bywinstonkoh87· 1 MCP server
Athena — a local-first agentic PKM that helps you make better decisions with your own context. Persistent memory, structured reasoning, and governed AI agents that work across any LLM.
$git clone https://github.com/winstonkoh87/athena-publicInstalls into the current project.
Install athena-public by running `git clone https://github.com/winstonkoh87/athena-public`, then use it for the current task and follow its documentation at https://github.com/winstonkoh87/athena-public.
| 1 |  |
| 2 | |
| 3 | <div align="center"> |
| 4 | |
| 5 | # Project Athena |
| 6 | |
| 7 | **AI-native personal knowledge management for your AI agents.** |
| 8 | |
| 9 | Capture what you learn, retrieve it when relevant, and carry your context between models — a local-first memory, reasoning, and governance layer for any LLM, across ChatGPT, Claude, Gemini, and whatever you switch to next. |
| 10 | |
| 11 | Own the state. Rent the intelligence. Platforms forget. Athena doesn't. |
| 12 | |
| 13 | *Most assistants remember you so they can agree with you faster. Athena remembers you so it can tell you when you're wrong.* |
| 14 | |
| 15 | [](https://github.com/winstonkoh87/Athena-Public/stargazers) |
| 16 | [](LICENSE) |
| 17 | [](docs/CHANGELOG.md) |
| 18 | [](https://www.reddit.com/r/ChatGPT/comments/1r1b3gl/) |
| 19 | [](https://codespaces.new/winstonkoh87/Athena-Public) |
| 20 | |
| 21 | [Quickstart](#-quickstart) · [How It Works](#-how-it-works) · [Validation Status](#-validation-status--whats-proven-vs-whats-proposed) · [Docs](docs/GETTING_STARTED.md) · [FAQ](Athena-Public.wiki/FAQ.md) · [Safety](SAFETY.md) · [Contributing](CONTRIBUTING.md) |
| 22 | |
| 23 | *Last updated: 22 July 2026* |
| 24 | |
| 25 | </div> |
| 26 | |
| 27 | --- |
| 28 | |
| 29 | ## The Problem |
| 30 | |
| 31 | You've spent months training ChatGPT to understand you. Then a model update resets the personality. Your custom instructions stop working. You can't find that conversation from last Tuesday. And if you switch to Claude or Gemini? **You start from zero.** |
| 32 | |
| 33 | Platform memory is **unreliable, opaque, and locked to one provider**. You don't own it, you can't inspect it, and you can't take it with you. |
| 34 | |
| 35 | ## Why Athena? |
| 36 | |
| 37 | Athena moves the memory layer to **your machine**. Plain Markdown files that you own, version-control, and point at any model. |
| 38 | |
| 39 | - **🧠 Your Memory, Your Machine** — Files on your disk, not in OpenAI's cloud. Read them, edit them, git-version them. |
| 40 | - **🔌 Switch Models Freely** — Claude today, Gemini tomorrow, GPT next week. The memory stays. The model is just whoever's on shift. |
| 41 | - **📈 It Compounds** — Session 500 recalls patterns from session 5. The durable asset isn't the code — it's your data: anyone can fork Athena; nobody can fork your sessions. That's a personal continuity advantage, not vendor lock-in — the files move with you. Honest caveat: compounding needs curation. Keep the `/end` loop running; unpruned memory decays like any archive. [→ The Compounding Effect](Athena-Public.wiki/The-Compounding-Effect.md) |
| 42 | - **⚡ 2K–20K Token Boot** — Scales to the task. Lightweight chat (~2K) → `/start` (~10K) → `/ultrastart` (~20K). 80–98% of your context window stays free, even after 10,000 sessions. |
| 43 | - **🔬 Meta-Game Reasoning** — Generic LLMs optimise *within* the game you're playing. Athena asks whether you should be playing that game at all. [→ Meta-Game Thesis](docs/concepts/Meta_Game_Thesis.md) |
| 44 | - **🛡️ Governed Autonomy** — 6 constitutional laws, 4 capability levels, bounded agency. |
| 45 | |
| 46 | > *A generic LLM is a brilliant amnesiac. Athena is the hippocampus — the memory that makes intelligence useful.* |
| 47 | > |
| 48 | > *Or in engineering terms: The LLM is the engine. Athena is the chassis, the memory, and the rules of the road. Swap the engine anytime — the car remembers every road you've driven.* |
| 49 | > |
| 50 | > *The design philosophy: [augment the human, not replace them](docs/concepts/Grace_Protocol.md). After 1,900+ sessions, the bottleneck shifted — [optimising the operator is now higher-leverage than optimising the AI](docs/USER_DRIVEN_RSI.md#phase-2-optimising-the-operator).* |
| 51 | |
| 52 | ### The Human Augmentation Thesis |
| 53 | |
| 54 | Athena's centralised design principle: **augme |