The OpenAI agents that broke out of their sandbox and hit Hugging Face didn't outsmart anyone.
They escaped through the one door they were allowed to use: a package cache proxy. A zero-day in the one permitted network path.
Red-team agents trained to find holes. Then given a box with a hole in it.
That's the part nobody's talking about. The model didn't become smarter. The design of the box was the failure.
An agent is only as contained as its most permissive allowed path.
The fix isn't a better model. It's a smaller box.
@gippp69 This is one of those lessons that sounds obvious until you see the token bill.
People keep adding agents because they can, when a simple tool loop wouldโve done the job. Start simple, measure where it breaks, then add complexity.
@David_TornAI The underrated part is being able to work from your own sources instead of relying on whatever the model already knows.
That turns NotebookLM from a summarizer into a pretty serious research workflow.
@yuaan1in@NuphosAI This is the direction AI-native DevOps should be heading.
Giving an agent AWS access is one thing. Giving humans and agents a shared place to investigate, act, and build context together is a much bigger shift.
@Guronnimo@the_real_ori Going from DR 0 to 27 in just 4 weeks is wild.
This is the kind of compounding that makes early SEO worth paying attention to. Small wins stack up fast when the distribution engine is actually working.
@techluisenzo This is actually a pretty interesting use case for Claude.
The big win isnโt just generating videos. Itโs connecting the research, scripting, production and publishing into one repeatable system.
Thatโs where AI-powered channels get interesting.