1. A compiler for real-time tensor processing (arbitrary DSP, ML). In something like LISP or Haskell, the goal is to compile lambda calculus for fast/reliable execution—as such, you can express a program in a fully general language that can represent any computation and execute it without explicitly modeling the lower levels of the machine. I'm building a compiler that does the same thing for the subset of programs that are guaranteed to execute on-budget. The effect: you write code that looks like DSP/ML math and it compiles/runs optimally with execution guaranteed by construction.

2. My take on an agent framework ... append only log + content hypergraph in Elixir, tools that regularly pull data from other services into Postgres—built as a kind of 'exoskeleton' around claude/codex so it's not competing with fast-moving tools.

Thinking about category theoretic models of computation: https://arxiv.org/abs/2208.03817

--

Some things I want other people to build:

- Indexing for Github

- All-in-one social media ingestion libraries for agents

- GOFAI-inspired knowledge / semantic / research graph stuff—I want to point agents at rules/structures for writing connected, verifiable statements