Learn how to build AI products responsibly

A 6-week program for product builders

Overview

This Responsible AI Program is designed to equip product managers, builders and entrepreneurs with the practical skills to navigate AI safety, governance and ethics.

This program offers a practical, case-study-driven approach to help PMs integrate responsible AI principles into their products effectively.

Why join?

This allows for product managers to navigate the risks and obstacles of rolling out AI technologies into their complex workflows:

Build products that align with your mission and attract loyal users.
Differentiate in your market by standing for integrity and trust.
Drive user acquisition and retention by fostering credibility.
Ensure compliance and avoid reputational risks with proactive strategies.

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Program Structure

Time Commitment: ~3 hours per week
- 1h40m weekly class
- 2 hours of homework & applied exercises
Schedule: Regular cohort-based model
Hands-on learning: Practical, real-world case studies
Goal: Up skill PMs to lead AI product development responsibly
Next cohort: Starting May 2025
Limited spots!

Join Waitlist

Be the first to receive an invite at discounted price when the course launches

Curriculum

Week 1: Setting the Stage for Responsible AI

Why responsible AI is a critical skill for PMs & founders
Key teams involved and their roles in AI governance
The evolving landscape and need for more holistic product development

Week 2: Risks & Mitigation

AI compliance and regulatory considerations
Reputational risks and ethical concerns
Risk assessment frameworks

Week 3: AI Governance in Practice

Essential governance methods for AI products
Team structures and key stakeholder touchpoints
Aligning AI ethics with product roadmaps
AI certification and compliance standards

Week 4: Driving Responsible AI Adoption

Organizational buy-in and cross-functional alignment
Strategies to influence AI product development
Building accountability frameworks

Week 5: Responsible AI Gets Technical

Addressing data bias and fairness
Explainability & transparency in AI decision-making
Ensuring AI robustness and reliability
Week 6: Experimental Release & Risk-Taking
Best practices for rolling out AI-driven features
Balancing innovation speed with responsible AI principles
Continuous monitoring and iteration

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Regenerative Products.

Changing the game on how we build software.

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