AI chat assistant: site-aware conversational guide

[silverbackdan]

Goal

Build an AI-powered chat assistant embedded in the docs/marketing site that can discuss CWA in a relatable, conversational way — similar to how NotebookLM works after ingesting a knowledge base.

What it should do

• Answer questions about whether CWA is right for the user's project
• Discuss how the module would work for their specific use case
• Draw on both the advertising/marketing pages (about, built-for-business, etc.) and the full technical documentation
• Help non-technical stakeholders understand the value proposition
• Help developers understand how to approach their implementation

Knowledge sources

• /llms-full.txt — full docs content (auto-generated, always up to date)
• /llms.txt — structured index
• Marketing/about page YAML content (content/*.yml)
• Potentially the GitHub READMEs / changelogs of the API bundle and Nuxt module

Approach (from earlier design discussion)

The owner has additional context from a prior Claude session on the planned implementation approach. Key notes:

• Embed the chat UI on the docs/marketing site (not a separate tool)
• Ingest the full site content so the AI has CWA-specific knowledge, not just generic answers
• The tone should be relatable and advisory, not a dry FAQ bot
• Should handle both "is this right for me?" pre-sales questions and "how do I do X?" developer questions

Foundation already in place

• GET /llms.txt — structured page index, auto-updated on deploy
• GET /llms-full.txt — full concatenated docs text, auto-updated on deploy

These can be fed directly to an AI system at startup or used as retrieval context.

Next steps

1. Decide on the AI provider / embedding approach (RAG vs full-context vs Claude API with system prompt)
2. Design the chat UI component
3. Decide where it lives — floating button on all pages, dedicated /ai page, or both
4. Handle the marketing pages content (currently YAML, needs to be included in the knowledge base)