Foundations of AI-Augmented Architecture with Claude and Sparx EA
You've got Claude and Sparx EA — now learn to do AI-Augmented Architecture with them. A private cohort course, taught on your own models and standards, powered by our own AI Power Tools for EA.
Format: private team cohort · Hands-on, on your repository · Prerequisites: Sparx EA + access to Claude
Access isn't capability
Turning on Claude doesn't make a team good at AI-augmented architecture, any more than opening Sparx EA makes someone an architect. The agents amplify expertise; they don't manufacture it. To get reliable results, an architect has to know how to direct the work — what to model, what standards to check, what "good" looks like in their repository.
That's what this course builds. Not button-clicking — the craft of working with Claude as a capable collaborator that takes your direction, works your live repository, and handles the mechanical steps, while your judgment stays in the loop.
What the cohort covers
Claude, for architects
Working fluently in Claude Cowork (and Code, if you prefer the terminal): prompting for architecture work, directing multi-step tasks, and keeping control of the outcome.
Sparx EA via MCP
How AI Power Tools connects Claude to your live repository over COM/MCP — elements, packages, diagrams, tagged values — and why working against the running model changes everything.
The four use cases
Modeling, analysis, governance, and stakeholder engagement — practiced on your real models against your own MDG standards.
Module by module
Orientation & the connection
Set up Claude against your Sparx EA repository via AI Power Tools. Understand the architect-drives/AI-executes model, and run your first guided task end to end.
Modeling on real inputs
Turn spreadsheets, documents, and inventories into properly stereotyped, connected diagrams. Reverse-engineer source data into the repository. Work within your MDG, not a generic default.
Analysis & governance
Relationship discovery, impact tracing, and dependency health; then validating against your standards and producing review-ready findings. Where automation checks completeness — and where you confirm correctness.
Stakeholder engagement & habit
Produce business-readable outputs from the model, and build the working habits that make this stick after the cohort ends.
Why this beats generic AI training
A generic Claude course teaches you to chat. This teaches you to do architecture — on your repository, in your MDG, with the connective tooling we build and use ourselves. You leave with a portfolio of real work produced during the program, not exercises. And because it's the deep path, you go further than any other tool allows.
Other Foundations
Bring the cohort to your team.
A conversation first — we'll confirm prerequisites and scope a cohort to your repository and goals.
Talk to us →