Build a 5-Layer AI Agent Stack with Cursor and Firecrawl | Alpha | PandaiTech

Build a 5-Layer AI Agent Stack with Cursor and Firecrawl

An architectural guide to setting up a complete AI Agent system, covering the agent harness, search layer, web data layer (Firecrawl), ops brain, and outbound stack.

Learning Timeline
Key Insights

The Importance of a Web Data Layer

Your AI Agent needs to 'see' the internet through Firecrawl to gather raw data before it can be converted into value, such as meeting notes or useful software context.

The Role of the Ops Brain

Use Notion or Obsidian as more than just note-taking tools; use them as long-term memory (context storage) so your agent always understands your project's current status.
Step by Step

Setting Up a 5-Layer AI Agent Stack Architecture

  1. Select an 'Agent Harness' as your central control hub using tools like Cursor, Codex, or Idea Browser Pro to manage all agents in one place.
  2. Configure the 'Search Layer' using Perplexity MCP or Exa to enable your agents to perform deep information searches.
  3. Integrate Firecrawl as the 'Web Data Layer' to allow agents to scrape, browse, and extract data directly from the internet.
  4. Set up the 'Ops Brain' using Notion or Obsidian to store system context, meeting notes, and vital startup data.
  5. Connect the 'Outbound & Audience Stack' using tools like Instantly or Apollo to automate outreach and audience management processes.

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