Exporting Your Hermes 3 Conversations for RAG and Second Brain

Nous Research’s Hermes 3 models are specifically tuned for advanced reasoning, system prompt obedience, and structured outputs. Because they don’t have the heavy-handed safety filters of proprietary models, they are the go-to choice for complex problem-solving and coding tasks.

But what happens after Hermes 3 gives you a brilliant, 2,000-word architectural breakdown? If you leave it in the chat interface, it is practically lost.

The RAG and Second Brain Approach

Power users are increasingly using RAG (Retrieval-Augmented Generation) and “Second Brain” apps like Obsidian and Notion to store their AI interactions.

When Hermes 3 generates a complex Mermaid diagram, a Python script, or an XML dataset, that output is an asset. To preserve it perfectly, you need Markdown. Markdown handles code blocks, bold text, and headers natively, making it the perfect format for both human reading and machine ingestion.

The Workflow

If you use web-based interfaces to access Hermes 3 (such as through OpenRouter or local web UIs), extracting that data cleanly can be frustrating. Copy-pasting often destroys formatting.

Here is the professional workflow:

1. Generate: Have your deep, technical conversation with Hermes 3.
2. Export: Use tools like the Pczio Claude Downloader (if using Claude interfaces) or our upcoming custom web exporters to download the entire thread.
3. Save: Choose the Markdown (.md) format during export.
4. Ingest: Drop the Markdown file directly into your Obsidian vault or your local RAG pipeline directory.

Because Pczio extensions preserve exact Markdown syntax, your local vector database can chunk and index the Hermes 3 outputs perfectly. The next time you ask your Hermes Agent a question, it can retrieve the exact reasoning trace from your past conversations, creating an infinite loop of productivity.