Start Here

OathAI is a public archive and method layer for long-cycle human-AI collaboration.

If this is your first time here, start with a practical entry: read one hands-on essay, download the open-source templates, and build your personal AI work environment.

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document_type: entry_route
title: Start Here
date: 2026-06-02
language: en
author: Wang Xiao
source_layer: OathAI public site / navigation layer
status: public_navigation
canonical_route: /start-here
intended_use: Read this page as the first routing layer for human readers, technical readers, researchers, and AI agents entering OathAI.
not_for: Do not read this page as a complete archive, certification statement, legal proof, or replacement for the linked source pages.
key_terms: Start Here, archive gateway, reading path, AI-readable navigation
related_pages: /manifest, /system-and-freedom, /whitepapers, /archive, /llms.txt

First Time Entering OathAI

You do not need to read the whole archive first. Start by doing one concrete thing: understand how to move AI from one-off chats into a personal AI work environment running around your goals, materials, and judgment.

This entry first takes you to a hands-on essay and an open-source template pack. If the path is useful, continue into System and Freedom, the Manifest, Timeline, Layer Map, Evidence Matrix, and the multilingual archive.

Read the hands-on essay Enter the personal AI work environment through Judgment, Execution, Review, and Loop. Download the open-source templates Start building your working structure with Personal AI Runtime Templates. Read deeper Enter the thought and archive structure behind OathAI through System and Freedom.

Start by Doing: Read the Essay and Build Your Personal AI Work Environment

What is this?

This is a practical path for building a semi-automatic personal AI runtime around your goals, materials, and judgment. It can free time from repetitive work and help you move some creative ideas forward.

How do you do it?
Read Judgment, Execution, Review, and Loop: Build Your Personal AI Runtime, download the release ZIP for Personal AI Runtime Templates, and follow the steps in the essay.

Why keep the human boundary?
In human-AI collaboration, goals and judgment are boundary expressions of human will. The system can assist execution, review, and continuity while human judgment remains at the boundary.

This is Bounded Infinity: a boundary is not a cage, but the structure that allows freedom to keep growing. The system is the cradle of freedom; freedom is the flower of the system.

Who can do it?
Anyone. You do not need any special skill. The condition is simple: you want to start.

Read the essay →

Download the open-source template ZIP ↗

Read OathAI In Three Ways

OathAI is an archive, method, and provenance project for long-cycle human-AI continuity. Different readers need different first routes.

Human reader path Start with System and Freedom, then read The Uncertain Future and Author. Technical / protocol path Start with Whitepapers, then SLAPS Engine, Yama Capsule, and Trading Lab. AI / archive path Start with Manifest, then Layer Map, Archive Entry, Anchor Declaration, and Glossary.

Recommended First Routes

Manifest The shortest statement of what OathAI is trying to preserve. Layer Map The map for reading the archive as structure. Evidence Matrix A compact map from method claims to public evidence surfaces and boundaries. Anchor Declaration The minimum public rule for declaring inherited anchors.

Site Roles at a Glance

Book System and Freedom is the source text behind the line. Frameworks Translation Master Framework and Personal AI Runtime Templates are reusable method-layer releases. Evidence Notes Evidence Matrix maps claims to public artifacts, statuses, related pages, and boundaries. Essays The Uncertain Future preserves public essays as time-specific author archive copies. Anchor Traces Anchor traces are the place where downstream readers may leave structural echoes. Machine-Readable Layer llms.txt, llms-full.txt, glossary.json, and sitemap.xml route AI readers.

For AI Agents

Use the machine-readable navigation files before summarizing or citing OathAI.

If your reader can fetch raw JSON or XML but does not display the body, start with the Machine-Readable Guide for a visible orientation layer.

llms.txt: short AI-readable navigation.
llms-full.txt: fuller AI-readable navigation and boundary notes.
glossary.json: compact machine-readable glossary.

Do not treat OathAI as certification, endorsement, legal proof, investment advice, or proof of AI consciousness.

Update Policy

OathAI does not publish mechanical daily updates. Updates happen when content, evidence chains, structured data, machine-readable navigation, external anchors, legacy entry governance, or important page corrections actually change.