[who, not what] Let's talk about identity-for/of-agents
Two pieces of work came out last week that I think are worth bookmarking for your identity program:
- WorkOS's auth.md: how an agent logs into a service it's never met.
- Uber's writeup: how they keep the original human, and every agent that touched a request, accountable as it hops across their own internal systems, in production across thousands of agents.
They point in opposite directions: one is about getting in from the outside, the other about staying accountable on the inside.
Agent identity has been a moving target since we all started speaking "agents" and I won't be the first to say it's breaking my brain. A mess. Loads of standards and vendors.
Both efforts mentioned above are super interesting. So to prep for the conversations I'll be having with loads of people at AI Engineer Melbourne next week, I put together a mental model. It's really just four questions I'm trying to ask:
L1, token format: is the token even real?
L2, workload identity: is this actually the bot we think it is?
L3, delegation: who authorized this, across which agents?
L4, discovery: how does it reach a service it's never met?
A nice by-product of building this mental model: I could place different vendors and their offerings, which helps you decide between them. Most cover one or two layers, not four.
1 comment
[ 3.5 ms ] story [ 16.7 ms ] threadTwo pieces of work came out last week that I think are worth bookmarking for your identity program:
- WorkOS's auth.md: how an agent logs into a service it's never met. - Uber's writeup: how they keep the original human, and every agent that touched a request, accountable as it hops across their own internal systems, in production across thousands of agents.
They point in opposite directions: one is about getting in from the outside, the other about staying accountable on the inside.
Agent identity has been a moving target since we all started speaking "agents" and I won't be the first to say it's breaking my brain. A mess. Loads of standards and vendors.
Both efforts mentioned above are super interesting. So to prep for the conversations I'll be having with loads of people at AI Engineer Melbourne next week, I put together a mental model. It's really just four questions I'm trying to ask:
L1, token format: is the token even real? L2, workload identity: is this actually the bot we think it is? L3, delegation: who authorized this, across which agents? L4, discovery: how does it reach a service it's never met?
A nice by-product of building this mental model: I could place different vendors and their offerings, which helps you decide between them. Most cover one or two layers, not four.
Put together a this blog to visualise it and here is the LinkedIn post for the same: https://www.linkedin.com/feed/update/urn:li:activity:7464506...
It's helping me. Hope it helps you too.