Course Overview

AI in Practice · Professional

An Intro to Coding Agents

What Cursor, GitHub Copilot, and Claude Code do, and what that means for the people who manage engineers

The current generation of coding agents differs structurally from the autocomplete-era tools that preceded them. This course explains what makes the difference, what the productivity evidence says, and what technical leaders need to know to manage teams that use them.

When you complete this course, you'll be able to:

  • Explain the structural difference between autocomplete-era coding tools and current agentic coding tools, and why that shift changes the risk and governance profile
  • Evaluate productivity claims for coding agents against the available evidence, including what the studies measure and what they miss
  • Describe the new error patterns that emerge with coding agent use and what reviewing AI-assisted code requires

Duration

~2.5 hours

Modules

3 modules

Level

professional

Format

Self-paced online

Audience

Technical leaders, engineering managers & anyone overseeing software teams

Access period

12 months

$199

Full course · One-time payment · 12 months access

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  • All 3 modules · access on any device
  • Progress tracking
  • 12 months access from purchase

What you'll learn

  • Explain the structural difference between autocomplete-era coding tools and current agentic coding tools, and why that shift changes the risk and governance profile
  • Evaluate productivity claims for coding agents against the available evidence, including what the studies measure and what they miss
  • Describe the new error patterns that emerge with coding agent use and what reviewing AI-assisted code requires
  • Define the key policy, security, and IP decisions an engineering organisation must make before formally adopting coding agents

Modules in the Course

1

What Coding Agents Are Doing

The structural difference between autocomplete-era tools and the current generation of coding agents: what they can do, how they do it, and what the model sees when it's working on your codebase.

Available 3 lessons ~50 mins
2

The Impact on Engineering Teams

The evidence on productivity gains, the new error patterns coding agents introduce, and the less-discussed effects on code review, institutional knowledge, and technical debt.

Available 3 lessons ~50 mins
3

Managing a Team That Uses Them

The decisions technical leaders need to make before their teams adopt coding agents: security posture, IP and licensing exposure, acceptable use policy, and how to frame the conversation with non-technical stakeholders.

Available 3 lessons ~50 mins