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Vibe Coding with Lamatic.ai

Vibe Coding with Lamatic.ai

Developers working on Lamatic.ai Docs can now supercharge productivity using AI‑assisted coding tools. This guide explains how to configure and use Vibe Coding tools—such as GitHub Copilot, Cursor, and Claude—for a deeply contextualized coding experience powered by the llm.txt file.

1. Prerequisites

  • Node.js 18+ and Git installed
  • Access to the Lamatic.ai Docs repository
  • Any LLM‑based coding assistant installed:     * GitHub Copilot (extension enabled in VS Code)     * Cursor IDE (with Lamatic project workspace loaded)     * Continue.dev (community‑compatible setup)

2. Understanding llm.txt

The llm.txt file defines the directories and configuration files that AI tools should prioritize when offering suggestions. This ensures the assistant understands Lamatic.ai’s architecture, ensuring relevant and structured completions.

The file includes:

  • /components/ — Core UI and React elements
  • /pages/docs/ — Lamatic documentation and integration guides
  • /next.config.mjs — Next.js configuration
  • /package.json — Node.js project manifest
  • /pyproject.toml — Python project configuration

By guiding your LLM here, you prevent distractions from build artifacts or external modules.

3. Setting Up Vibe Coding Tools

GitHub Copilot Setup

  1. Ensure the Copilot extension is installed in VS Code.
  2. Context Note: Copilot does not automatically read the llm.txt file. To ensure Copilot uses the project context:
    • Use Attach Context: In the Copilot Chat pane, click the paperclip icon and manually attach the necessary component folders (e.g., /components/, /pages/docs/).
    • Use Tags: Explicitly reference files in your prompts (e.g., #file:components/Header.tsx).
  3. For specialized instruction, ensure github.copilot.chat.codeGeneration.useInstructionFiles is enabled to read any .instructions.md files you may create in the .github folder.

Cursor Integration

  1. Open the Lamatic Docs root folder in Cursor IDE.
  2. Cursor automatically respects the llm.txt file as its project context.
  3. Use the in‑line prompt (Cmd/Ctrl + K) to generate or refactor code.     Example prompt:     > “Based on Lamatic’s DocsNav component, generate a collapsible section with AI‑powered section titles.”

Cursor lets you connect custom AI APIs too—ideal for contributors using their own OpenAI or Anthropic credentials for Lamatic.ai development.

4. Example Prompts and Best Practices

ScenarioBasic PromptContext‑Aware Prompt
Component Creation"Make a new button""Using Lamatic’s Button.tsx design from /components/ui/, create a PrimaryBadge variant matching Lamatic.ai styling."
Documentation Enhancement"Add integration doc""Following /pages/docs/integrations, create a doc titled AI Automation Setup demonstrating Lamatic.ai’s workflow configuration."
API Logic"Write API route""In reference to pyproject.toml dependencies, implement a Python FastAPI route for Lamatic.ai’s webhook ingestion."

Pro Tip: Include component or page paths in prompts (e.g., components/ui/Button.tsx)—LLMs use them as explicit context anchors.

5. Troubleshooting

IssuePossible CauseRecommended Solution
AI not responding contextuallyIDE not loading llm.txtRestart your environment or reload the Lamatic Docs workspace.
Off‑theme code suggestionsOutdated assistant cacheClear Copilot/Cursor cache or reload Lamatic configuration.
Code format mismatchesLocal ESLint not runningExecute npm run lint or npm run format.

Why This Matters

Lamatic.ai thrives on collaborative, intelligent documentation. By configuring context correctly and aligning Vibe Coding tools, your LLM assistant effectively “understands” Lamatic’s structure—making your prompts smarter, faster, and fully contextual.

These improvements allow new contributors to get productive immediately, reducing setup friction and ensuring Lamatic.ai remains a pioneer in developer‑friendly AI documentation integration.


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