How I Think About Prompt Systems
A prompt system is more than one clever instruction. It is examples, boundaries, checks, and a repeatable way to judge the output.
Find a practical note.
Working guidance for local-first tools, AI systems, mobile UX, privacy, support, and launch decisions.
31 notes found
Showing 1–8 of 31.
When Local AI Models Make Sense
Local models are useful when privacy, repeatability, speed, or batch review matter more than having the biggest hosted model every time.
Turning An App Idea Into A Tiny Launchable Product
The first launch should prove the useful center: one audience, one job, one workflow, and enough support material to be real.
Prompting For Repeatable Outputs
Repeatable AI output comes from a stable job, a clear output shape, examples, and a review pass that catches drift.
Why Local-First App Design Matters
Local-first app design keeps the useful work close to the user, reduces account friction, and makes privacy claims easier to understand.
An Offline-First Collection Tracker Checklist
A checklist for offline-first collection tracker apps: collections, item fields, photos, location labels, search, backups, privacy, and no cloud lock-in.
A Collectory Location Label System Checklist
A practical checklist for naming shelves, display cases, bins, closets, garage cabinets, and other collection storage locations before tracking items.
An Android Internal Testing Readiness Checklist
A checklist for preparing an Android app internal test without implying public launch: privacy, support, backup, testers, feedback, and status copy.