# blakeandersonw/ai-app-playbook

> A playbook for building and monetizing AI-powered mobile and web apps, covering niche selection, stack choices, costs, and distribution, with an AGENTS.md file for coding agents.

- Magnitude: 4.9 out of 10 — Early signal
- Stars: 182 total · +39 stars measured 2026-10-26, 20:11–21:44 UTC, ≈ 42 by evening
- Star trust: star growth looks organic
- Category: Learning & lists · Language: TypeScript · License: MIT · Created: 2026-10-26 · Last push: 2026-10-26
- GitHub: https://github.com/blakeandersonw/ai-app-playbook · Page: https://gitnova.dev/en/r/blakeandersonw/ai-app-playbook

## Useful for

- Pick a niche and validate demand using the scorecard and waitlist approach.
- Set up a Cloudflare-based backend with Workers, D1, and R2 following the templates.
- Estimate monthly costs and revenue for different user scales using the provided tables.

## Why it’s here

- Star-counter measurements on 2026-10-26 (UTC), 20:11–21:44: 143 → 182 stars (+39). This is the change over that interval.
- Estimated end-of-day forecast: about +42 stars, using observed gains and the previous day.
- The repository is 0 days old and already has 182 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #125.
- About 115 forks a day — people are taking the code.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 24
- Issues and pull requests: 0
- Watchers: 0
- Average over the last week: 42 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 25

## Stars per day, last 1 day (oldest → newest, today is partial)

2026-10-26 … 2026-10-26: 39

## Spotted in now

- Top new repositories this week: #125

## More in this category

1. **designfuchen/word-atlas** — 8.2 · Breakout · Learning & lists · TypeScript · +1,146 stars measured 2026-10-26, 00:11–21:43 UTC, ≈ 1,252 by evening
   A free, open-source PWA for memorizing 7,298 IELTS words, each with an original illustration, UK/US audio and example sentences, using FSRS spaced repetition with no login. The dataset is CC BY 4.0.
   Full card: https://gitnova.dev/en/r/designfuchen/word-atlas.md
2. **amosblomqvist/learnharness** — 7.9 · Breakout · Learning & lists · TypeScript · +538 stars measured 2026-10-26, 05:01–21:43 UTC, ≈ 589 by evening
   A desktop app that uses AI agents to plan and teach lessons from your current understanding to a goal, tracking progress in a persistent knowledge graph.
   Full card: https://gitnova.dev/en/r/amosblomqvist/learnharness.md
3. **luongnv89/claude-howto** — 6.1 · Breakout · Learning & lists · Python · +266 stars measured 2026-10-26, 00:11–21:43 UTC, ≈ 292 by evening
   A visual, example-driven guide to Claude Code with copy-paste templates: from basic commands to agents, hooks, skills, and MCP servers. Provides a structured learning path from beginner to power user.
   Full card: https://gitnova.dev/en/r/luongnv89/claude-howto.md
4. **agharsallah/esp-labs-web** — 4.8 · Early signal · Learning & lists · TypeScript · +54 stars measured 2026-10-26, 00:12–21:44 UTC, ≈ 59 by evening
   An interactive web guide to the ESP32-S3: 32 hands-on labs with in-browser simulators, a live pinout, a 3D board and a line-by-line reader for the esp-labs firmware. Available in 8 languages, including Arabic (RTL).
   Full card: https://gitnova.dev/en/r/agharsallah/esp-labs-web.md
5. **rohitg00/ai-engineering-from-scratch** — 4.6 · Steady · Learning & lists · Python · +521 stars measured 2026-10-26, 00:12–21:44 UTC, ≈ 570 by evening
   Open-source AI engineering curriculum: 523 lessons across 20 phases (~342 hours) in Python, TypeScript, Rust and Julia, where every lesson ships a reusable artifact such as a prompt, skill, agent or MCP server.
   Full card: https://gitnova.dev/en/r/rohitg00/ai-engineering-from-scratch.md

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-10-26 21:55 UTC, updated every 30 minutes.