Vijoy Pandey
On The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis
“Engineering assumes 100,000 users in total, whereas the customer really meant 100,000 concurrent users. There is a grounding problem here, there is a discovery problem here, there is a term alignment problem here. You don't really know what 100,000 means. Is it the total number of users? Is it concurrent users?”
The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis · AI Research & Frontier Labs · November 2026
Context
Asked for a concrete picture of a semantic failure between AI agents, Pandey gave this example from a deal passing between sales and engineering agents. He says it is the same misunderstanding human teams have, and it is what Cisco's Accord protocol is meant to resolve before work starts.
Transcript
So could we maybe work through an example a little more deeply? I have an intuition, of course, for like going back to the contract example,
…again, I have an intuition for sort of how people come together in a meeting or whatever and like hash it out and somebody makes a decision. What's the, what is the sort of, you know, step-by-step, blow-by-blow of the Accord and Concord protocols that perform the same core function for the agents?
…with where multiple agents from sales and marketing, legal, and engineering all coming together towards that deal desk situation. Sales, in this case, let's say here's a number: build a feature for 100,000 users. Sales being sales takes that number and says, We're going to solve for this challenge, comes back and says, Engineering and product, this is what we need to go after: 100,000 users. Engineering assumes 100,000 users in total, whereas the customer really meant 100,000 concurrent users. There is a grounding problem here, there is a discovery problem here, there is a term alignment problem here. You don't really know what 100,000 means. Is it the total number of users? Is it concurrent users? Is it MAO? Is it DAO? I mean, you don't know what that means. So, there itself is a simple example of what human teams do, and it's a simple example of what agentic teams do all the time. Alignment on terms, discovery of terms, resolving conflicting terminologies. This is before the work even starts. And so, what Accord allows you to do is to just align on the goal, term alignment, just being a…
So from a very procedural standpoint, a lot of this sounds like it would ultimately depend on frontier language models to sort of take in the interactions that the multi-agent system has had and kind of run them through another prompt that's like, does there appear to be any potential disagreement…
We are hitting a level of maturity in multi-agent systems, Nathan, that is actually decoupling this entire architecture. And you're seeing this happen everywhere. So we went from, again, isolated agents to islands of agents to connected agents. What we are also finding out is this within each…
So, earlier, you mentioned that the verifier in today's world is often a human. How sort of opinionated and contextualized or embedded do you think these verifiers will tend to be? I'm kind of wondering: like, is what we need for leaders, you know, whoever in this sort of deal example, right?…
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