Vibe Coding: governance, architecture, and the discipline that compounds
92% of US developers use AI coding tools daily. Only 29% trust the output. The 63-point gap between those two numbers is the most consequential unsolved problem in enterprise software engineering today. The five assessments and the posts on this page are the discipline most teams are skipping. Score where you stand, then read the angles that fit your situation.
Five assessments. Five different angles on the same problem.
How Mature Is Your Governance Over AI-Generated Code?
Score the disciplines that prevent vibe coding from sinking your codebase — policy, review, attribution, security, accountability, and training.
Take the scorecard →Are Your Devs Tethered to Strategic Architecture While Vibe Coding?
A scored profile of whether your AI-accelerated development respects the architecture you designed — or quietly diverges from it.
Take the scorecard →Is Your Codebase Ready for AI Coding Agents?
A scored profile of how productively AI code agents can work in your codebase — and the cleanup that unlocks 10x output.
Take the scorecard →Does Your AI-Generated Code Meet Production Standards?
A scored quality profile for the code AI is shipping into your repo — correctness, security, readability, testability, maintainability, and the tooling that gates it.
Take the scorecard →What's the Production Risk Hiding in Your AI-Generated Code?
An audit of the operational risk your AI coding tools have shipped into the codebase — credential exposure, hallucinated dependencies, auth drift, test mirages, architecture drift, and audit visibility.
Take the scorecard →Six posts on the angles the assessments raise
If a scorecard surfaced something you want to think through, these are the longer-form takes that go with each one.
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Vibe Coding Governance: The Discipline Most Teams Are Skipping
92% of US developers use AI coding tools daily. Only 29% trust the output. The gap between those numbers is governance, and most engineering orgs have not closed it.
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Developer AI Fluency vs Developer AI Tool Usage. Why They Are Not the Same
92% of US developers use AI tools daily. Only 29% trust the output. The gap is fluency, not adoption: the discipline separating who ships from who pastes.
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Before Your Team Vibe Codes, Define the Code Footprint
AI coding tools generate code faster than teams can review it. Quality is set before the first prompt, by your starter template, context file, and defined target.
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Enterprise Vibe Coding Isn't Typing Less — It's Thinking in Loops
What enterprise engineering teams get wrong about vibe coding: the skill shift isn't from writing code to prompting. It's from writing lines to designing loops.
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What to Look for in a Fractional CTO in the Vibe Coding Era
Vibe coding has changed what software teams do. The fractional CTO qualifications that mattered in 2022 are incomplete in 2026. Here is what to evaluate now.
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Vibe Coding Code Footprints: Why Your Template Is Your First Architecture Decision
AI-generated code accumulates fast. Without the right constraints in place from day one, the codebase becomes unmanageable before the product ships.
The shortest path: score, then read what your score surfaced.
Most teams underinvest in the governance and overspend on the tooling. The assessments will tell you which side of that you are on, and the posts give you the moves that matter for your specific gap.