The Technical Program Manager's Guide to Practical AI: Workflows and Frameworks for Smarter, Faster, Higher-Impact TPM Execution

Master AI tools and methodologies to transform from a traditional TPM into an AI-enabled leader, unlocking scale, speed, and impact beyond human capacity limits

Key Features

• AI Foundations and human judgement (EQ) you need as a TPM
• Effective Prompting and Agents frameworks
• Practical AI use cases across the Technical Program Lifecycle

Book Description

Technical Program Managers operate in increasingly complex environments where scale, speed, and cross-functional coordination often exceed human capacity. AI is rapidly transforming how this work gets done, and TPMs need practical ways to apply it in their day-to-day workflows.

This book shows you how to use AI across the TPM lifecycle to reduce operational overhead, accelerate decision-making, and increase strategic impact. Each chapter combines hands-on practical AI use cases, frameworks (inputs → AI assist → human verification → output), and practical guidance tailored to TPM workflows, helping you navigate tools, understand trade-offs, and apply AI effectively.

You’ll learn how to apply AI for planning, technical reviews, dependency management, risk analysis, status reporting, stakeholder communication, workflow automation, and career management. The book also covers prompt engineering, AI agents, governance considerations, and how to evaluate AI tools effectively in enterprise environments.

What you will learn

• AI tools, concepts and methodologies
• AI agents, workflows and their creation
• Effective prompt engineering frameworks
• AI tools evaluation, selection and trade offs
• AI strategies throughout the program lifecycle
• AI automations for career management
• Human input (EQ) vs AI driven automation balance

Who this book is for

This book is for Technical Program Managers, Engineering Program Managers, Project Managers, Program Leads, and technology professionals (Engineering Managers, Product Managers and others) who want to apply AI to improve execution, decision-making, and impact across complex environments. A basic understanding of TPM practices, initiation, planning, execution, closure, maintenance, stakeholder communication, and risk management is recommended. No deep AI expertise is required.

Table of Contents

1. How AI is Changing the TPM Role
2. AI Fundamentals and Core Concepts
3. Modalities of AI Interactions
4. Introduction of AI Use Cases for TPMs
5. AI for Initiation and Planning
6. AI for Program Execution
7. AI for Delivery and Closure
8. AI for TPM Leadership
9. AI for Career Management
10. Responsible AI
11. The Importance of EQ in a World of AI
12. Staying Relevant and Leading the Way

Liana Gevorgyan is a TPM leader with over 20 years of experience driving complex machine learning, data science, infrastructure and platform programs at companies including Oura, Block (Square, Cash App), Meta (Instagram), McKinsey. Beginning her career as a software engineer focused on big data and algorithm optimization, she has built and led TPM organizations, driven AI initiatives impacting billions of users, and helped organizations operationalize innovation at scale. She is also a mentor, coach, and exhibiting artist based in New York City.

Joshua began his journey in Project Management as a Technical Lead at Hewlett Packard in 2012 by learning the basics of managing a project and working with stakeholders. In July of 2013, he made the career switch to pursue Technical Program Management at Amazon. During that time, He advanced in his career twice from TPM to Sr. TPM in 2017, and then to Principal TPM in 2022.

James Dayhuff is a technology leader whose career spans software engineering, product management, and technical program management. With a master's degree in Information Systems Management, he has led cross-functional teams, delivered large-scale infrastructure initiatives, improved compliance and security programs, and enabled new business growth opportunities. Known for connecting strategy to execution, James combines deep technical understanding with business-focused thinking to help organizations deliver impactful outcomes while balancing customer needs, technical constraints, and organizational goals.

Malvika Sinha is a TPM leader with 13+ years of experience driving end-to-end programs across healthcare and digital pharmacy at Walmart, payments at Stripe, Middleware at Intel, and gaming at Electronic Arts. She began her career as a systems engineer and automation expert and has remained deeply involved in the software development lifecycle, combining technical depth with strong execution. She is passionate about AI, particularly agentic AI, and is excited about how the field is evolving and transforming how products are built and teams operate.

Aadil is a Technical Program Manager with 16+ years of experience leading complex, zero-to-one hardware and software programs across mobile, IoT, and desktop platforms. He has worked at BlackBerry, Apple, Google, and Nike, led Software Program Management at Humane, and now drives Airbnb's first major push into AI products. Aadil believes great TPMs are systems thinkers who blend technology with psychology, philosophy, and design. He writes The Art of Doing Technical Program Management on Substack, sharing practical insights for product, engineering, and TPM leaders.