Generic courses teach tools. This program starts with a survey of what each person does over and over, builds the curriculum from their answers, and ends with every participant using AI on their own real work.
A finance analyst, a recruiter and an operations lead repeat very different tasks. Generic examples don't map to anyone's actual day.
Watching someone else use AI feels impressive. Back at their desk, people don't know where to start with their own work.
Without guidance on what data is safe to use and when to trust an output, people either avoid AI or use it in ways that create risk.
Before any session, every participant answers a short survey: the tasks they repeat, how long each takes, the tools and data involved, and how comfortable they are with AI today.
The answers become a task inventory, and the curriculum is built from it. Examples, exercises and tools all come from your team's own workflows, matched to their starting level.
Live, hands-on sessions where people work on their own tasks, not toy examples. Short concepts, then practice, with support between sessions.
Small projects run alongside every module, and the program ends with a capstone: each person or team implements an automation for one of their recurring tasks and presents the result.
Participants learn the same method we use in deployment work: look at each recurring task and decide which of four buckets it belongs in. Once people can do that, they keep finding new opportunities long after the training ends.
Every curriculum is built from the survey, so the mix and depth change from team to team. These are the building blocks most programs draw from.
What models are good at, why they make mistakes, and how to check their work.
Writing instructions, examples and templates that produce reliable results on recurring work.
Summarizing, extracting and analyzing information from files, spreadsheets and reports.
Connecting AI to the tools you already use so multi-step tasks run with less manual effort.
Custom assistants and agents for team-specific work, for groups ready to go further.
What data is safe to use, privacy and compliance basics, and your organization's own policies.
For professionals who want to use AI in their own role. Same survey-first approach, with six weekly sessions built entirely around your tasks and one project you implement along the way.
For teams of up to 12. The full program: survey of every participant, a custom curriculum, live hands-on sessions, projects throughout and a capstone where each team ships an automation for its own work.
For managers deciding where AI fits: how to spot high-return opportunities, set usage policies, and measure whether adoption is paying off.
I'm Tunga Tessema, Head of Product at a US healthcare company and an AI and data engineer. Before building products, I taught software engineering at Addis Ababa University, supported courses at Carnegie Mellon and taught web development to students in Atlanta. I design training the way I design software: from the user's real needs.
No. The survey tells us where each person starts, and the curriculum meets them there. Technical teams go deeper into automation and building assistants.
The ones your organization already has or has approved. If you haven't chosen yet, we'll recommend options based on your work and your data requirements.
Live online sessions scheduled in your time zone, with async support between sessions. In-person sessions can be arranged on request, with travel and accommodation covered by the client.
Yes, within your policies. We agree up front which data and tools are approved, and projects use sample or anonymized data wherever sensitive information is involved.
Book a 30-minute call. We'll talk through your team and goals, and we'll show you the survey your people would answer.