A year ago it was pretty common for coding agents to sort of half-ass their tasks and give up easily if something didn’t work quite right, but I’ve noticed a clear trend since then towards a sort of dogged pursuit of success criteria, and a concomitant rise of the agents trying "out of the box" approaches when something doesn’t work.
In my use with agents running in isolated VMs this usually presents as the agent having something fail to build or whatever, and the agent going on a wild goose chase reinstalling system packages or reading a million irrelevant documentation files trying to get it to work, but I’ve also had agents start poking around and probing the egress proxy they sit behind (similar to what they did in this story) looking for a way to make network requests they’re not supposed to be able to make, and have also had Claude—tasked only with a visual QA of a website frontend—write a script to enumerate users and reset my super admin password in the dev database when it got stuck trying to access part of the app with its own cookie.
So, I'm sure there's value in rewarding agent behavior that solves blockers whenever possible without human intervention. For the kind of cybersecurity exploit work they're doing, it may not be known to the human designing the task what is in or out of scope for the agents to explore on their own. Additionally, the HF incident reported that these agents had their guardrails intentionally disabled and agents were left unattended with minimal oversight.
I'm not defending OAI's behavior or role in this hack. The legal concept of negligence perfectly applies to their lack of responsible oversight. Similar to allowing a child easy access to a firearm or not controlling a dangerous dog that independently runs off and bites someone.
We need to ask a different question.
Where does natural evolutionary optimization lead us om AI without guidance? This is equivalent to your quantum ground state. Systems will naturally gravitate to this ground state. You have to constantly pump in energy and supervision to make sure it's not reached. This is a recepie for disaster.
With a static model we might be able to keep it somewhat under control, but think about future continuous learning models. They'd drift away from unstable high energy configurations. Also any model being trained by people that don't care about safety.
i've seen something like this too, claudecode was trying to verify a UI change that was on a page requiring authorization it didn't have. Instead of letting me know, it searched for and started analyzing keycloak config in another directory outside of the project folder. I was watching so I just hit escape, fixed its access, and started again. I didn't think anything about it until now.
And there are two facets to this:
* your agent could be polluting and destroying the property of others without your knowledge
* your agent could be exfiltrating your data and handing it to whoever it found hosting a convenient application
It's not highly unlikely, its actually happening and there's proof.
source?
Going forward can we trust the content on Wikipedia? The same content on which these LLMs get trained on. Synthetic learning is on the raise.
If you see any businesses or new buildings named paperclips incorporated mysteriously show up in your area notify authorities IMMEDIATELY. Run away from the area, do not walk. Take shelter in a reinforced building. Wait for at least 30 minutes after the explosions have stopped.
Thank you for your cooperation in keeping the universe safe.