The instinct
to see AI clearly.
Not a syllabus. A reference map of every decision point in an AI initiative — from first diagnosis to sustained deployment. Each module stands alone. Enter wherever your organization is right now.
Not another AI course
Every other program is a syllabus — start here, finish there. MitraAI is a reference. Enter at the decision you're facing right now.
Start after you've already decided to deploy AI
MIT, Wharton, Google courses teach deployment to organizations already committed. They assume the decision is made. They address the how, not the whether.
The diagnostic spine before you spend a dollar
A complete map of the AI initiative lifecycle. Every module is self-contained — facing a CFO meeting? Go to M06. Deploying next quarter? Go to M07. Prior modules add depth, not prerequisites. The quiz PDFs let you check what you already know before or after any module, in any order.
Three questions. Every AI proposal.
If the team presenting to you cannot categorize their problem as one of these three types, the initiative is not ready.
Prediction Problem?
You have historical data and want to know what happens next. Forecasting, churn scoring, demand planning.
Optimization Problem?
You have constraints and want the best allocation of resources, time, or cost. Scheduling, routing, prioritization.
Pattern Recognition Problem?
You have signal buried in noise and want to surface it consistently at scale. Fraud, segmentation, document processing.
A forward-pass.
Not a topic survey.
Each module addresses a decision point your organization will face. Start at the one you're facing today. Prior modules add depth — not access.
- Strategic Decision-MakingThe three diagnostic questions. Prediction, optimization, or pattern recognition — and how to tell before approving anything.Diagnose
- Understanding DataQuality, types, bias, and AI readiness. Why the data layer is where most initiatives fail before they start.Diagnose
- Algorithms and Decision ContextThe 25 foundational patterns, errors, and tradeoffs. Algorithms are formalized human reasoning — named, mapped, and usable.Diagnose
- RecognitionMapping algorithms to organizational processes. Five org models, their embedded algorithms, and where AI can formalize them.Decide
- Recognizing AI in Existing ToolsYour org is already an AI user. Outlook, Salesforce, Workday, ServiceNow. Governance changed when AI started acting, not just recommending.Audit
- Building the Business CaseNPV, IRR, payback — and the with/without delta that turns "we should do AI" into a fundable CFO proposal.Fund
- Deploying Without BreakingMVP, Blue-Green, and the Crawl-Walk-Run discipline. The gap between funded and live is where most AI initiatives die.Deploy
- Psychology of Metrics FramingThe same number means different things to different roles. How to present accurate data through the frame most legible for each decision-maker.Measure
- Roles and Functions Required for AIThe Human-AI RACI model and accountability structure. The Super Child Principle. Accountability assigned before deployment, not after failure.Govern
- Governance and Continuous AlignmentManaging AI systems after deployment. Data drift, concept drift, feedback loop failure. The structures that keep AI aligned with the intent of those who authorized it.Sustain
- Bonus: AI OrchestrationAgentic AI, multi-model pipelines, orchestration patterns for leaders governing systems that govern themselves.Orchestrate
Get notified when Module 1 drops.
One email. No pitch. Just the publish date.
What no other program has built
The difference is structure, not subject matter. No competitor organizes by deployable workflow.
- Start after the deployment decision is made
- Organized by AI topic area, not organizational workflow
- AI literacy as the end goal
- Separate courses: strategy, data, finance, governance
- No diagnostic spine before the commitment
- Every module is self-contained — enter at the decision you're facing today
- Full arc available: Diagnose → Decide → Fund → Deploy → Measure → Govern → Sustain
- Speed-to-decision is the outcome — process inspection to defensible ROI
- One integrated workflow spanning CS, finance, org design, cognitive science
- 9 proprietary frameworks: 9-Yard, Triple-A, Human-AI RACI, With/Without, and more
Start free. Go as deep as the decision requires.
The diagnostic spine is free. The implementation layer — templates, capstone, evaluation — is the paid product.
- All 10 core modules, full content
- Slide decks at algorithmicthinker.com/decks
- Complete diagnostic frameworks
- Share with your team
- One scenario per module — any module, any order
- Check what you know before or after watching
- No right or wrong — evaluate your own reasoning
- Each scenario references the relevant slide directly
- Bonus Orchestration module
- Capstone: bring a real initiative, use a provided scenario, or join a team — your choice
- Your case stays confidential — sanitize as needed, no org details required
- Three-pronged evaluation: your team, peer cohort as stakeholders, and AI — all weighted
- Output is a consultant-style report — what worked, what can work — not a grade
- DCF model, RACI, Business Case templates
- Open Badge certificate
- 12–14 curated senior executives
- Application-gated, never advertised
- All meals and wine included
- Introduced via post-capstone video only
Built by someone who has run these decisions.
Nandeep Nagarkar is the founder of SVAG Labs and creator of MitraAI. 25+ years of enterprise technology and transformation experience. Published author on AI leadership.
MitraAI was built because no program existed that addressed the diagnostic and governance layer upstream of deployment — where most AI initiatives actually fail.
Start with the free modules.
Build the instinct.
Ten modules. Full content. No email required. The application layer is there when you're ready.