Brief in progress — review the script and demo before recording.
This one gets us to a point where agents manage other agents within an environment we shape. Our job becomes building primitives agents can use to build and manage tools, integrations, and workflows. This gets very close to a software factory — or becomes one — though it covers not only the development process but also the other areas that make a product.
- Organization: when we think about agentic teams, we often imagine a complicated setup designed from scratch. Here, we will focus instead on making a system that can evolve.
- Coordination: agents have to be short-lived, but the system itself has to be durable. Those agents need to be aware of what they are doing, what they have done, and what is planned.
- Parallelism: autonomous agents get messy quickly, especially when they are managed by multiple people. If more than one agent works on something similar, they often collide and start fighting each other. Even if we do not have answers to all of these issues, we should show that they exist and have to be considered.
- Supervision: say we have Pi instances spawned on multiple machines. An AI agent has to be able to get us to any of those instances and its history, and explain what has been done, what failed, and so on. We may show scenarios where agents monitor a system on a schedule, suggest improvements, and find issues.
We may want to showcase scenarios such as:
- A custom setup based on Omp, a few agent templates, and a knowledge system. It would be useful to include as many insights, ideas, tools, and configs as possible — all oriented toward self-evolving systems.