yep! So all repos get a (.gitignore'd) folder of `plans/<task>/plan.md` work histories . That ends up being quite helpful in practice: calculating billable hours of work, forking/auditing/retrying, easier replanning, etc. At the same time, I rather be with-the-grain of the agentic coder's native systems for plans + todos, eg, alignment with the models & prompts. We've been doing this way b/c we find the native to be weaker than what these achieve, and to hard to add these kind of things to them.

RE:Other note, yes, we have 2 basic goals:

1. Louie to make graphs / graphistry easier. Especially when connected to operational databases (splunk, kusto, elastic, big query, ...). V1 was generating graphistry viz & GFQL queries. We're now working on louie inside of graphistry, for more dynamic control of the visual analysis environment ("filter to X and color Y as Z"), and as you say, to go straight to the answer too ("what's going on with account/topic X"). We spent years trying to bring jupyter notebooks etc to operational teams as a way to get graph insights to their various data, and while good for a few "data 1%'ers", too hard for most, and Louie has been a chance to rethink that.

2. Louie has been seeing wider market interest beyond graph, basically "AI that investigates" across those operational DBs (& live systems). You can think of it as vibe coding is code-oriented, while louie is vibe investigating that is more data-oriented. Ex: Native plans don't think in unit tests but cross-validation, and instead of grepping 1,000 files, we get back a dataframe of 1M query results and pass that between the agents for localized agentic retrieval on that vs rehammering db. The CCC talk gives a feel for this in the interactive setting.