Rajiv Shah – AI Problem Framing for Agentic AI

Sale Page: https://maven.com/rajistics/ai-problem-framing

Most AI teams think their biggest challenge is:

• Model performance
• Prompt engineering
• Tool selection
• But in reality…
• The biggest failure happens before any code is written
• They’re solving the wrong problem.

AI Problem Framing for Agentic AI by Rajiv Shah is built around a critical idea:

AI success is determined by how well you define the problem — not how well you build the solution The Core Idea: Most AI Failures Are Framing Failures

Many AI projects:

• Work in demos
• Hit evaluation metrics
• Still fail in production

Why?

Because they solve something that doesn’t actually matter

According to the course, teams often spend months building systems… only to realize they tackled the wrong problem from the start The Shift: From “How Do We Build This?” → “Should We Build This?”

Traditional AI thinking:

Choose model → build system → optimize

Inside this course, the order flips:

Define problem → test assumptions → choose approach → then build

This shift alone can save:

• Months of development
• Significant cost
• Entire failed projects
• The “5-Step Loop” Framework

At the center of the training is a structured thinking model:

The Loop:

Outcome – What are we actually trying to achieve?

Assumptions – What must be true for this to work?

Alternatives – Is AI even the best solution?

Trade-offs – What are we sacrificing?

Signals – How do we know it’s working?

This loop becomes:

• A repeatable decision-making system for every AI project
• Why This Matters More in the Agentic AI Era

With AI agents:

• Systems are more complex
• Costs are higher
• Failures are harder to detect

Which makes:

Problem framing exponentially more important

The wrong framing doesn’t just create bugs – it creates entire systems that shouldn’t exist.

Where This Course Has the Most Impact

AI Problem Framing for Agentic AI is especially relevant for:

• AI engineers
• Product managers
• Startup founders
• Teams building AI agents

It’s less about coding… and more about:

Thinking correctly before building anything