174 karma · joined September 11, 2014
To this point, however, writing informative articles about regulation or legal topics goes great! I don't want there to be ambiguity.
One tactic I use is to point out specific phrases as awkward, and create a tone guide both for the series and the specific article. They can mostly understand when you show them, it makes the process easier!
https://github.com/ArtRichards/docs-cli
and
https://artrichards.github.io/agent-playbook-suite/blog/
it works with docs-cli
`pipx install docs-cli`
I love reading them to see if theres a way mine could be improved, what topics they hit on, how they approach different problems.
https://github.com/ArtRichards/agent-playbook-suite
edit: tmux + terminal harness is my current go to
Works with 5.6 sol also, when you're deep in the weeds. I rationalize this as the models attempting to compress as much into the fewest tokens, though the choice of words often doesn't make sense to me, going back to read the original after, its often there. It definitely feels like a different sort of 'Machine Language' though xD
What if there's a way to extract the commodity of intelligence from smaller models?
I've seen for many use cases it's well enough. :)
My flow state is thinking about and understanding this: am I solving a problem that needs to be solved now, for the right person?
I created this to help me understand it (project foundations + create milestones) and then bring it to reality (ship milestones).
I'm interested in others dping something similar :) I included a docs cli tool in pypi to manage this context:
I created docs-cli (pypi) to manage the index of specs as source code: the framework that goes with it will first create tests for as much as it can, so reproducability becomes the goal, not readability.
But Codex to plan big features and Claude to review the feature plan (often finds overlooked discrepancies) then review the milestones and plan implementation of them in planning mode, then clear context and code. Works great.