“If you just look at agents being up and working, which is what all dashboards show today, we saw that the system was 66% up, which was defined as working perfectly. But it had 0% task completion. 0%. It did not complete the task. … So your dashboards might be green, but your outcomes might be wrong, completely wrong.”

…the work, making sure that what you've delivered is aligned to the global goal and not aligned to the individual agents' local optima and incentives. So that stack is what we are building. And yes, you can experience that stack through WebEx and Slack or whatever your collaboration choice is. So

…potentially to a problematic degree quite soon. How do you think about building the right level of detail into that stack, given the delta between like the models that we have available now and the ones that we have, you know, at least like a pretty clear foreshadowing of what's about to happen?

Hey, we'll continue our interview in a moment after a word from our sponsors. The cognitive revolution is brought to you and powered by Tasklet. I've been running Tasklet agents for almost a year, and they've become a major part of how the show gets made. Before every recording, one agent…

Now, having said that, the next question is: what do I do about it? So we've highlighted where the problems are, but how do I enable these agents to then talk to each other, align on intent, communicate meaningfully so that they are reasoning collectively? The way you would do that is to use…

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,