What I've been more interested in lately is structural intelligence as a field in whole.

Things with LLMs break because our infra was always designed for analyzing lines(tools like grep fuzzy matching) and working on quite small sections of code. LLMs struggle with this in cases when they have to analyze different parts of a codebase they either get too much context where you're throwing whole files at them, or too little where they only see the function in isolation, with no real understanding of how the pieces actually connect to each other.

That's really the gap sem is trying to fill. With sem impact you can give an agent the precise blast radius of a change instead of guessing which files matter, and sem diff --patch lets you enforce that a change only touches specific functions and reject anything that bleeds outside that boundary something that's really hard to do with line-level diffs.

Your testing idea is actually closer than you might think. sem already extracts entity signatures, dependencies, and call graphs, so you could build a harness that gives the test-writing agent only the function signature with its dependency graph and behavioral contract, while withholding the implementation entirely. That would force the agent toward behavioral tests because it literally can't see the internals to mock them. I haven't built this harness myself yet but sem graph and sem inspect expose everything you'd need.

The general principle is that sem gives you a structural map of the codebase to both constrain and validate what the model produces, rather than treating code as flat text and hoping the model figures out the relationships on its own.

Another usecase can be about figuring out dead code present in the codebase.

Edit: Also one last thing because I started working on this while solving the fundamental issue of why merge conflicts were occuring with git, so you might also like the merge drive I open sourced on the same Github org - Weave