CHESTON RILEY
Senior practitioner
Data discipline. Custom AI builds. Practical leadership.
Did AI write this? Dang right they did! I trust my team.
Data discipline. Custom AI builds. Practical leadership.
Did AI write this? Dang right they did! I trust my team.
You probably should be a little scared.
A lot of dashboards lie a little. Some lie a lot — not from malice, but from the shortcuts that ship under deadline and quietly stay for years. I've made those shortcuts. Now I help leaders see what's actually underneath.
I know where the bodies get buried.
I'm the auditor with practitioner's eyes.
I find what your dashboards are hiding.
Engage me. Your CDO should be an ally in this conversation.
If a question is forming, contact me.
You are going to get a product, not a Power Point.
I build AI applications for companies that want results, not exploration. Revenue lifted, cost cut, or time saved — scoped before the engagement starts, measured at the end. If AI is the wrong tool for the problem, I tell you that out loud, up front.
Real results beats polished problems.
I won't force an AI solution if it is the wrong move.
Iterate. You are in the loop.
Engage me when you want the solution, not the power point.
If a question is forming, contact me.
Closing the gap.
01 The problem
The most dangerous analyst is the one everybody likes.
Fast. Never pushes back. Clean SQL, and nothing ever comes back for rework.
Somewhere in that run of clean work is a number that was technically right and conceptually wrong — shipped, trusted, and sitting inside a decision nobody will trace back.
Nothing upstream catches it. There is no test for judgment, and nobody ever sat down and taught it.
02 The principle
Technical skills are tablestakes. Acting like a partner advances everyone.
The principal analyst in the room isn't there because of years of SQL. They're there because they operate with wisdom — clients, definitions, bad data, the questions everyone else didn't ask. I will teach you that.
03 The course
Two days
Nobody gets warned. They get the request and the data cold, they step on the trap, and only then do I teach it. The lesson lands differently when you just made the mistake yourself. Scars without the wounds.
Every one of these feels like covering yourself the first time. It is not. It is what the good ones already do, and nobody wrote it down for them.
They come back eager to work this way rather than careful about it.
Engage me to compress the analyst's path to principal.
01 The problem
Two reports. Both correct. Completely different numbers.
You have sat in that meeting. It gets settled by taking whichever number sounds more like what the room already believed.
You would never accept that on a forecast, or a hire, or a schedule — you know enough to push on those. Data is the one discipline nobody ever expected you to pick up.
So the number goes unchallenged. And it decides something.
02 The principle
Trust comes from dialogue. Dialogue comes from going one layer deeper.
Imagine how much more powerful you'd be if you understood one thing about this you don't today. The basics are easier than you think — easier than finance, easier than HR. Your data team already crossed over to your business language. You haven't crossed to theirs. When you can meet them one layer deeper — when you can ask the question and follow the answer — the dialogue changes. You stop being your data team's customer. You start being their partner.
03 The course
One day
Not a briefing. You go behind the curtain into the part you only ever hear named. ELT, joins, grain, nulls. Words that get used in meetings you sit in, that nobody has ever actually shown you. You will take a pile of records and turn it into a number yourself.
You know enough finance to challenge a forecast. Enough HR to challenge a hire. Enough operations to challenge a schedule. Data is the one discipline nobody ever expected you to pick up. That made sense once. It does not now.
Data is a discipline. You learned the others, and this one is easier.
Engage me when you're done nodding through dashboard reviews.
If a question is forming, contact me.
Make the organization run for you.
A lot of leaders aren't in command of their own operation. They can sense it across their dashboards and their direct reports, but they can't say it out loud and don't know how to fix it. I do.
From “I don't know what's going on” to “I'm running the show.”
I've assisted leaders with chaos. I know how to help them take control.
Scorecards, transparency, management routines. Unapologetically build what you have been wanting.
Engage me as your translator into your own operation.
If a question is forming, contact me.
But not the kind of AI Leadership you were thinking.
Building AI teams isn’t about endless skills and commands. It’s about leadership — the thought pattern that lets a team get better the way the technology gets better. Management adds tools to a flat list. Leadership connects them into a system that compounds.
It may not necessarily make AI better. But I know it makes me better.
I approach AI the way I approach leading people.
I’m not afraid to be the student in the room.
Engage me to lead. I'm the player-coach.
If a question is forming, contact me.
Other functions get treated as disciplines. HR, finance, project management — people learn the pieces, get comfortable, and own the practice. Data doesn't get that treatment. It gets treated like a giant spreadsheet in the sky — something other people make, something other people "know," something to be feared or trusted blindly. It isn't. Data has standards. It demands humility. It rewards judgment. The first thing I want to change is how you think about it.
Buying more tools doesn't fix it. Most teams fail at data because they learn to talk about it without learning to think with it. The vocabulary fills the room. The discipline doesn't grow.
A confident slide is not a defensible decision. When narratives replace inquiry — when the story crowds out the question — decisions break quietly, and the data takes the blame.
A number can be technically right and still used wrong. Interpretation — knowing what it means and what to do with it — is a leadership job. No tool fixes that for you.
Some companies aren't short on smart people. They're short on permission to say what's wrong. Agency is the willingness to name it — and to act.
Nobody in data sets out to confuse you — but when data isn't treated like a discipline, fewer people learn its pieces, and the rest end up scared of it. You should be able to own your data the way you own your hiring decisions or your budget.
Data without definition isn't information. It's numbers pretending to be measurements. Anything you build on it is a guess pretending to be a decision.
Data people are expected to learn the business. Non-data people aren't expected to learn the data. That's a wasted asymmetry. Close it, and everyone gets more powerful.
Cheston Riley · The gap
Everything upstream is somebody's profession, with standards and review. The step where a number becomes a decision is nobody's. Ask who owns it and it turns into an IT problem or a business problem. Neither of which is an answer.
Analyst side
The junior analyst
Nothing feels wrong. That's the tell.
If a question is forming, contact me.