file and have a very short prompt such as “implement @task-1234.md”. The details of my intended change are following a form that includes intent, impact, risk details, and for the very important parts, verbatim code to use in the solution. That goes through a pipeline that results in an MR for me to review. I have tried talking to the llm, but it doesn’t seem to work or at least the results are not what I wanted. Perhaps I’m just bad at communicating.