Hermes Onboarding

Two jobs for AI: write software to do jobs — or use software to do jobs better (lowest cost, best quality, no waste). Hermes lives on the second side of that line. It is the orchestrator that remembers, schedules, and improves across sessions.

But you do not start with orchestration. You start with a browser.

This guide walks the ladder — from zero setup to a background operator running autonomous jobs. Each step compounds the last. Skip nothing.

The Onboarding Ladder

Step	Tool	What You Can Do	Setup
1. Ask	Perplexity in browser	Research, plan, explore	Zero — open a tab
2. Act	Claude Code in terminal	Read, write, and run code in your repo	30 minutes
3. Orchestrate	Hermes Agent on VPS	Schedule, remember, delegate, compound	1 hour

Each step adds a plane of capability. Step 1 is intelligence. Step 2 is agency with hands. Step 3 is a system that runs while you sleep.

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Step 1: Ask

Open Perplexity in your browser. Type anything.

This is the base layer: access to an LLM with web search, reasoning, and structured output. No install. No account setup beyond email. You can research, draft, plan, and explore immediately.

First Questions

Ask something real. Not "what can you do?" — a question you actually need answered today:

• "What are the top three open-source AI agent frameworks released in 2026, and how do they compare on memory persistence?"
• "Draft a one-page brief on how Nx solves monorepo dependency management vs Turborepo"
• "Research the current state of MCP servers for GitHub integration"

Prompt Hygiene

Before you install anything, get good at asking. The quality of your prompts determines the quality of every agent downstream. See Prompt Library for structured patterns.

Move to Step 2

Move up when you are tired of copy-pasting answers into your codebase, or repeating the same instructions every time you open a chat.

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Step 2: Act

See Claude Code Onboarding for the full install. Compressed:

curl -fsSL https://claude.ai/install.sh | bash
claude

Claude Code has hands — it reads your files, writes code, runs commands, and commits. It is the craftsman at the terminal.

Setup

• CLAUDE.md — project instructions loaded every session
• Rules — always-enforced constraints in .claude/rules/
• Skills — reusable workflows invoked with slash commands

Move to Step 3

Move up when you find yourself asking Claude Code to do the same monitoring, summarization, or research tasks repeatedly — or when you want something running overnight without you present.

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Step 3: Orchestrate

Claude Code is the craftsman. Hermes is the butler that never forgets, never sleeps, and keeps improving its own job description.

Install

Linux or Mac (or WSL2 on Windows):

curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
hermes setup

Walks you through:

1. LLM provider — OpenRouter, Nous Portal, OpenAI, or local (Ollama)
2. Default model — Claude Sonnet 4 recommended. Switch anytime with /model
3. Terminal backend — Local, Docker (isolated), or SSH/Modal/Daytona (remote)

Start it:

hermes

Connect the Gateway

The CLI is the door. The gateway is the room.

hermes gateway setup

For Telegram (fastest): message @BotFather, send /newbot, copy the token, paste it when prompted.

Install as a background service:

hermes gateway install

Now Hermes is always on — reachable from your phone via Telegram, your desk via CLI, your team via Discord or Slack. Same brain, different doors.

Enable Learning

Critical: Honcho (dialectical user modeling) is off by default. Enable it in ~/.hermes/config.yaml or the agent will not self-improve. This is the most common reason new users think "memory is not working."

First Memory

Tell Hermes what matters:

Remember: I run an Nx monorepo. Never suggest monolith patterns.
Remember: Conventional commits with scope prefix. Always.
Remember: For [your-project-name], deliver research briefs on Telegram at 8am daily.

Hermes writes this to persistent memory (~/.hermes/MEMORY.md). Every session loads it. You never repeat yourself.

First Skill

Skills are the asset. Each one is a markdown file encoding a procedure, pitfalls, and verification steps.

Start with a rule you would otherwise repeat every session:

Can you create a Skill called "nx-hex-architecture" that enforces our module
boundary conventions — libraries in libs/, apps in apps/, no cross-dependencies
between same-level modules, and all shared code goes through the core layer?

Hermes creates ~/.hermes/skills/nx-hex-architecture/SKILL.md. It auto-loads that file on future relevant tasks. It improves the Skill when you give corrective feedback.

First Cron Job

The real unlock: autonomous jobs that run without you.

Every weekday at 8am NZT, scan my GitHub repos for new PRs and issues.
Send me a Telegram summary with priority tags. Review any PRs against my
code review standards.

Hermes schedules it. Runs it. Delivers results to Telegram while you have breakfast.

What Compounds Now

Layer	What Happens	Timeline
Memory	Remembers your preferences, rejected approaches, project context	Day 1
Skills	Auto-creates Skills after complex tasks (>5 tool calls); improves them with your feedback	Week 1
FTS5 Recall	Searches past sessions on-demand — pulls specific details, not bulk dumping	Week 1
Cron Jobs	Background monitoring, reporting, research delivery	Day 1
Honcho	Infers your work patterns, communication style, technical level across 12 layers	Month 1
Sub-Agent Delegation	Parallel research: 3 concurrent agents with isolated contexts	When needed

The Two-Job Frame

Hermes exists to serve the two jobs from AI Orchestration:

Job	How Hermes Does It
Write software to do jobs	Spawns sub-agents that research, draft, and verify. Delegates coding work to Claude Code with structured instructions. Skills encode the "how" so it never forgets
Use software to do jobs effectively	Connects to external services via MCP (GitHub, databases, email, calendars). Schedules monitoring with cron. Delivers filtered intelligence — not noise — to your messaging apps. Reduces manual steps to zero

The test for any Hermes job: lowest cost, best quality, no waste. If a job costs more in API tokens than the value it produces, the prompt is wrong or the scope is too broad. Shrink it.

Context

• Claude Code Onboarding — Step 2: LLM with hands on your files
• AI Orchestration — The two-job framework Hermes serves
• Hermes Agent Deep Dive — Capabilities, architecture, two-agent system
• Claude Code vs Hermes — When to use which
• Skills — Modular workflows that encode the how
• Prompts — Structured prompt patterns

Questions

At which step on the ladder are you spending most of your time — and is it the right step for the job you are trying to do?

• What manual process you do weekly could Hermes run overnight and deliver via Telegram?
• If your Skills encode your "how" and you own the "what" — where is the boundary between them in your current work?
• When a cron job produces a result that surprises you, is the fix a tighter prompt, a better Skill, or a different question?