Prompting / 4 min read
Read Note
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.
AI NOTES
Short notes for practical AI work.
Not a feed. Just evergreen notes that explain how Newman AI Works thinks about prompt systems, local models, app direction, and launch work.
Local Models / 3 min read
Read Note
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.
App Direction / 4 min read
Read Note
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 / 3 min read
Read Note
Prompting For Repeatable Outputs
Repeatable AI output comes from a stable job, a clear output shape, examples, and a review pass that catches drift.
Local Models / 4 min read
Read Note
Cloud Models Vs Local Models
Cloud and local AI are both useful. The right choice depends on privacy, context size, repeatability, cost, and how much reasoning the task needs.
App Direction / 4 min read
Read Note
A Small App Store Launch Checklist
A small app launch still needs support, privacy, screenshots, store copy, contact paths, and a clean first product promise.
App Direction / 3 min read
Read Note
How To Scope A Tiny AI App
A tiny AI app should do one useful job, make the human review point clear, and avoid promising more automation than it can safely deliver.
Workflow / 3 min read
Read Note
Building AI Workflows Without Overbuilding
The fastest way to ruin a useful AI workflow is to turn it into a platform before the first loop proves itself.