There’s a framing spreading through the AI security conversation that I think gets systems compromised. On one side, people say the model is aligned now, so you don’t need all that security architecture.
On the other, people say alignment is vibes and the only thing that counts is a deterministic control. Both are wrong, and they’re wrong in the same way. Each describes half of a defense and calls it the whole thing.
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I've made a version of the security-side argument myself. I wrote that it was never the model, and I said agent security is a system security problem, not an alignment problem.
Half of that was right.
The cleanest way I've found to frame it is that an agent deployment's risk is the likelihood of a failure times the damage one can do. Alignment works on the probability. Security works on the blast radius.
July's sandbox escape that ended inside Hugging Face showed what happens when every layer that could have held was disabled, absent, or thin. Then each community declared the incident belonged to the other.
Security figured out long ago that we're in the business of risk management, not risk elimination.
It's equally delusional to think there will ever be perfect alignment. The answer is to treat alignment as a control with a known failure rate and build something behind it.
In the video I cover:
Plain definitions of alignment and security, and why one is subjective while the other has checkable success criteria
Soft guardrails versus hard boundaries, and probability versus blast radius
Where the discourse is splitting, from model-side over-claims to the security side (including my own) to policy
The July sandbox escape into Hugging Face, and why both readings of it are half the story
Why refusals are speed bumps and not security controls
Excessive agency, and why least privilege can't stop misuse of legitimate access
What defense in depth looks like when you run both: model, harness, runtime, identity, and governance
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