Engineering Management and Leadership in the Age of AI

This lecture introduces the fundamentals of engineering management, exploring what the role entails, its scope, and how it differs from technical leadership. You’ll learn why management requires a distinct skillset, common pitfalls for first-time managers, and how the rise of AI is reshaping managerial responsibilities. By the end, you’ll have a clear understanding of what it takes to lead technical teams effectively.

This lecture guides engineers through the critical transition from individual contributor to manager. You’ll learn how to shift your mindset from doing tasks to enabling outcomes, navigate the challenges of leading former peers, balance technical expertise with leadership, and build credibility through trust and effective communication. Packed with practical tips and real-world examples, this session equips you to lead your team confidently and successfully in today’s fast-paced, AI-driven engineering environment.

Learn how engineering managers balance technical, management, and leadership skills, why the right mix shifts with seniority, and how to assess and grow your capabilities. This session offers practical frameworks, real-world examples, and strategies to design your growth intentionally in the AI era.

This lecture explores the essential responsibilities of an engineering manager, covering people management, project delivery, process ownership, and aligning engineering work with business goals. Learners will understand how EMs act as a bridge between leadership and their teams, communicate effectively with stakeholders, and leverage tools—including AI—to amplify team impact. Practical examples and strategies help aspiring and current EMs succeed in driving both team growth and business outcomes.

This lecture explores how engineering managers can leverage AI to enhance their effectiveness without replacing human judgment. Learners will discover practical applications such as summarizing notes, preparing agendas, analyzing metrics, and improving daily workflows. Emphasis is placed on using AI responsibly to augment decision-making, boost team productivity, and focus on strategic leadership, while maintaining human oversight, empathy, and accountability.

This lecture guides engineering managers through the essentials of hiring in the AI era. Learn how to define clear roles, identify must-have skills, write effective job descriptions, conduct structured interviews, and leverage AI tools for resume screening and interview preparation — all while maintaining fairness, reducing bias, and making data-informed hiring decisions.

This lecture explores effective strategies for onboarding new engineers, including structured 30/60/90-day plans, documentation and buddy systems, and AI-assisted tools for checklists and personalized learning paths. Participants will learn how to accelerate time-to-productivity, enhance engagement, and set measurable outcomes for retention and growth.

This lecture explores how engineering managers can intentionally build and sustain a healthy team culture. It covers psychological safety, inclusivity, and trust, how to recognize early signs of dysfunction, and practical ways to leverage AI-driven feedback to gain insights without replacing human empathy. Participants will gain actionable strategies to foster collaboration, innovation, and engagement in modern, AI-augmented teams.

This lecture equips engineering managers with practical strategies for effective team communication. You’ll learn how to run impactful 1:1s and team meetings, optimize asynchronous updates, and leverage AI for meeting summaries and knowledge management—all while building trust, alignment, and efficiency within your team.

This lecture covers how engineering managers can build trust with leadership, align effectively with product and design partners, and communicate with impact through concise status reports and presentations. It also explores how AI can accelerate reporting and visualization, enabling managers to spend less time on formatting and more time driving outcomes.

This lecture equips engineering managers with practical strategies for giving and receiving feedback, navigating conflicts within and across teams, and turning challenging conversations into opportunities for growth. Participants will learn how to deliver clear, behavior-focused feedback, manage conflicts constructively to build trust and collaboration, and leverage AI-assisted roleplay to safely practice tough conversations.

This lecture introduces engineering managers to the fundamentals of planning and estimation in modern software projects. You’ll learn how to break projects into milestones and tasks, choose the right planning approach—Agile, Waterfall, or Hybrid—apply effective estimation techniques, and leverage AI to make smarter, data-informed decisions. The lecture also highlights common pitfalls and best practices to ensure clarity, predictability, and value-driven delivery.

This lecture explores how engineering managers can effectively track project execution to ensure teams stay aligned, predictable, and high-performing. It covers key metrics like velocity, lead time, and cycle time, introduces popular tracking tools such as Jira, Linear, and GitHub, and highlights how AI can surface risks and unblock delivery. Learners will also see how visual dashboards and continuous feedback loops drive proactive decision-making and sustainable improvement.

This lecture explores how engineering managers can turn incidents into opportunities for learning and improvement. You’ll learn how to run blameless postmortems, identify systemic issues, convert findings into actionable improvements, and leverage AI tools to analyze patterns and suggest preventive measures. The session emphasizes building a culture of transparency, psychological safety, and continuous improvement, helping teams become more resilient and proactive in managing failures.

This lecture explores how engineering managers can use 1:1 meetings and coaching to build trust, support growth, and align their teams. You’ll learn how to structure effective 1:1s, shift from directing to coaching, leverage AI for smarter conversations and progress tracking, and avoid common pitfalls—all aimed at creating high-performing, engaged teams.

Learn how to build a fair, effective, and growth-focused performance management system for your team. We’ll cover setting clear expectations, running regular reviews, and using AI to synthesize peer feedback, detect performance trends, and draft review summaries. You’ll walk away with practical strategies to balance human judgment with AI insights and turn performance reviews into opportunities for continuous development rather than just evaluation.

This lecture explores how engineering managers can foster career growth, engagement, and retention within their teams. It covers building clear career ladders, supporting promotions and skill development, conducting meaningful career conversations, leveraging AI for personalized learning, recognizing achievements, and measuring progress to drive performance and reduce attrition.

This lecture explores the core pillars of engineering excellence — quality, testing, documentation, observability, and culture — and shows how managers can influence and sustain these practices. It also highlights how AI can amplify good practices while emphasizing continuous improvement as a habit, not a one-time project.

This lecture explores how engineering managers can design and optimize team processes to balance structure and agility. You’ll learn when to add or remove processes, how agile ceremonies, CI/CD, and code review culture drive efficiency and quality, and how AI can enhance workflows without replacing human judgment. Practical insights and examples will help you create processes that empower your team, reduce friction, and accelerate delivery.

This lecture explores practical ways to measure developer productivity beyond simple metrics. It introduces DORA and SPACE frameworks for team-level and holistic insights, highlights vanity metrics to avoid, and shows how AI dashboards can provide meaningful, actionable data. Emphasis is placed on continuous improvement, team wellbeing, and using metrics to guide coaching, not rank individuals.

This lecture explores how AI can help engineering managers communicate more effectively and efficiently. Learn how to draft emails, write status updates, summarize meetings, and generate focused agendas — all while saving time, maintaining clarity, and amplifying your human judgment. Practical tips, examples, and prompts show how AI can become a trusted assistant in your day-to-day communication.

This lecture explores how AI can support engineering managers in making better, faster, and more informed decisions. We cover AI-powered data analysis, risk identification, prioritization, and scenario simulations, highlighting practical strategies to combine AI insights with human judgment for optimal outcomes.

This lecture explores how AI can transform knowledge management in engineering teams. You’ll learn how AI automates documentation, discovers hidden insights, and enables semantic search to capture tribal knowledge, making information more accessible, reducing reliance on individuals, and boosting team efficiency.

This lecture introduces engineering managers to Generative AI, explaining what it is, how Large Language Models power copilots and assistants, and where AI adds the most value — as well as its limitations. Attendees will learn how to leverage AI to accelerate productivity, support decision-making, and amplify their team’s impact while maintaining human oversight.

This lecture explores how engineering managers can leverage Generative AI in everyday workflows. It covers practical applications such as drafting performance reviews, writing project proposals, and brainstorming solutions, highlighting how AI can save time, enhance decision-making, and spark innovation. The session emphasizes human oversight, best practices, and integrating AI as a co-pilot, helping managers maximize productivity while maintaining quality and context.

This lecture explores the key risks and ethical considerations of using AI in engineering management. Topics include bias, hallucinations, over-reliance, and confidentiality issues, along with practical strategies for keeping humans in the loop and mitigating potential harms. Managers will learn how to adopt AI responsibly while maximizing its benefits for teams and products.

This lecture explores how engineering leaders can successfully scale teams from 10 to 100 engineers. It covers the evolution of leadership layers, the importance of delegation, strategies for effective communication, maintaining culture, and leveraging AI to augment team productivity. Practical insights help managers navigate growth without losing agility, alignment, or team cohesion.

This lecture equips engineering managers with practical strategies to navigate high-pressure situations, including layoffs, production incidents, and sudden pivots. It covers immediate response principles, leading teams with empathy, and leveraging AI for scenario planning and communication. Attendees will learn how to act decisively, maintain trust, and turn crises into opportunities for learning and long-term resilience.

This lecture guides engineering managers on how to craft and execute strategy that aligns with company vision. It covers balancing innovation with stability, prioritizing initiatives for maximum impact, and leveraging AI as a tool for scenario planning and decision-making. Practical frameworks and cultural practices are highlighted to help teams work strategically and effectively in a rapidly evolving tech environment.