Category: AI-Driven Development

  • The AI Tool Dependency You Didn’t Choose

    The AI Tool Dependency You Didn’t Choose

    The CTO of a Series B healthtech company approved full adoption of an AI coding agent for her twelve engineers in the middle of a compliance-critical sprint, because the acceleration was real. Within six weeks the team had moved its whole development workflow inside the tool: custom skills encoding how they elaborated and built features,…

  • AI Comprehension Debt: The Codebase Nobody Understands

    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…

  • The 5x Myth: What AI Actually Changes About Delivery Speed

    The 5x Myth: What AI Actually Changes About Delivery Speed

    A fintech CTO I work with had her board moment three months ago. The chair leaned forward mid-review and asked the question every technology executive dreads: “So you’re telling me you don’t know if this is working?” Her answer was better than most: “I’m telling you that the numbers we were using to answer that…

  • The vanishing rung: what happens when entry-level engineering disappears

    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…

  • The AI Productivity Paradox Has Data Now

    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…

  • Who Owns AI Governance When Everyone Thinks Someone Else Does?

    Who Owns AI Governance When Everyone Thinks Someone Else Does?

    A few months ago, during a governance assessment at a mid-size financial services company, I asked a simple question: “Who owns AI governance here?” The CISO said the CTO owned it because AI is a technology decision. The CTO said the data team owned it because AI is fundamentally a data problem. The head of…

  • Mob Construction: What Changes When AI Generates Code from a Real Specification

    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…

  • Mob Elaboration: What Happens When AI Runs the Requirements Room

    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…

  • The Community Is Building AI-DLC Without Knowing It

    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…

  • Security as a Development Constraint, Not a Review Gate

    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…