without-ai

Design AI-trending-to-zero infrastructure plans with architecture diagrams and phased roadmaps.

2|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/bjamba/bjamba-skills --skill without-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: without-ai
Source: https://github.com/bjamba/bjamba-skills/tree/main/without-ai
Command: npx skills add https://github.com/bjamba/bjamba-skills --skill without-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

It helps you stop relying on one-off LLM outputs by turning prompts into durable, self-hostable infrastructure plans (and optionally a scaffolded repo) that you can run and maintain without ongoing AI usage.

Core Features & Use Cases

  • AI-to-infrastructure transformation: identifies when your prompt is actually asking for a tool, engine, editor, or rules/data layer—then abstracts upward to the real target.
  • Run-ready deliverables: produces an architecture overview with Mermaid diagrams, a phased roadmap with explicit “AI dependency over time,” and copy-paste handoff packets.
  • Optional build-and-prove: can scaffold a minimal repository as a proof-of-plan, demonstrating the infrastructure can answer the original prompt.

Quick Start

Use the without-ai skill by telling it: "Build this without an LLM: make me a clone of Magic: The Gathering that runs on my laptop."

Frequently Asked Questions about without-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build self-hosted infrastructure instead of relying on repeated LLM API calls?▼

You can transition from repeated LLM outputs to durable infrastructure by generating architecture diagrams, phased roadmaps, and handoff packets that shift logic to self-hosted systems and rules engines.

What is AI dependency minimization for stateful workflows?▼

AI dependency minimization for stateful workflows involves designing rule-driven adjudication layers and owned artifacts that process repeated tasks locally, eliminating the need for continuous token-based generation.

Can I scaffold a project repository for a custom editor without ongoing AI usage?▼

Yes, you can scaffold a minimal repository as a proof-of-plan for custom editors, demonstrating that the generated infrastructure can answer your original prompt independently without ongoing AI usage.

When should I use a rules engine instead of an LLM for repeated asset generation?▼

You should use a rules engine instead of an LLM when your prompt requires repeated asset generation, stateful workflows, or rule-driven adjudication, shifting from one-off token answers to durable owned artifacts.

How do I create architecture diagrams for AI-trending-to-zero infrastructure plans?▼

You create architecture diagrams by generating Mermaid-based overviews that map the transition from initial AI-assisted processing to a steady-state, self-hosted system with near-zero AI dependency.

Does this approach work for building a clone of a complex game like Magic: The Gathering?▼

Yes, this approach works for complex games by abstracting the prompt upward to design a custom rules engine and infrastructure plan, enabling the game to run locally on your machine without AI.