The dashboard that updates itself while I’m in another meeting.
Most people are still using AI like a really smart search bar. Ask a question, get an answer, close the tab. Repeat.
That’s not where the value is.
The value is in building tools that work for you while you’re doing something else. Not chatbots. Systems that go pull the inputs, process them, and update your view of the world while you’re in a 1:1 about something completely different.
Here’s what I built for myself this week.
A live project health dashboard artifact. It tracks every project I’m running — milestones, risks, decisions, stakeholder sentiment, commitments I’ve made and haven’t closed out yet.
I don’t update it. A skill I built pulls the last 72 hours of meeting notes, emails, Slack, and project files tied to each project, and rolls it all into the dashboard. I open it Monday morning and the picture is already current.
So I walk into every leadership meeting knowing where things actually stand — not where the last status deck said they stood three days ago.
This is what agentic AI looks like when it stops being a demo.
It’s a tool that knows what sources to pull from, what’s signal vs. noise, how to structure the output for the decision I’m actually making, and what cadence to keep so it stays ahead of the work. That last piece is underrated.
The architecture matters more than the model. Claude, GPT, Gemini, open source — pick your stack. What separates a useful agent from a slick demo is the orchestration. Which tools it calls, in what order, with what grounding, and how it knows when it’s done.
That’s the work. And it’s the part most enterprise AI efforts I see haven’t really started on yet.