TRAINING
From learning about AI to organizations that build with it.
Not one-way lectures — programs where participants find problems,
use generative AI, shape ideas, and carry them into execution.
Executive AI strategy workshops
Reframing AI as a management agenda with real priorities.
AI opportunity discovery workshops
Finding and prioritizing use cases from real operational problems.
AI risk, ethics, and governance
Turning defensive concerns into workable rules.
Understanding cannot be outsourced
Distinguishing decisions that can be delegated to AI from those that cannot.
Hands-on generative AI training
Learning through direct application to participants’ own work.
AI hackathons
Two days from problem discovery to working concepts.
Vibe Coding for non-engineers
Non-programmers shipping real apps with generative AI.
From prompting to AI-agent design
Moving from using AI to designing the system around it.
Requirements engineering for AI agents
Roles, authority, stopping rules, and accountability.
Evaluation design for AI projects
Metrics and validation plans that move beyond the PoC stage.
Multi-agent development lab
An intensive path from design through implementation and evaluation.
Automorphic development in three-person teams
A small-team pattern for fast development with generative AI.
Generative AI in schools and universities
Course design, assessment, and protecting learner agency.
Teaching app development with Vibe Coding
Designing classes that put students on the maker side.
AI mentors, personalized learning, and career support
Using learning and dialogue logs responsibly in education.
- AI use-case map of your organization
- Prioritized adoption candidates
- Working AI prototypes
- A lightweight requirements brief for an AI agent
- 90-day action plan
- A draft set of AI-use rules
- 01
Discovery
Who is in the room, and where the organization stands with AI.
- 02
Design
Lecture/workshop balance, materials, and deliverables tailored to you.
- 03
Delivery
Half-day to multi-day; on-site or hybrid.
- 04
Follow-through
Review of outputs and a bridge into execution — development or advisory.
Training is measured not by what participants heard, but by what they built and decided. We define the take-home outputs before the program begins.
Let’s create an AI workshop inside your organization.
Tell me the audience, headcount, and where your organization stands with AI.