17 points noemit 4 hours ago 1 comments
I ran an experiment to see if CLI actually was the most intuitive format for tool calling. (As claimed by a ex-Manus AI Backend Engineer) I gave my model random scenarios and a single tool "run" - i told it that it worked like a CLI. I told it to guess commands.
it guessed great commands, but it formatted it always with a colon up front, like :help :browser :search :curl
It was trained on how terminals look, not what you actually type (you don't type the ":")
I have since updated my code in my agent tool to stop fighting against this intuition.
LLMs they learn what commands look like in documentation/artifacts, not what the human actually typed on the keyboard.
Seems so obvious. This is why you have to test your LLM and see how it naturally works, so you don't have to fight it with your system prompt.
This is Kimi K2.5 Btw.
shomp 34 minutes ago | parent
Great observation. The brain of a programmer is still a "black box" to the feed-forward network of nodes . But in theory, if you pumped a lot of the live-coding videos from something like youtube into the process, you could get a bit of that "what's your approach"-erism to bleed into the model. There might not be enough material there to truly "train it to think" but it would be interesting to try and "fill the gaps" of black-box-ed-ness in the LLM with supplemental "here was the process that got us there" video feeds. The next natural move might actually be recording thousands of hours of footage of developers working with the LLMs directly like in Cursor or another IDE that has LLM live-pair-programming , maybe calling it "pair programming" is generous , but it might be a reasonable foray into teaching the next generation of LLMs the "thought process" behind things. In reality you'd be teaching it which files to inspect, which windows to open/close, which tools to switch to and focus on. And while it might be imperfect, it might just be enough.