Engineering Management and Leadership in the Age of AI

What you'll learn
Understand the role and scope of engineering management vs. tech lead or IC roles.
Build core skills in people management, leadership, and technical decision-making.
Transition smoothly from individual contributor to manager while avoiding pitfalls.
Apply practical frameworks for delegation, performance, and stakeholder alignment.
Leverage AI tools for notes, agendas, and team insights in daily workflows.
Evaluate how AI complements but doesn't replace engineering management skills.
Requirements
No prior management experience required - this course is beginner-friendly.
Some professional experience as a software engineer, developer, or technical role is helpful.
Basic familiarity with software projects and engineering workflows recommended.
Curiosity to learn leadership, communication, and people skills.
(Optional) Interest in using AI tools for productivity and team support.
Description
Transitioning from engineer to manager is one of the biggest career shifts in tech. Writing code and leading people require completely different skillsets-and in today's AI-driven world, engineering leaders face new challenges and opportunities.This course is designed to help you bridge the gap. You'll learn how to move beyond being an individual contributor and develop the leadership, communication, and management skills needed to guide high-performing engineering teams. We'll cover the fundamentals of engineering management, common pitfalls for new managers, and strategies for building trust, setting direction, and scaling organizations.You'll also explore how AI is transforming engineering leadership-from smarter decision-making to improving productivity and supporting your teams. By the end, you'll have the tools to step confidently into management or strengthen your existing leadership role, while staying ahead in the age of AI.By taking this course, you will:Understand the differences between technical and managerial rolesBuild essential leadership and people management skillsAvoid common mistakes that derail first-time managersLearn how to integrate AI tools into your leadership toolkitDevelop strategies for scaling teams and organizations effectivelyThis course is ideal for software engineers, team leads, and aspiring or current managers who want to grow as leaders and succeed in a rapidly evolving tech landscape.Engineering Manager Toolkit - Templates, Prompts & SamplesAs part of this course, we provide a ready-to-use Engineering Manager Toolkit with over 40 templates, prompts, and sample documents that you can download and start using immediately. These practical resources cover everything from people management and hiring to project tracking, communication, and AI-assisted decision-making-helping you apply what you learn directly in your day-to-day work.Available Templates, Prompts, and Samples:Hiring the Right TalentJob Description TemplateInterview Scorecard TemplateAI Interview Question Generator Prompt - generate role-specific questions automaticallyCandidate Red Flags Checklist - quick reference of warning signs in interviewsOnboarding New Engineers30/60/90-Day Onboarding Plan TemplateFostering Team CultureTeam Culture & Feedback Survey TemplateAI Sentiment Analysis Prompt - summarize feedback from surveys or Slack/Teams messagesCommunicating with Engineers1:1 Meeting Agenda & Notes TemplateAsync Update TemplateAI 1:1 Prep Prompt - generate talking points for 1:1s based on prior notesTeam Update Email Draft Prompt - AI helps write concise weekly updatesManaging Upwards & OutwardsStakeholder Update / Status Report TemplateMeeting Summary Template (AI-Assisted)Conflict Resolution & FeedbackFeedback / Conflict Resolution TemplateAI Roleplay Prompt - simulate difficult conversations before the real meetingPlanning & EstimationMilestone Breakdown / Project Plan TemplateTask Estimation WorksheetAI Backlog Prioritization Prompt - generate recommended priorities based on impact/effortRisk Identification Checklist Prompt - quick prompt to surface possible blockersScrum Guide 2020 Ken Schwaber Jeff Sutherland CC BY SA 4.0.pdfExecution & TrackingSprint / Project Tracking DashboardRisk & Blocker Log TemplateAI Progress Summary Prompt - summarize team progress from Jira/Linear/GitHub ticketsPostmortems & Continuous ImprovementBlameless Postmortem TemplateAI Retrospective Insight Prompt1:1s & CoachingCoaching Plan TrackerAI Coaching Suggestion Prompt - suggest growth topics for a direct reportSkill Gap Analysis Prompt - AI helps summarize missing skills per engineerPerformance ManagementPerformance Review TemplateAI Draft Performance Review Prompt - generate draft review language for managersCareer Growth & RetentionCareer Growth / Development Plan TemplateAI Career Path Suggestion Prompt - suggest next steps for promotion or learningDefining Engineering ExcellenceCode Quality & Review ChecklistProcess DesignProcess Audit / CI-CD ChecklistAI Process Improvement Prompt - suggest ways to streamline workflow or reduce bottlenecksMeasuring Developer ProductivityDeveloper Productivity Metrics DashboardAI Metrics Interpretation Prompt - analyze DORA/SPACE metrics trendsAI for CommunicationEmail Draft Prompt - generate professional emails for stakeholders or teamMeeting Agenda Generator Prompt - AI auto-suggest agenda itemsAI for Decision SupportDecision Matrix / Prioritization TemplateScenario Comparison TemplateScenario Comparison Prompt - summarize pros/cons for multiple optionsRisk Analysis TemplateRisk Analysis Prompt - generate a risk table for upcoming projectsAI for Knowledge ManagementDocumentation TemplateDocumentation Summary Prompt - convert tribal knowledge into structured docsManaging in CrisisScenario Planning / Crisis Response TemplateShaping Engineering StrategyStrategic Alignment Template
Who this course is for
Software engineers and developers preparing for their first management role.
Tech leads who want to strengthen leadership and people management skills.
Current engineering managers seeking to sharpen their technical, organizational, and communication abilities.
Professionals interested in blending technology, management, and leadership for career growth.
Learners curious about how AI can enhance decision-making and productivity in engineering management.
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