Build a PM Skill that Learns from you (Learning Loops)

Hosted by Mahesh Yadav

Fri, Apr 24, 2026

4:00 PM UTC (45 minutes)

Virtual (Zoom)

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Agentic AI Product Management Certification
Mahesh Yadav
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What you'll learn

If agent loops can handle context, what must PMs design

Understand learning loops that are still an open area of research and are critical for building scalable AI agents.

Hands-on: Build agents using Claude Code

See how even the latest models (Opus 4.7) struggle with tasks that require continuous, human-level improvement

Explore the risks of deploying agents without learning loops

Learn the system design patterns that address poor UX

Learn how to design feedback-driven learning loops

Apply learning loop system design via a hands-on case study you can use in real products and interviews.

Why this topic matters

For 70+ years, programming meant humans writing code & machines executing it. Autoresearch, Ralph, & Hermes invert this: humans write natural-language instructions (program.md, prd.json, SKILL.md), & the agent writes, modifies, and iterates on code. This isn't vibe coding — it's a new job description. The PM becomes a "programmer of programs.md" — authoring research org instructions, not Python.

You'll learn from

Mahesh Yadav

Ex AI Product Lead -Google l Meta l Microsoft l AWS | 10k+ Alums l Founder - Agentic AI Institute

Mahesh Yadav brings 20+ years of experience building AI products at Google, Meta, AWS, Microsoft. He holds 12 patents in AI training, power management and computer vision. He has launched major agentic-AI initiatives (for example launching an agent for AWS Bedrock, featured in CEO keynote) and trained thousands of professionals to succeed in AI roles. With this programme you get rare access to CEO-level of mentorship.
Substack AI PM Newsletter l Linkedin Community of AI PMs l YouTube For Free Sessions Recordings
Currently, he is building back-office AI agents for the enterprise, starting with in-house legal teams through LegalGraph.AI. His work bridges education and real-world AI deployment, helping organizations adopt agentic systems that automate complex knowledge work.

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Previously at

Google
Microsoft
Amazon Web Services
Meta

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