I’m on site at my properties doing some due diligence, so won’t be able to join today. See you guys next week!

We will resume the Q&A sessions next week on our regular schedule!

I’ve been working on a system for agent continuity. One of the biggest problems with AI agents is that they eventually get overloaded with too much context, too many workflows, or too many responsibilities. The usual answer is to “start fresh,” but that creates a new problem: you have to retrain the next agent on everything the first one already learned. So we built a top-level agent orchestrator. The orchestrator acts as the source of truth for what an agent needs to know and what it needs to run. Core setup applies across all agents (context for the business, access to certain apps / document repositories) Then we get specific based on the context of the new agent: 1. Skills & Crons - and the attached github repo link for each 2. Which Business Silo the skill lives in (Finance, Ops, Marketing etc.) 3. Setup Standards & Guardrails so the skill is set up the right way every time When a new agent is created, the orchestrator can install the right skills and scheduled workflows for that agent’s role. Operations gets operations workflows, Sales gets sales etc. The key idea is portability. If one agent gets overloaded, you don’t lose the operating knowledge. You can spin up a new agent, assign it the right silo, install the relevant skills and crons, and continue from where the prior agent left off. This becomes especially easy if you use our platform Agentic Beaver, because creating a new agent takes one click. It turns agents from isolated chat sessions into a more durable operating system so that future agents inherit the right capabilities without manual retraining. This feels like an important step toward making agents maintainable over time. Not just smarter in a single conversation, but easier to scale, hand off, and keep aligned as the system grows.

Im on with a client so we will start at 1 pm today

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