AI Problem Framing for AI Practitioners

Rajiv Shah

ML Engineer with 10+ years of experience

Most AI fails from bad framing, not bad models. Learn to fix that.

AI Problem Framing is to AI practitioners what System Design is to software engineers and Product Sense is to PM. This is the foundational thinking skill that separates senior from junior.

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🚨 Pilot cohort: February 16 – March 20, 2026 - limited to 25 students. 🚨

This is the first run of the course, that means:

Never before published material, you see it first!

• Smaller cohort = more direct access to me

• Pilot pricing won't last

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What you get:

🔄 The Loop, a 5-step framework you'll use to think through every AI project

🧑‍🏫 Live sessions and office hours where you can bring your real problems

📊 Access to 150+ case studies, the largest collection of AI reframing examples

📋 Production-ready checklists for RAG, Forecasting, GenAI

🎥 Lifetime access to all recordings

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This course is for you if:

• Your AI works in demos but fails in production

• You've spent months on a model only to realize you solved the wrong problem

• Stakeholders ask for solutions that feel wrong, and you can't explain why

• You're leading AI initiatives but came from engineering or product (not ML)

You'll learn from 150+ AI failures in 5 weeks. You gain years of experience and recognize the scars.

What you’ll learn

How to think through AI problems end-to-end: scoping, debugging, and knowing when to pivot.

  • Use the Loop: a 5-step framework (Outcome, Deconstruction, Alternatives, Trade-offs, Signals) for your AI solutions

  • Learn to ask the questions that reveal whether you're solving the right problem.

  • Recognize the signals that tell you what's actually broken.

  • Learn whether to fix the data, fix the architecture, or fix the framing, and how to tell the difference.

  • Shift from executor to AI Architect: question requirements before building them.

  • Push back with evidence: "I know you want a chatbot, but here's why search is better."

  • Study real failures so you can spot the warning signs before they become expensive.

  • Set realistic expectations and catch bad framings before the team spends months on them.

  • Translate AI trade-offs into business terms stakeholders actually understand.

Learn directly from Rajiv

Rajiv Shah

Rajiv Shah

Enterprise AI veteran: Shipping AI to production, with clarity and humor

Hugging Face
DataRobot
Contextual AI
Snowflake
Snorkel AI

Who this course is for

  • Engineers who can build AI but want to master outcome engineering: knowing what to build, not just how

  • Building RAG, agents, or ML models? Let's get your demos into production! Learn the thinking that makes the difference.

  • Tech Leads and Engineering Managers who need to evaluate AI/ML proposals and catch bad ideas early

Prerequisites

  • You understand what AI/ML is at a conceptual level

    We focus on framing and strategy, not explaining what models or training means. Basic vocabulary lets us go deeper faster.

  • You've worked on or led AI projects in some capacity

    Real experience gives you context. The frameworks click when you can map them to projects you've actually built or managed.

  • No coding during the course; frameworks for thinking, not tutorials

    This is about decision-making, not implementation. You'll learn what to build and why, not how to code it.

Course syllabus

9 live sessions • 60 lessons • 11 projects

Week 1

Feb 16—Feb 22

    Lesson 1: Sharpening Your Approach to AI Problems - Developing the Mindset

    7 items

    Lesson 2: AI Alternatives - What is Possible with AI

    15 items

    Feb

    17

    Optional: Exercises + Live Office Hours 1

    Tue 2/177:00 PM—8:00 PM (UTC)
    Optional

    Feb

    19

    Optional: Exercises + Live Office Hours 2

    Thu 2/199:00 PM—10:00 PM (UTC)
    Optional

Week 2

Feb 23—Mar 1

    Lesson 3: The Loop - A Framework for AI Problem Framing

    10 items

    Feb

    23

    Optional: Exercises + Live Office Hours 3

    Mon 2/237:00 PM—8:00 PM (UTC)
    Optional

    Feb

    26

    Optional: Live Office Hours 4

    Thu 2/264:00 PM—5:00 PM (UTC)
    Optional

Schedule

Live sessions

2 hrs / week

Combination of live sessions covering material and office hours for your questions. Depending on the time zones of the final cohort, I may adjust some of these time to cover as many people as possible.

    • Tue, Feb 17

      7:00 PM—8:00 PM (UTC)

    • Thu, Feb 19

      9:00 PM—10:00 PM (UTC)

    • Mon, Feb 23

      7:00 PM—8:00 PM (UTC)

Projects

1 hr / week

Optional exercises you can do to dig deeper and master the the content

Recorded Lessons

1-2 hrs / week

Lectures are recorded for your convenience

Course Map

From Mindset through The Loop to Build, Evaluate, and the Pivot decision in one view.

From Mindset through The Loop to Build, Evaluate, and the Pivot decision in one view.

Participation & Code of Conduct

Participation Expectations

  • This is a practitioner-focused cohort built on trust and discussion.

  • Participants are expected to engage respectfully and professionally.

  • Disruptive behavior, bad-faith participation, or misuse of course materials may result in removal.

No Recording / Redistribution Clause (clear and unambiguous)

Content Use Policy

  • Course content, discussions, slides, and materials are for personal educational use only.

  • Recording, transcribing, scraping, or redistributing any portion of the course is not permitted.

  • This includes sharing with employers or third parties.

  • Violation may result in removal from the course.

Frequently asked questions

$980

USD

Feb 16Mar 20
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