https://github.com/mas-bandwidth/fixed3d -- port of box3d to fixed point :)
https://github.com/mas-bandwidth/fixed -- fixed point math library
I do you think now need to watch out for the opposite problem. These things become so easy to build that the temptation is just to go ahead and build. But unless you really do need them, all that new code just goes to waste. The cost to produce has become very low, but sometimes the value can end up being negative.
Big fan of RDF, your sexpr notes are hilarious https://github.com/mas-bandwidth/fixed/blob/main/docs/roadma...
What tooling do you have around this?
And then the AIs can easily write tooling in lisp to manipulate these structures, and you can talk to them from some golang program in a verb like way, sort of like a redis client.
I was planning on doing this to effectively replace issues/PRs in git, and have my entire future work set that I import into sprints stored inside this lisp sexpr.
It's implemented in nova-sprint as a tracer bullet (search for "roadmap" scripts in lisp...), but I definitely see this as something I want to keep pushing harder on.
It's a really effective thing, storing all your work in a data structure, and then being able to manipulate that data structure. beats having to hammer the GitHub API when you ask questions like "OK so what else can we bring into the sprint now?"
=)
I find it really useful to track future work, and then bring it in the current session or sprint. It also regenerates nice roadmap tables in markdown that people can read like these ones:
https://github.com/mas-bandwidth/schema/blob/main/ROADMAP.md
I did some prototype games, one thing that worked really well for me was having a deterministic replay system where the agents could drive the gamestate via recorded inputs. Kept me from having to do any playtesting or debugging in the main agentic loop.