AI adoption in most companies looks the same: a handful of people using ChatGPT, a couple of point tools bolted onto a workflow, and no coherent picture of what's being automated or why. That isn't an AI strategy - it's noise. The real leverage comes from treating AI as an operating layer over your existing systems, not another tab in the browser.

This session lays out a first-principles approach to designing an AI operating system for your company: how to identify the work worth automating, how to define agents with clear boundaries and responsibilities, and how to connect them to the tools where your data actually lives - your CRM, your finance stack, your project management, your documents. Once that layer exists, asking an assistant in plain English to pull numbers across systems and assemble a picture of your company becomes a matter of seconds, not a developer ticket and a week of lead time.

Attendees will leave with a mental model for what an agent should and shouldn't do, a practical framework for auditing their current AI usage, and concrete patterns for connecting agents to internal systems safely. The session is aimed at founders, operators and technical leaders who want AI to give them a clearer, faster view of their company - not just faster typing.

Key themes: agent design from first principles; the tool layer (MCP, APIs, integrations); building an AI-augmented view of company operations; where humans stay in the loop; common failure modes and how to avoid them.