Stop watching
AI happen. Start shaping it.
You already use ChatGPT. You know what RAG is. This is the 100-day program where you find out what was actually true — and take it ten levels further. Trinity coaching, Pitstop support, and a credential you can defend in front of a board.
You don’t have an AI knowledge problem. You have a context problem.
Most senior professionals trying to learn AI fail in the same four ways. The pattern is so consistent we built the program around breaking it.
After eight years leading product, I'd rather sit through a board review than open another “Intro to LLMs” tutorial.
- 01The endless tutorial loopHours of YouTube on prompting. None of it survives Monday morning.≈ 14 hrs lost
- 02The MOOC graveyardThree courses started. Zero completed. Certificates aging on LinkedIn.≈ $800 wasted
- 03Tool-soup paralysisTabs open: ChatGPT, Claude, Copilot, Cursor, n8n. None integrated into your actual work.0 shipped
- 04Stuck without a peerNo one to ask when the model is wrong, the API breaks, or the prompt won’t generalize.−5 hrs/wk
Three real participants. Not two pretending to be three.
A learner alone with AI is a chatroom. A learner alone with a human is a tutorial. A learner with a pair and an AI is a triangle — the only stable structure adult learning at scale survives in.
Three phases. Twenty minutes each. The Trinity in motion.
Every hourly arc is the same I-do / We-do / You-do model that built apprentice systems for a thousand years — made structural, then rebuilt around the Trinity. Repetition is the point.
I Buildi.
MAIA builds in front of you, narrating the move. You watch, annotate, and ask — no keyboard yet.
We Buildii.
You and your pair build it together. MAIA is the third participant — referee, refresher, refactor. The Trinity, in full.
You Buildiii.
You build it solo. MAIA is on tap but silent unless asked. Your pair reviews on ship. The hand-off is the proof.
Kolb's first stage. You see the move performed before you attempt it. Cognitive load is on observation, not generation.
Kolb's middle two stages. Dialogue with a peer is where principles get extracted from examples. The AI keeps the dialogue honest.
Kolb's fourth stage. You apply the principle, alone, in a new context. Mastery accrues here — only here.
One minute of your Theater phase, on a real session.
No keynote. No marketing reel. Instructors and students working through a real problem on a real system — same room, same recording, unedited.
The 100-day arc.
Six levels. Twenty blocks. Approximately two hours a day for mid-career schedules. The same spine for everyone; a fork at Level VI.
| Phase | What happens | Outcome | |
|---|---|---|---|
| Days 01–15 | 1. Ground Truth → AI Operator | Calibrate what you already know against what is actually true. How LLMs really work, where they fail, the operator’s mental model. | Read any AI capability claim and know what it can and cannot do |
| Days 16–35 | 2. The Toolkit → AI Practitioner | Daily reps in Claude, ChatGPT, and Cursor. Move from one-off prompts to durable, measurable workflows you own. | A reusable prompt + workflow library applied to your real work |
| Days 36–55 | 3. The Field → AI Builder | Take the toolkit into your day job. Ship one real initiative other people use. Weekly critique from a senior engineer. | One AI initiative shipped inside your company |
| Days 56–75 | 4. The Craft → AI Specialist | Move from delivery to depth. Real fluency in agents, RAG, evals, multi-agent. The team’s go-to AI specialist. | Pattern depth across the surfaces that matter in production |
| Days 76–90 | 5. The Forge → AI Founder | Author a complete AI system end-to-end with your Pair. Pair-attested, replay-able, evaluated. The work that founds a capability. | A portfolio artifact you can defend in a board review |
| Days 91–100 | 6. The Charter · or · The Architecture → AI Strategy Architect · or · AI Solutions Architect | Fork. Business depth (strategy, governance, transformation) or production depth (MLOps, scaling, observability). Capstone deployed on Kapi. | A credential triangulated by simulator + MCQ + pair attestation |
Built for mid-career professionals.
Three quarters of our learners have ten or more years of experience. The program assumes you already know how to ship; we focus on what you don’t.
The senior PM
Eight years shipping. Now expected to make every roadmap an AI roadmap — without hand-waving.
The analyst
Deep in spreadsheets, dashboards, models. Wants to extend the toolkit, not be replaced by it.
The team lead
Runs a 12-person team. Needs to evaluate AI proposals on substance, not be talked past by them.
Eight things, all included.
No upsells. No premium tier. Tuition covers everything from kickoff through graduation and the alumni access that follows.
100 days of structured curriculum
Six levels, twenty blocks. ~2 hours a day. Designed for mid-career schedules.
Pitstop — never stuck for long
Real engineers on call when MAIA can’t close the gap. The thing that breaks the MOOC pattern.
Pair learning with a partner
A human counterpart for the full arc. Attests your demos. Rotates each block.
Live cohort sessions
Weekly classroom plus a contest and a peer-study slot. Cameras on, problems on the table.
A specialization fork at L6
Choose business depth (Charter) or production depth (Architecture) in the final stretch.
Triangulated mastery validation
Simulator missions + MCQ banks + pair-attested Kapi project. Three signals, none fakeable in combination.
A portfolio shipped on Kapi
Your capstone deploys to a real URL. Defensible in interviews. Visible to alumni.
Lifetime alumni network
2,500+ graduates across six years. Access to future cohorts, events, and AIPL community clubs.
One fakeable signal. Two unfakeable ones. A credential that means something.
MCQs can be gamed. Demos can be staged. Three independent signals, validated in sequence, cannot. We borrow the architecture medicine, aviation, and security all arrived at independently — and apply it to AI fluency.
The same architectural answer medicine, aviation, and security all converged on independently. Not novel pedagogy. Applied pedagogy.
Never stuck for more than an hour.
MOOC failure is rarely a curriculum problem — it's a momentum problem. A real engineer answers on Pitstop within the hour, including weekends. The Pair holds you to the rhythm. MAIA covers the in-between.
“I was stuck on a retrieval pipeline at 11 pm on a Sunday. An engineer was on a call with me by 11:42. That's when I knew this was different.”
Three-day intensives, taught by working practitioners.
Standalone short-format programs alongside the 100-day arc. A useful first taste — many graduates start here before continuing into the full program.
We’re not just teachers. We’re practitioners.
The team behind Mitra — India’s first social robot — now building the next AI conglomerate. Every instructor has shipped real AI systems into production. We teach what we’ve actually deployed, and we still deploy.
Dr. Balaji Viswanathan
Ex-Microsoft. Led the creation of Mitra, India’s first social robot, deployed at major airports and enterprise events. Most-followed person on Quora with over a million followers.
Mahalakshmi Radhakrishnan
Roboticist and engineering leader. Co-created the Mitra robot’s intelligence layer. Has shipped human-robot interaction systems into production enterprise environments.
Ready to stop watching and start shaping?
Rolling enrollment, pair-matched on signup. Tell us where you are — an admissions lead replies within two business days. No GMAT, no essays.
Prefer a human first? Use the form — an admissions lead replies within two business days.
