Engineering Notes

Code is abundant now. Architecture, maintainability, and staying true to what the application is for are still the hard part.

All AI-Assisted Development Engineering Practice Infrastructure and Operations Search and Marketing Engineering Security

AI-assisted development Clear topic

AI agent skills AI-assisted development APIs AWS Accountability Architecture Async Authorization Automotive Background Workers Backups Claude Code Quality Consent Content Maintenance Content pipelines Crawlers Data Isolation Debugging Disaster Recovery Django Docker Email Engineering Practice Error Handling GA4 Google Ads Grafana IMAP Image Processing JSON-LD JavaScript Job Queues Landing Pages Local SEO Logging Mailcow Migrations Monitoring Multi-tenant OAuth Observability Opinion Performance PostgreSQL Pre-signed URLs Production PromQL Prometheus Python React Releases Reliability S3 SKIP LOCKED SMS Search Console Security Staging Technical SEO Testing Tooling Triage Twilio Uploads Validation Webhooks Workflow design

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Why I Write Tests Before AI Writes Code

AI coding works when the agent runs inside rules I set: fixed function contracts, known patterns, and tests that define done before the code exists.

Oct 14, 2026 Read more →

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The Hidden Costs of AI-Assisted Development

AI has changed how I write software, and I think the costs are easy to miss: ownership uncertainty, skill atrophy, and accountability that stays with the engineer.

Oct 14, 2026 Read more →

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How This Site's Content Is Built and Validated

Every page on this site is a markdown file that passes a validator, gets its JSON-LD generated from its own content, and imports into Django only when it changed.

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How to Write AI Skills Other People Can Reuse

A skill that works for you is full of your own facts and habits. Making it reusable means splitting the method from the person, and moving fragile steps into scripts.