For over 14 years I have worked on teams tasked with collecting, modeling, and activating data across organizations. The goals have always varied, but I've learned to simplify them into two: we are either trying to improve the customer experience or improve the employee experience. And to do either correctly, the tools collecting the data, the tools modeling it, and the tools exposing it have to work in perfect sync. Any break in that chain undermines the whole objective.

Historically, that sync has been hard to achieve — too many integrations, too many repositories, too much institutional friction. But with AI-generated code, that is changing. Context is everything. When an AI agent can explore an entire project — from the moment a customer clicks something, to the event that fires, to the notification that lands in a rep's queue — it becomes a genuinely powerful and productive tool. I've been living that for the past six months, and the results have been remarkable. No use case is too complicated when one of those two objectives is clearly understood.

That is the business case, and companies have already started to figure it out. When the innovation directly impacts the bottom line, that part takes care of itself.

What I find more compelling — and more urgent — is what happens when you take this same empowerment and point it at problems outside the business sphere.

We are a country in a difficult moment. Public discourse has fractured. Lines have hardened. And a lot of that traces back to a decade of information abundance with very little quality control — the volume of what we consume has exploded while its trustworthiness has collapsed. Meanwhile, our public institutions have stayed quietly in the background, not taking advantage of the same innovation that has transformed the private sector. Their incentives are less legible than a bottom line, and the result is that almost no progress has been made.

This is where I believe AI becomes one of the most important public tools in a generation. LLMs are only as powerful as the context they are given and the tools they have to retrieve supporting data. Right now, most government institutions lack that infrastructure — or if they have it, they don't make it accessible. That gap is the problem I want to work on.

This site is where I am trying to put that belief into practice. The first project is Ward 51 — built with AI tools to surface Illinois, Cook County, and Chicago public data, and make the political decisions happening in your community actually comprehensible. Alongside it, I'll publish pieces on the two Chicago Fires: the soccer team and the television show. Because while this work comes from a serious place, it would be a mistake to take it so seriously that there's no room for joy. The show has run long enough to say something real about how Chicago sees itself — big but balanced, opinionated but fair. And the team is in the middle of a rebuild worth watching: investing in the city, embracing its international footprint, and building something Chicagoans can grow with.

Maybe this takes off. Maybe it doesn't. If it sparks one idea in one reader's mind about what AI can do for the public good — especially given the skepticism AI is navigating right now — I'll consider it worthwhile. The potential I'm most excited about isn't efficiency. It's accountability. The ability for ordinary people to hold those in power to a higher standard, armed with the same data those in power have always had.

If you have thoughts, questions, or disagreements, please reach out. This is not an easy topic, and change is always hard. But I am trying to be ready for it.