Ship Your AI Project: 3 Questions

Hosted by Rajiv Shah

55 students

In this video

What you'll learn

Lock down the right problem and metric

Most teams jump to a solution before locking down what decision the system is supporting and how they will measure it.

Choose the right approach for your problem

Agents aren't always the answer. Know what you are building and why so you can adapt when things change.

Define success before you start building

If you can't define success before building, you're doing research, not product.

Bonus: The AI Framing Worksheet

A one-page tool you can run on any AI project starting today.

Why this topic matters

After personally working through hundreds of AI use cases, I've distilled a consistent pattern for successful projects. The projects that shipped, that created real value, that made it to production, they all took time early to frame things properly. With agents now in every team's toolkit, the cost of skipping this step has never been higher.

You'll learn from

Rajiv Shah

AI Engineer, 10+ years, 100k followers

Rajiv Shah is an AI Agentic Engineer at OpenHands.

He's worked hands-on with 100+ AI use cases with over 10 years in AI/ML across enterprise, startup, and research - from ML systems, to RAG pipelines, to coding Agents. The failures taught him more than the successes. They almost always came down to framing, not algorithms.

His career spans 20+ patents, been cited over 1000 times, a PhD from UIUC, and an expert in practical AI.

Today he reaches 100K+ practitioners through talks, videos, and content at AI conferences - known by @rajistics.

Follow Rajiv on Linkedin or Reddit

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