No magic — just 30 years of knowing what actually works. Your developers own every line. AI is the tool, not the answer.
You define the what and why. AI handles the how. But you still own every decision — because accountability can't be delegated to a text generator.
Why accountability matters →Senior developers see 5-8x gains. Not because AI is magic — because experienced people know what to feed it. Juniors without guidance just make faster mistakes.
Vibe coding vs orchestration →We don't create dependency. After training, your people know how to work with AI themselves. That's the whole point — we build capability, then we leave.
The human-in-the-loop approach →From teams we've trained — not theory, not projections.
Development teams ship real code to production during training. Not demos, not sandboxes — their actual codebase, their actual deadlines.
Senior developers with deep domain knowledge see the biggest gains. The more you know about your system, the more AI amplifies your output.
Teams are consistently surprised by how little AI actually costs when used correctly. The investment is in people, not tokens.
Own every line
You own every line of code. AI is the tool, you're the professional. No blame-shifting, no hiding behind automation.
The no shortcuts principle →Understand everything
Every line understood. Every change validated. You remain in control because you're personally responsible for what ships.
Vibe coding vs orchestration →Validate systematically
Based on real enterprise feedback: testing is the #1 concern. Comprehensive testing strategies are built into every technical track.
Developer accountability →Not theory
Not theory. We're actively building with these methods and training organizations right now. Methods refined through real implementations, not conference talks.
Beyond prototypes →What gets left out of the sales pitch.
Free tier gives you about 3 A4 pages of context. That's why your AI 'forgets' mid-conversation. The million-token marketing? Mostly irrelevant for real work.
Read the full analysis →Testing costs almost nothing. Production costs 10-100x more. Nobody mentions this until you've committed. We show you the real numbers upfront.
See real numbers →Where does your data go when you use AI? Who trains on it? Multi-component AI creates complex security surfaces. Your responsibility, not the vendor's.
Understand the risks →From boardroom understanding to hands-on building
Executives, board members, decision makers
2-8 hours
What does AI actually cost? Where does your data go? What can't it do? We give you facts, not sales pitches. You'll leave knowing what questions to ask.
Consultants, researchers, legal professionals
4-6 hours
Turn document chaos into structured knowledge. AI-powered organization with your actual files, not demo data.
Development teams, technical leads
8 hours
The core track. Your developers learn to work with AI using their own codebase. Voice-to-specification, context window mastery, production deployment. We build real things.
Senior developers, CTOs, architects
6-8 hours
Testing strategies that actually work with AI. Legacy modernization. Governance frameworks your organization can live with.
Two working implementations of voice-to-structured-data. Open source, used in production, available on GitHub.
Meeting recordings processed into documentation with decisions, action items, and searchable history. The transcript skill handles extraction — you direct what matters.
Voice reflections processed into five connected documents that accumulate over time. The goals skill detects what you missed and asks you to complete it.
"The shift isn't about writing less code — it's about thinking at a higher level. You become the conductor, not the typist."
"I was skeptical. Then we built something real in three hours that would've taken two weeks. Same quality, my code, my responsibility."
"We replaced $50,000 in traditional development costs with $20 in AI tokens and 3 hours of orchestration time."
"It's not about the time you spend — it's about the time you've invested. 30 years of experience is what makes AI useful."
Guides for developers, team leads, and decision makers. The methodology, the tools, and the honest assessment of what works and what doesn't.
We'll tell you what will work and what won't — before you commit to anything.
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