Kosi Uzodinma · Lead Data Architect, General Mills

The people winning with AI aren't the smartest ones. They're the most clear.

I help business owners and professionals choose the right AI tools and build something that works. No technical background required.

Kosi Uzodinma, Lead Data Architect and AI speaker

About

I am a Lead Data Architect at General Mills. I have spent years making AI and data tools work inside a large, complex organization. What I learned there is simple: the tools are not the problem. People do not know which one to reach for. And they are not clear enough about what they are trying to build.

AI feels like the internet did in the late nineties — a once-in-a-generation shift where most people are not sure where they fit in what is coming. Some think it will take everything. Others think it is overhyped. Most are somewhere in the middle: curious, a little overwhelmed, not sure how to start. I built my work for those people.

Outside of work, I build for real clients. A real estate investor writing letters of intent manually for every deal now generates them in under two minutes. A marriage counselor without a development budget built her entire practice website without a developer and owns it outright. I build for myself too: a personal operating system that remembers my financial goals, training protocol, and the decisions I have already made, so I can show up and work without re-explaining my life. I have tried most of the tools that exist, not to collect them, but to understand what each one is actually designed to do. That is the work that makes me a useful guide, not a theorist.

Before General Mills, I spent two years as a Young Adult Pastor: preaching, teaching, and leading discussions with people at very different starting points. That is where I learned how to hold a room.

The Clarity Method

The two things that make AI work for you.

The underlying models are impressive. That is not the gap. The gap is between what a model can do and what the application built around it was designed to do. Every company building on top of AI is solving a different problem. If you do not know which problem a tool was built for, you will keep reaching for the wrong one.

Pillar One: Tool Literacy

Think of it like trades. A handyman can do a lot: hang a door, patch drywall, fix a cabinet. But there comes a job where they hit a wall. Rewiring a panel. Running new plumbing. Not because the job is too hard. Because it requires a specialist. You would not call a handyman to wire a new circuit. You would call an electrician. AI works the same way. There are tools built for conversation. Tools built to write and run code. Tools built to retrieve from your documents without losing context. Tools built to generate images. Each one was designed with a specific job in mind. The skill is knowing which one to call.

Pillar Two: Clarity

AI does not know what you need. You have to. Most people open a tool and start typing without knowing what they are asking for. They get something that sounds right but does not help. Your industry knowledge, your experience, your judgment: that is the raw material these tools run on. AI multiplies what you bring. The people who get results are not smarter. They are more specific. Getting clear about what you want, before you open any tool, is the skill that changes everything.

“The tools will do almost anything. Knowing what to ask for is the whole job.”

Bring this framework to your audience.

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Builds

I build with AI tools the same way I teach about them: clear problem, specific tool, honest assessment of what worked.

ClaudeClient Work

LOI Automator

Problem

A real estate investor client was hand-writing letters of intent for every property offer. Same format. Different numbers. Every single time.

What I Built

A tool he describes a deal to in plain language and receives a complete, properly formatted letter of intent in under two minutes. He kept the judgment. I removed the friction.

The Lesson

The friction was not in the decision. It was in the document. Identifying that distinction is the whole job.

LovableClient Work

Marriage Counseling Website

Problem

A marriage counselor client was building her practice with her own curriculum and methodology. She needed a client-facing website but did not want recurring platform fees or a developer she would have to call every time something needed to change.

What I Built

A full website where she can present her services, share her approach, and collect client inquiries. Built entirely in Lovable. She owns it outright, saving over $1,000 in development costs and replacing a Google Docs intake process with a professional client-facing site. No platform dependency, no ongoing fees, no developer required.

The Lesson

The goal was not a website. The goal was independence. Knowing which tool gives you that matters as much as knowing how to use it.

Claude CoworkPersonal Build

Personal Operating System

Problem

Every major area of my life was siloed: career, finances, training, health, nutrition, relationships, business. I had tools for some of it and notes scattered across the rest. Nothing held the full picture, and nothing connected the dots between them. Every time I sat down to think through something real, I was starting from scratch.

What I Built

A Personal OS in Claude Cowork with nine workstations covering every area of my life. Each one has its own memory and rules. A master constitution governs how they interact when a decision touches more than one area. It knows my salary, my financial philosophy, my training protocol, and the calls I have already made. When I was deciding whether to sell my rental property, it already held the financial context. The answer was clear: I was profiting and did not know it. I open it and pick up exactly where I left off.

The Lesson

Without context, you cannot get the right answer. You are guessing, or the tool is making assumptions based on generalizations that have nothing to do with your actual situation. The system works because it holds the context. Walk in with the right context and the right answer is usually obvious.

PerplexityPersonal Build

BibleScholarGPT

Problem

Reading Scripture without historical and cultural context means missing most of what is actually there. Ten open browser tabs later, you still are not sure what to trust.

What I Built

A personal Bible study companion that gives historical context, original audience perspective, word studies, and cross-references for any verse. Not a replacement for study. A research assistant that handles retrieval so I can focus on the real work: reflection.

The Lesson

AI is not a rabbi. It is a research assistant. Knowing the difference before you start is the whole point.

GeminiPersonal Build

YouTube Key Points Summarizer

Problem

Most podcast episodes are not worth 40 minutes to find out if they are worth 40 minutes. The queue piles up and the guilt sets in.

What I Built

A Gemini gem that extracts main points and creates analogies for each takeaway from any YouTube link. Gemini was the deliberate choice: YouTube is Google, and the integration is architecturally tighter than any workaround.

The Lesson

Infrastructure matters. The right tool often is the one with the least resistance.

Xcode + CodexPersonal Build

UzoFitness

Problem

Every gym session was tracked in a notes app or not tracked at all. No history, no progression data, no way to look back and see if the work was actually working.

What I Built

A native iOS gym logging app built with Xcode and Codex. Log workouts, track sets and reps, and build a personal training history that persists. The data belongs to the athlete, not a subscription.

The Lesson

The best tracking system is the one you keep using.

Writing

I write about what I actually build: the problems, the tools, and what came out the other side. Published on LinkedIn.

He Was Writing the Same Letter Five Times a Week. We Fixed That.

A real estate investor was drafting Letters of Intent by hand for every offer. The task was simple. He just had not built the system to do it for him. That is what we built.

Read on LinkedIn →

The Bedtime Stories I Couldn't Find, So I Built Them

My son had read every book we owned. The library had gaps. So I built a tool that generates illustrated stories where he is the main character. In under five minutes, every night.

Read on LinkedIn →

The Macro Tracker I Built Because I Was Tired of Weighing Food

Tracking nutrition works until the friction kills the habit. I stopped weighing food and started talking to my tracker instead. Here is what I built and why it actually stuck.

Read on LinkedIn →

How I Use AI to Study the Bible Without Cheating Myself

Context matters. Culture matters. I built a personal Bible study companion that gives me historical context, original audience perspective, and word studies, so I can do the real work: reflection.

Read on LinkedIn →

Read by 237+ professionals on LinkedIn.

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4.5 / 5

average rating across all training programs

Testimonials

You did a great job and helped demonstrate what adoption looks like at your company. I can tell the participants enjoyed it.

Event Organizer, GitHub Meetup

You are great at moving people towards adoption and communicating ideas.

Senior Manager of Data Architecture, General Mills

I never had a curriculum or clear pathway to understand what I should know as a data engineer. This changed that.

Data Engineer, General Mills

This is exactly what we need to start automating our business to free us up to do more high value work.

Real Estate Investor

I had an idea and didn't know it was possible and after talking to Kosi about my needs he created a platform that is perfect for my practice.

Marriage Counselor

Speaking & Training

I give audiences a framework they can put to work the next day. I speak at conferences, professional associations, masterminds, schools, and universities. If your audience includes business owners, leaders, or professionals who know AI matters and have not found a practical path into it yet, that is who I am built for.

Talks

Clear Over Smart

Keynote

The Two Skills That Separate AI-Effective Professionals from Everyone Else

Most professionals who struggle with AI blame the tools. The tools are fine. This talk identifies the two skills that determine whether AI works for you: knowing which tool is designed for what, and being specific enough about what you want that the tool can deliver it. Audiences leave with a framework they can apply the next day.

45–60 min

Pick the Right Tool

Workshop

A Practical AI Workshop for Business Owners and Teams

A hands-on session for business owners and professionals who have tried AI, gotten mediocre results, and are not sure why. We map the AI ecosystem by what each tool is designed to do, identify where your current workflow has the most friction, and leave with a specific tool tied to a specific problem. No technical background required.

90 min – half day

What AI Can and Cannot Do

Fireside chat or breakout

An Honest Conversation for Leaders Who Need to Make Decisions

A direct conversation about the current state of AI tools: what they are genuinely good at, where they fail, and how leaders should think about bringing them into their organizations. Designed for decision-makers who need to act on AI without becoming technical experts.

30–45 min

AI Literacy for the Real World

Keynote or classroom session

What You Need to Know Before You Graduate

A session for students on how to think clearly about AI as a skill set, not a threat. Covers the AI tool ecosystem, the clarity required to use these tools effectively, and what it actually looks like to build with AI in the real world. Designed for any major, any background.

45–60 min

  • Conference keynotes and breakout sessions for professional associations, mastermind groups, and community organizations
  • Workshops for small business owners and entrepreneurs who want to use AI but have not found the right entry point
  • School and university programs on AI literacy, practical tools, and how to think clearly about what you are building

Upcoming

EventOrganizerDateFormat
DevColor Member Led Professional Development Workshopdev/colorOctober 29, 2026Virtual

Past Sessions

  • How We Increased AI Adoption, GitHub Meetup (~50 attendees)
  • AI and Data Engineering Training Program, General Mills — two-year internal curriculum for data engineers and data scientists (2023–2025, 50+ attendees)
  • Diversity and Inclusion speaker, General Mills — company-wide sessions (300+ attendees)
  • Career Mentorship Program, Possible — prepared 10 college students for careers in data engineering
  • AI Tool Training, Dean of Students — one-on-one session on using Microsoft Copilot for data analysis
  • AI Workflow Automation, Real Estate Investors — private session on using Claude and Cowork to automate business operations (2 attendees)

Bring Kosi to Your Audience

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