Start AI Coding from Zero
Understand models, providers, coding agents, tokens, Markdown, permissions, and the Git workflow before you begin.
Practical guides for AI Blueprint, coding agents, design, and AI content production with reviewable workflows.

Search any term or follow 16 free guides, including an 8-module AI coding path and the AI Blueprint product guide.
16 guides found
Understand models, providers, coding agents, tokens, Markdown, permissions, and the Git workflow before you begin.
Install an IDE and start safely with VS Code, Antigravity, Codex, Claude Code, Gemini CLI, OpenCode, ZCode/GLM, or Kimi Code.
Choose models efficiently and understand why quotas, units, and reset windows differ by provider.
Compare direct providers and aggregators, then validate models, outputs, fallbacks, cost, security, and lifecycle before production.
Create safe checkpoints, inspect diffs, use branches, recover mistakes, and publish a repository to GitHub.
Write executable prompts, select relevant context, and turn an idea into testable requirements.
Write clear repository instructions, understand project data files, and isolate AI coding work with branches or worktrees.
A knowledge base for choosing frontend, backend, hosting, database, and mobile stacks from requirements, cost, risk, and product stage.
Learn navbars, heroes, CTAs, sections, cards, sidebars, forms, modals, states, and responsive layouts for precise UI prompts.
Turn visual references into a DESIGN.md, an asset inventory, and one reviewable vertical slice.
Run PostgreSQL locally, protect environment variables, and understand schemas, migrations, auth, permissions, and APIs.
Understand Free Tier limits, safely create and apply revision proposals, then unlock Project ZIP for a coding agent.
Understand every Project ZIP file, then move from extraction and a Git baseline to staged, verified implementation with a coding agent.
Move an application from local to preview and production, connect a domain safely, and maintain it after launch.
A free public 8-module path with 10 practical exercises, from choosing tools to testing, debugging, and deployment.
Understand AI Blueprint outputs, lifecycle, states, revisions, versioning, export, billing, security, and feature boundaries in one guide.

Learn how to protect secrets, create a Git baseline, read the manifest, and run each implementation stage safely.
Open the Blueprint to Code tutorial