The AI-Era Engineering Organisation
When AI contributes code, the questions that matter move from writing to judging: who decides, who reviews, and how people grow. These posts cover organisation design, roles, career paths, hiring and mentoring.
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- The AI-Era Engineering Org in Practice describes an operating model in which AI executes and humans judge, and what each role then does.
- The Future Engineering Org Chart argues that organisation structure, not coding speed, is the constraint.
- Building Career Ladders for AI-Era Engineering Teams covers what a ladder must measure when agents also produce.
- The Expertise Discount looks at why firms are discounting senior engineers, and why that bet may correct.
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Is Anybody Actually Reading This?
: AI makes polished tickets, replies and pull requests cheap, so they no longer prove understanding. A test for which delivery practices still create it. -
Building Career Ladders for AI-Era Engineering Teams
: Career ladders reward production seniority, but AI agents now produce. What a new ladder must measure, and why entry-level roles need redesign, not removal. -
The AI-Era Engineering Org in Practice
: The AI-era engineering team needs an operating model, not a new org chart. This post shows where AI executes, where humans judge, and what each role now does. -
The Permission to Try
: AI has cut the cost of writing code, not maintaining it. This post argues for exploring more before committing, as judging what to keep is the bottleneck. -
AI Is Not an Engineering Strategy
: Boards hear AI will write 90% of code and cut engineering headcount. Why code is not engineering, and what AI amplifies and what it cannot touch. -
The Expertise Discount
: Firms spend billions on AI while discounting senior engineers. This post argues the 'Junior + AI = Senior' bet is bubble behaviour and will correct. -
Task Decomposition for AI Collaboration: The Art of Prompt-Ready Work Boundaries
: Vague AI requests give poor results. How to break user stories into bounded, prompt-ready work units with clear inputs, outputs and standards. -
The Future Engineering Org Chart: How AI Changes Team Structure
: Teams code faster with AI but ship at the same speed. This post argues org structure is the constraint, and sets out new roles, team shapes and a roadmap. -
Leading Without Authority: The Senior Engineer's Paradox
: Seniority is judgement, systems thinking and influence, not years or titles. How senior engineers lead without authority, and why AI cannot replace that. -
Mentoring Developers When AI Writes Half Their Code
: AI-assisted juniors look productive but get promoted beyond their ability. Why career timelines still matter, and how to mentor when AI writes half the code. -
The Hidden Cost of Cheap AI: Why Your Organisation's Strategy is Creating a Skills Crisis
: A junior engineer plus AI looks cheaper than a senior, but hidden costs and skills gaps reverse that. This post argues for AI spend that builds capability. -
Brushes and Algorithms: What the Miniature Painting Community Teaches Us About AI in Creative Work
: What the miniature painting community's row over AI at Golden Demon teaches engineering leaders about skill growth, authenticity and drawing lines on AI. -
The Great Wait: How AI Expectations Are Freezing the Software Engineering Job Market
: Firms are freezing engineering hiring while waiting for AI to replace engineers. This post argues that is a strategic error, and what to do instead. -
Documentation as Decision History: Creating Better Paper Trails for Teams and AI
: Treat decisions like code changes and write them as pull requests. It stops repeated debates, keeps context and gives AI assistants the history they lack. -
Too Many Ideas, Not Enough Systems: Building Your External Brain
: How engineering leaders can capture, triage and act on a constant stream of ideas, using RICE, the Eisenhower Matrix and AI tools, without losing the best. -
Better Communications for Software Engineering: The Foundation of Process and AI Success
: AI amplifies the communication habits a team already has. Why clear written communication comes first, with frameworks for requirements, feedback and AI use. -
Hiring Engineers in 2025: Testing AI Collaboration, Not AI Avoidance
: Coding interviews that ban AI test the wrong skills. Assess how candidates work with AI, critique its output and judge when not to use it.