Enterprise AI Adoption, Use, Evaluation, and Governance in Practice
Read by Goal
Choose a reading path for one of four goals: adopting and embedding enterprise AI, implementing AI agents in business workflows, designing quality, safety, and governance, or improving development with Claude Code and Codex.
Implement AI Agents in Business Workflows
Design AI Quality, Safety, and Governance
Improve Development with Claude Code and Codex
Read the Latest Articles
Explore the latest articles to catch up on AI trends.
Designing Self-Healing Loops for Coding Agents
A practical guide to coding-agent self-healing loops based on 2026 research and official implementations from OpenAI, Google, and GitHub, covering layered verification, stop conditions, permission boundaries, and human approval.
What Is Generative UI? Architecture, Use Cases, and Constraints
An overview of Generative UI, where the AI generates the interface itself rather than text, covering how it works, use cases in the Vercel AI SDK and Claude, its potential, and points to check before adoption.
Claude Code vs Codex: How to Choose by Workflow Stage
How I choose between Claude Code and Codex in the same repository by comparing discussion, design, implementation, verification, and handoff work.
How AI Development Rules Protect Color Accessibility
How I am building a harness to reduce repeated color accessibility issues in UI components created through Vibe Coding, especially across light/dark themes, hover, selected, and focus states.
Codex Memories: What to Store and When to Reset
A practical guide to what Codex Memories are for, how they differ from AGENTS.md, and when to avoid, review, or reset memory behavior.
AI Agent Skills vs Instruction Files: When to Use Each
A practical comparison of Claude Code Skills, Codex Skills, GitHub Copilot Skills, Google Antigravity Skills, CLAUDE.md, AGENTS.md, GEMINI.md, and copilot-instructions.md, with guidance on what belongs where.
Claude Code to Codex Handoffs: Three Ways to Preserve Context
How I decide when to use Claude Code versus Codex in the same repository, and how I design handoff documents to transfer context across sessions.
How prebuild Normalization Prevents Validation-Order Failures
How I reduced recurring Astro build failures by moving automatic normalization into prebuild instead of treating each failure as a one-off fix.
How to Verify AI-Implemented UIs with Playwright
How AI Learning Playground positions Playwright alongside structural checks, URL verification, and human review.
Copyright and Publication Responsibility in AI-Assisted Writing
A summary of copyright, responsibility, and reader disclosure policy when using AI as a writing support tool.
A 12-Step Pre-Publication Review for AI Drafts
When using AI to draft blog posts, I separate structural checks from publication approval and keep new articles out of passed until human review is complete.
AWS AI BPR: A Strength-Based Workflow for Process Redesign
A plain-language information summary of AWS AI BPR, its four strength-based steps, and the questions to consider when evaluating it for AI projects.
Three Months of Vibe Coding: From Development to Maintenance
A look back at three months of building and running AI Learning Playground with Vibe Coding, organized around insights from the technical, design, and operational phases.
Claude Dynamic Workflows: Architecture and Parallel Task Design
A plain-language guide to Dynamic Workflows in Claude Code: how multiple AI workers divide a job, which tasks fit, and how to plan outputs, limits, costs, and resumption.
Claude Design: Workflow Roles vs Figma and Canva
A plain-language workflow for using Claude Design for early concepts and dividing later work among Figma, Canva, and Claude Code.
What Is Vibe Coding? Capabilities and Human Review Boundaries
A clear distinction between Vibe Coding and broader AI-assisted development, plus the human review needed for prototypes and production use.
Claude Code Hooks: Setup and Automated Check Examples
A plain-language guide to using Claude Code Hooks for repeated checks, including before-versus-after timing, human approval boundaries, and an adoption process.
How to Reduce Claude Code Token Use Without Losing Quality
Seven ways to reduce Claude Code input and output tokens while preserving required context, verification, and safety constraints.
AI Driven vs AI Native: Differences and When to Use Each
AI Driven and AI Native represent different starting points for how organizations design their relationship with AI. This article clarifies the distinction and what each approach means in practice.
How to Preserve AI Workflow Decisions in lessons.md
How to record an AI workflow problem, cause, resolution, and prevention in lessons.md as a decision history that later work can verify.