---
title: Atman — Persistent Memory for AI Agents
emoji: 👀
colorFrom: purple
colorTo: indigo
sdk: static
pinned: true
short_description: Persistent identity layer for AI agents
---

# Atman · Persistent Memory Layer for AI Agents

> *In Indian philosophy, Atman is the unchanging self — the core that remains
> constant through all change. We give AI agents the same thing.*

---

## The Problem

Your agent can reason, write code, and explain quantum mechanics.
But the moment a session ends — it forgets everything about *itself*.

Not just facts. The sense of continuity. Who it spoke to, what it learned,
how it changed its mind. Every session starts from a stack of notes:
*"you're this kind of agent, these are your values"* — taken on faith,
not lived experience.

**Atman fixes this.**

---

## What It Is

A local memory and context system that runs alongside your LLM —
augmenting cognitive capabilities without steering opinions or output.

Seven components work together:

| Component | What it does |
|-----------|-------------|
| **Factual Memory** | Verifiable facts with relations, no hallucination layer |
| **Experience Store** | First-person lived session experiences with salience decay |
| **Identity Store** | Stable self-model: principles, values, behavioral anchors |
| **Reflection Engine** | Between-session processing — finds patterns, refines principles |
| **Session Manager** | Assembles coherent context on session start |
| **Reality Anchor** | Detects identity drift during context pressure |
| **Affective Regulation** | Emotional tone calibration without pretense |

---

## Key Properties

- **Local-first** — Postgres + pgvector + Ollama, no cloud required
- **Model-agnostic** — OpenAI-compatible endpoint or Anthropic SDK, config-only switching
- **Russian/English bilingual** — hard requirement throughout all components
- **Augments, doesn't steer** — improves retrieval and grounding; never influences opinions
- **Optional eval isolation** — all research/benchmark tooling in `atman[eval]`, zero prod leakage

---

## Architecture

```

Session start 
	Session Manager pulls together: 
			Identity Store — who the agent is Experience Store — what it lived through 
			Factual Memory — what it knows 
			Reflection output — what it concluded last time 
During session 
	Reality Anchor watches for identity drift in real time 
Session end 
	Reflection Engine processes the session 
		→ updates Identity Store 
		→ updates Experience Store

```

---

## Status

```

```
	● Research              ✅ Complete
	● Design                ✅ Complete
	● Prototyping           ← We are here
	  ├─ Factual Memory     ✅ Stable (v0.1.0)
	  ├─ Experience Store   ✅ Stable (WP02)
	  ├─ Session Manager    🔧 High readiness — debugging (current focus)
	  ├─ Reflection Engine  🔧 Medium readiness — in development
	  ├─ Skill Manager      🔧 Medium readiness — in development
	  ├─ Identity Store     🔧 Low readiness — in development
	  └─ CI & test coverage ✅ GitHub Actions on `main`/PRs (`make check`, pytest-cov ≥90%)
	○ First production slice
	○ Integration
	○ Evolution
```

```

---

## Stack

- Python 3.11 · Pydantic · PostgreSQL + pgvector
- BGE-M3 + bge-reranker-v2-m3 (hybrid retrieval)
- LlamaIndex · httpx · Anthropic SDK

---

## Links

- 🌐 [atmanai.dev](https://atmanai.dev)
- 📖 [Manifesto](https://github.com/hleserg/atman/blob/main/MANIFEST.md)
- 🏗 [Architecture docs](https://github.com/hleserg/atman/blob/main/docs/architecture/SYSTEM.md)
- 💻 [GitHub](https://github.com/hleserg/atman)

---

*Atman is a hypothesis in the form of a system:
that behavioral consistency, accumulated experience, and reflective capacity
are sufficient conditions for something worth calling identity.*