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My Mom Called About Crochet. So I Built Her a Pattern Design Tool.

Pattern started with a phone call from my mom about crochet graph paper. Here's how that conversation became a design tool — and how every feature traces back to protecting her work.

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From DynamoDB to Bunny Database

How I migrated the portfolio's data layer from DynamoDB to Bunny Database, what changed about access patterns, and why a simpler database on the same platform as the runtime was the right call.

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Collapsing Lambda into Containers

How I replaced a stack of Lambdas and API Gateway with a single Magic Container that owns its own routing, and why the simpler shape was worth the move.

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Edge Auth Without Lambda@Edge

How I replaced Lambda@Edge and CloudFront Functions with Bunny's edge behavior and Magic Containers, and why the auth story got cleaner when it stopped being a separate compute layer.

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Why I Moved My Portfolio from AWS to Bunny.net

Why I moved a multi-app portfolio from AWS to Bunny.net: privacy, security, speed, better operator ergonomics, and working with a smaller company that builds with real users.

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Reviewable AI Engineering Workflows

Reviewable AI engineering workflows create safer software teams by keeping audit trails, approvals, queue state, and human review ahead of deployment.

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Tarot Journals and Readings Now Have Stronger Encryption

The latest tarot update adds end-to-end encryption for saved journal content, local unlock after refresh, simpler password changes, and optional recovery support.

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Human-Centered AI Product Design

Human-centered AI product design requires transparent systems, clear operator controls, and interfaces that help people make better decisions instead of surrendering them.

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Why The New Beautiful Me Uses AI for Reflection Instead of Prediction

The New Beautiful Me uses AI for guided interpretation around tarot readings, while keeping private journals outside the AI workflow.

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Why an AI Code Review Dashboard Needs Human Approval

A trustworthy AI code review dashboard needs structured findings, approval checkpoints, and evidence-backed status instead of silent autonomous changes.

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Building Privacy-First AI Products

A practical approach to building privacy-first AI products with data minimization, user control, transparent AI, and architectures that reduce unnecessary exposure.

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