[alfiedotwtf]

Same thing could be said with SKILL.md yet they are highly useful...

Yes you can automate via scripting, but interacting with a process using natural language because every instance could be different and not solid enough to write a spec for, is really handy.

tl;dr: there's a place for "be liberal in what you receive and conservative in what you send", but only now have LLMs provided us with a viable way to make room for "be loosey goosey with your transput"

[chris_money202]

I understand but there still is usually 80-95% of the skill flow that you can script out that is repeated. Script it out and simplify your skill, make it more stable, and provide more opportunity to scale it up or down i.e use stronger or weaker models if need be. We should be scripting and forming process first then seeing where we can put AI after that.

[ziml77]

The AI for everything thinking is really easy to let infect you. I was trying to figure out how to make some SQL alerting easier to understand quickly. The first thing my brain went to was "oh just shove it into an LLM to pull out the info of what the query is doing". And it unfortunately wasn't until after I said that out loud that I realized that was a stupid idea when you could just run a SQL parser over the query and pull the table names out that way. Far faster, more cost effective, and reliable than asking an LLM to do it.

[alfiedotwtf]

That’s actually an awesome idea and totally helps to reduce wasting context size - move repeatable instructions to a SKILL.md, and once they’re repeatable and no longer have variability to input, turn it into a tool! Rinse repeat.

Oh nice, you could even eventually turn the whole process including inference into an app so that you’ve cut out the LLM from the whole process saving you execution time