Building Software in the AI Era
Master the tools, habits, and operating models needed to ship high-quality software in a day-to-day workflow shaped by LLMs, moving past outdated sprints and velocity metrics.
Series Curriculum
Why Sprints Are Broken
Technical debt is inevitable. What matters is whether you manage it deliberately. A practical framework for prioritisation and stakeholder communication
Shape Up: A Practical Introduction
A practical introduction to Shape Up - the planning methodology built on appetite over estimation, fixed time with flexible scope, and small autonomous teams.
Writing Pitches That Work
How to write Shape Up pitches that give engineering teams real clarity - problem definition, appetite, solution shaping, rabbit holes, and no-gos explained.
Spec Driven Development With LLMs
How to write specifications that produce useful LLM output, covering interface definitions, edge cases, and why the spec is your highest-leverage artifact.
Reviewing AI Generated Work
How to review AI-generated code effectively, what failure modes to watch for, and how to maintain quality standards as code volume increases.
Redefining Engineering Roles in the AI Era
AI makes implementation cheaper and judgment more valuable. Learn how engineering roles, hiring, and team design are changing.
Managing Expectations in the AI Era
How to have honest conversations with stakeholders about AI productivity — what actually changes, what doesn't, and how to set realistic expectations.
Running A Better Table
How to run a Shape Up betting table — the planning meeting where pitches get selected and cycles begin or quietly collapse.