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What AI Team Compression Means for Engineering Organisations and the People Who Lead Them
AI is restructuring engineering teams, not replacing them. Explore the evidence, case studies, and frameworks for navigating team compression at your organisation.
Building an Engineering Headcount Model That Accounts for AI Leverage
A practical framework for CTOs building headcount models with AI leverage factors — from deriving a defensible multiplier to presenting the case to the board.
How Shopify Klarna and Tailwind Are Reshaping Engineering Teams With AI — Three Strategic Patterns
Shopify, Klarna, and Tailwind reveal three distinct strategies for AI-driven team compression. Compare the proactive, aggressive, and crisis-driven patterns.
The One-Person Unicorn Versus Reality — What Actually Happened When a Journalist Hired Only AI Agents
Sam Altman says one person with AI can build a billion-dollar company. A journalist tested the claim. Here is what AI agents can and cannot actually do.
Governing AI-Generated Code in a Compressed Engineering Team
AI-generated code ships faster but compounds risk. Here’s a governance framework for compressed engineering teams balancing speed with safety.
The Pipeline Problem — Why Pausing Junior Hiring Now Creates a Senior Engineer Shortage Later
Pausing junior developer hiring saves money now but risks a senior engineer shortage in 3-5 years. Here’s the pipeline data and three ways to avoid it.
From Writing Code to Orchestrating Agents — How the Senior Engineer Role Is Changing
Senior engineers are shifting from writing code to orchestrating AI agents. What tacit knowledge, one-pizza teams, and the mid-level quiet crisis mean.
What the Data Actually Shows About AI and Junior Developer Employment Decline
Stanford’s ADP study reveals a 16-20% employment decline for junior developers in AI-exposed roles. Here is what the data shows and what it does not show.