Category: Software Development
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AI Comprehension Debt: The Codebase Nobody Understands
Six months ago, a fintech team I work with shipped an authentication service in three days. Claude generated most of it, the senior engineer who prompted it reviewed and approved, and the service passed all tests. It worked. Last month, a different team member needed to modify the token refresh logic. She spent four days…
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The vanishing rung: what happens when entry-level engineering disappears
She joined the team seven months ago, right out of university. Smart, motivated, technically capable. Her PRs merged on the first or second try. Her velocity numbers were solid. Her manager called her “a natural.” Last month, there was a production incident. A payment processing service started timing out under load. The team needed someone…
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The AI Productivity Paradox Has Data Now
Months ago, I wrote about the measurement problem: engineering metrics rewarding the wrong behavior after AI adoption. That post was a diagnosis based on pattern recognition across organizations, velocity climbing while delivery stayed flat, dashboards turning green while products shipped late. The data arrived. Between late 2025 and mid-2026, five independent research programs published findings…
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The four layers of AI-driven engineering organizations
After a year of writing about what breaks when AI enters engineering organizations, I can name the single thread that connects every failure and every success: whether the organization preserved judgment while changing how work gets done. Threat modeling, governance, spec-driven development, architecture reviews, measurement problems, the CTO’s evolving role. Each post addressed a specific…
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Mob Construction: What Changes When AI Generates Code from a Real Specification
Two weeks after the Mob Elaboration session I described in my previous post, the same financial services team sat down for their first Mob Construction session. They had a validated specification: twelve user stories with acceptance criteria, a domain model with verification tiers, non-functional requirements with measurable thresholds, and a risk register that included the regulatory…
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Mob Elaboration: What Happens When AI Runs the Requirements Room
The first time I facilitated a Mob Elaboration session, the Product Owner read the Intent aloud: a new customer onboarding flow for a financial services platform. Within four minutes, the AI had generated twelve user stories, acceptance criteria for each, a proposed domain model, and a decomposition into three independent units of work. A senior…
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The Community Is Building AI-DLC Without Knowing It
A few weeks ago, a developer on Reddit posted about a workflow they had built for Claude Code (r/ClaudeAI, March 2026). They had split their AI-assisted development into three distinct agents: an Architect that defined the system design and constraints, a Builder that generated the code, and a Reviewer that evaluated the output against the…
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Security as a Development Constraint, Not a Review Gate
A compromised npm maintainer account pushed malicious versions of Axios, one of the most widely used JavaScript libraries, to the registry. The attack, which hit last month, bypassed GitHub Actions entirely. The attacker published directly via the npm CLI with stolen credentials. A hidden dependency deployed a remote access trojan. For three hours, every npm install that…
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The Measurement Problem: When Your Metrics Reward the Wrong Behavior
Last year, I sat in a quarterly business review where an engineering director presented what he called “the best quarter in the team’s history.” Velocity was up 42%. Pull requests per developer had nearly doubled. Sprint burndowns were textbook smooth. The slides were polished, the trend lines all pointed up, and the room was nodding…
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The Conversation This Book Is Really About
Over the past year, I’ve had the same conversation with at least thirty CTOs and VPs of Engineering. The setting changes: a conference hallway, a video call, a dinner after a workshop. The words change. But the conversation is always the same. It starts with a number. “Our developers are 40% more productive.” Or 30%.…
