field-noteStep 1
Your AI Needs a Harness, Not Another Browser Tab
If your AI lives in a browser tab, you don’t have an AI. You have a visitor.
Read NoteField Notes
Building the AI operating system in public.
Learn why the harness matters, launch one working agent, choose model access, protect its context, and build memory that scales from one operator to a company brain.
Why the Harness
field-noteStep 2
A Smarter Model Is Not a Better Harness
Same model. Same prompt. Different system. Completely different result.
Read NoteGetting Started
tutorialStep 1
How to Launch Your Hermes AI Agent in Under 5 Minutes
The quickest honest path from zero to a useful cloud-hosted Hermes agent—plus the cost, OAuth, limitations, and upgrade path nobody should hide in the fine print.
Read NoteModels & Value
field-noteStep 4
The Portability Test for an AI Coding Subscription
Before comparing monthly prices, ask whether the subscription can reliably power the harness where your work runs—and what happens when its included capacity ends.
Read Notefield-noteStep 5
Stop Making One Context Window Do Everything
Hermes delegation protects the parent agent’s working context by sending bounded tasks to isolated workers—and returning only the useful result.
Read NoteOwned Memory
field-noteStep 6
Don’t Let Any AI Company Own Your Agent’s Memory
Models will change. Your agent’s memory, skills, workflows, and operating rules should remain readable, portable, and under your control.
Read Notefield-noteStep 7
Your AI Agent’s Memory Is Becoming a Junk Drawer
Useful memory is selective. Stable facts, reusable procedures, temporary work, stale context, and secrets should not all live in the same place.
Read NoteCompany Brain
field-noteStep 8
The Ontology Is the Moat
Ontology, world model, company brain, LLM wiki—four names for the durable layer under your agents: owned memory, structured relationships, and a maintenance loop that survives model churn.
Read Note