How to Build Your Own Hermes Agent

Overview

Hermes Agent is an always-on AI assistant reachable from Telegram, Slack, email, and more, accessible via CLI, gateway, or API, and it keeps learning from every conversation instead of starting cold each time.

Under the hood it runs one core agent loop with pre-installed tools and skills, and two layers of memory: markdown files it edits itself, plus a full session transcript store it can search back through.

How does this help?

• Removes the confusion of wiring an agent to Telegram, Slack, and email separately, one gateway handles all of them through the same async loop
• Gives you a memory architecture you can reuse in your own builds: markdown files for personality and facts, SQLite transcripts for recall, optional external memory for cross-session context
• Shows exactly when and how context compresses, so long conversations don't quietly blow past the model's context window

Apps and tools

• Hermes Agent installed
• Command line access
• Telegram, Slack, or email, for the gateway (optional, pick what you need)
• External memory provider: Mem0, SuperMemory, or Honcho (optional)

Main steps: understanding the architecture

Step 1: Understand the core agent loop

• Every message builds context from internal memory and the system prompt before the model sees it
• The model runs with full context and history, calling tools as needed, then a memory-update step analyses the exchange and writes anything worth keeping, e.g. your job title, into user.md

Step 2: Know the three files that build context

• soul.md sets the agent's personality, tone, and goals
• user.md fills itself in automatically as it learns about you
• memory.md holds facts, tool patterns, and workflows it's picked up over time

Step 3: Watch for context compression

• Once a conversation hits roughly 50% of the context window (tunable to 70 to 80%), Hermes summarises older messages instead of dropping them
• Token usage is estimated by character count at first, then switched over to the model's own usage numbers once they're available

Step 4: Wire up the gateway

• One async loop listens across Telegram, Discord, email, SMS, WhatsApp, and Slack, using webhooks, polling, or websockets depending on the platform
• Full context per conversation is pulled from a SQLite database keyed by session ID, so switching platforms mid-conversation doesn't lose the thread

Step 5: Add external memory if you need it

• Mem0, SuperMemory, or Honcho query after your first message in a conversation, not before
• Hermes waits until it understands the topic before pulling in outside context, rather than querying blind on every message

Final checklist

• soul.md, user.md, and memory.md all in place
• Gateway connected to at least one platform
• Compression threshold understood and tuned if needed
• External memory provider wired up, if your use case needs cross-session recall