How Large Language Models Learned to Think, Reason, and Act

Hosted by Mahesh Yadav

Fri, Aug 22, 2025

4:00 PM UTC (45 minutes)

Virtual (Zoom)

Free to join

Invite your network

Go deeper with a course

Agentic AI Product Management Certification
Mahesh Yadav
View syllabus

What you'll learn

The Evolution of LLM Architectures

From transformers to chain-of-thought reasoning

The Reasoning Breakthroughs

Why reasoning is emerging naturally in scaled models

The Rise of Action-Oriented Models

Connecting LLMs to tools, APIs, and environments

Implications for Product Managers

How reasoning-enabled AI will reshape product design

Why this topic matters

Just a few years ago, large language models (LLMs) could only predict the next word in a sentence. Today, they can reason, plan, and act — even orchestrating multi-agent workflows. For product managers, understanding how and why this leap happened is the key to building future-proof AI products. This isn’t just about prompts and APIs — it’s about the cognitive evolution of machines.

You'll learn from

Mahesh Yadav

Ex-GenAI Product Lead at MAANG Firms l AI PM Coach l 10k+ Alumni

Mahesh has 20 years of experience in building products at Google, Meta, Microsoft, and AWS AI teams. Mahesh has worked in all layers of the AI stack, from AI chips to LL,M and has a deep understanding of how using AI agents companies ship value to customers. His work on AI has been featured at the Nvidia GTC conference, Microsoft Build, and Meta blogs. :

His mentorship has helped various students build real-time products & careers in the Agentic AI PM space.

Whether you're a hobbyist or a professional looking to get a grasp on GenAI Product Management, feel free to join our channels for more such sessions


Sign up to join this lesson

By continuing, you agree to Maven's Terms and Privacy Policy.

© 2025 Maven Learning, Inc.