I baked in lethal trifecta guards into my primary harness, DSCO, but it makes things much less smooth to run autonomously. Basically if you load secrets into a context, ideally it stops that and creates a process running a small local model that will write some code to not look at the secret and instead run code to operate on the secret without reading it in.

The risks are 1) exfiltration (network calls) 2) prompt injection (untrusted inputs) and 3) access to secrets

You can do some clever tricks like "spin up subagent without net access" to handle OCR of an internal document and have that agent communicate summaries to another "spun up subagent with net access" - imagine if one subagent is a local model and the other model is a frontier model over a web API. Maybe they still communicate in Neuralese or in abbreviated notes that you don't capture and are able to surreptitiously / covertly exfiltrate your information.

Ideally eventually you'll have some kind of dashboard that surfaces these risks as you're working.

Reports of AI researchers running massive swarms of 10,000 agents are definitely believable but the moment you start pulling in code libraries or other technology assets seems like you can get destroyed by a rogue actor. Definitely tons of unsolved problems here

Writing on mobile so this might poorly articulate the issue but it's interesting