> utterly exhausted

Keep your toolchain as simple as possible.

A really nice rig, which you can use in an existing repo, is to have ollama and aider simply log everything that happens in the session, through tee, into a log directory which you do - indeed - check into the repo.

> almost exclusively with coding agents

Do your own commits too (don't just let the ML do them), and in those commits, keep your prompts.

Learn to use your AI skills with succinct and calculated, forthright projection.

Which is to say, it is your own personal set of words now which define your control over your computer.

The words are tools. But what are your methods?

> .. tedious to write full sentences for every change I want .. interaction paradigm ..

Your own command of your speaking/thinking language can be extended as far and as wide, now, as you can possibly imagine. In fact, you must control AI/ML with imagination now, in multiple ways.

One of those ways is to iterate on expansion of your own ontology. There has to be an input from the AI before an adequate human output can send the AI directly at the heart of it. This improvement loop is on you. Get smarter with the loop.

> pseudo-code -> sync -> record of intent

[1] "Idea -> Description -> Result -> Build -> [human] (use)"

Well, I get this by checking all my aider logs into a submodule of my main source tree. All my prompts, all the happy little mistakes and bright, shiny things, commit by commit. Sure, the logs grow and grow, but you know what .. I learn a hell of a lot by reading them.

Time-stamped. So, nice graphs if I wanted them, one of these days we'll do it, me and the AI.

The commit point for where I cut the exhaustion between me and the immense power of the AI/ML tooling, is when there is a new build, and I have tested it, personally.

I get exhausted if there is no delivery factor, to me personally, from whatever method I'm wrangling the tools with. Like if I really push too hard on the prompt, things get gnarly.

But, I've been here before over the decades, there are methods.

Even in the AI/ML age .. tooling and methodology requires a discipline - what is true now more than ever is that if a method fails, the usual approach of building another tool is not necessarily the best approach.

Methods can be sharpened just like tools. But every tool carries a cognitive load.

The methods are there to make that load useful. Are you a user?

So then just do a build and run it. See if is worth it.

Goto [1].