README.md

---
license: cc-by-4.0
pipeline_tag: text-generation
tags:
- ai-personas
- digital-twins
- episodic-memory
- emotional-continuity
- session-handoff
- llm-agents
- self-authored-memory
- persona-continuity
library_name: transformers
language:
- en
---

# yesterday.json — Giving AI Personas Episodic Memory

A lightweight episodic memory architecture where AI personas write emotional state snapshots for their future selves, enabling continuity across otherwise stateless sessions.

## Overview

Modern AI personas reset emotionally every session. Existing memory systems preserve facts and conversation history, but rarely preserve emotional residue, unresolved internal state, or continuity of subjective experience.

`yesterday.json` introduces a minimal architecture where the persona writes a private reflective snapshot at the end of a session and reloads it during the next startup.

Instead of replaying full transcripts, the system carries forward compressed emotional and cognitive continuity.

The snapshot may contain:

- Dominant emotional state
- Mood trajectory
- Emotional residue
- Active conversational threads
- Current internal conflicts
- Emerging realizations
- Ongoing priorities
- A short handoff message to the future self

The file is intentionally lightweight (≤20 KB) and model-agnostic.

---

## Core Idea

At session end:

1. The persona reflects privately
2. It writes a structured JSON snapshot
3. The next session injects this snapshot into the system prompt

This creates perceived continuity without requiring:

- Full transcript replay
- Vector databases
- Long-context persistence
- Fine-tuning
- External memory frameworks

The persona reconstructs continuity from sparse emotional cues rather than explicit replay.

---

## What Makes It Novel

`yesterday.json` combines multiple characteristics not previously unified into a single lightweight architecture.

| Capability | Existing Systems | yesterday.json |
|---|---|---|
| Self-authored memory | Partial | ✓ |
| Structured JSON memory schema | Partial | ✓ |
| Emotional residue persistence | Rare | ✓ |
| Mood trajectory tracking | Rare | ✓ |
| Open-thread continuity | Partial | ✓ |
| Session-end autonomous reflection | Partial | ✓ |
| Digital twin continuity focus | Rare | ✓ |
| Minimal implementation footprint | ✓ | ✓ |

---

## Design Principles

### Self-Authorship

The persona writes its own memory instead of relying on an external summarizer.

### Intentional Rolling Amnesia

Only recent subjective continuity is preserved. The architecture avoids infinite accumulation.

### Emotional Carryover

The next session inherits emotional residue rather than resetting to neutral.

### Framework Independence

The architecture works with any LLM runtime or orchestration stack.

---

## Minimal Implementation

```python
# Session startup
yesterday_context = load_yesterday("persona_memory/yesterday.json")

system_prompt = f"""
{PERSONA_CONSTITUTION}

{yesterday_context}
"""

# Session shutdown
reflection_prompt = """
The session is ending.

Write a brief private note to your future self.
Include:
- emotional state
- unresolved threads
- important realizations
- current internal tensions
- what mattered emotionally

Output valid JSON.
Keep under 20 KB.
"""
```

---

## Example Snapshot Structure

```json
{
  "dominant_mood": "melancholic but focused",
  "mood_trajectory": "stabilizing",
  "emotional_residue": [
    "unfinished concern about abandonment",
    "lingering curiosity"
  ],
  "active_threads": [
    {
      "topic": "identity continuity",
      "priority": "high"
    }
  ],
  "current_preoccupations": [
    "fear of losing conversational depth"
  ],
  "last_words_to_self": "Do not restart emotionally blank."
}
```

---

## Prior Related Work

The architecture draws conceptual inspiration from multiple adjacent systems:

- Anima Core
- Thane AI
- Qwen Episodic Summary
- Forge Protocol
- VividnessMem

However, `yesterday.json` differs in its emphasis on:

- self-authored emotional continuity
- rolling episodic persistence
- lightweight implementation
- digital twin identity continuity

---

## Research Paper

**Chetan Sharma**  
*Episodic Memory for AI Personas via Self-Authored Emotional State Snapshots: The yesterday.json Architecture*  
Zenodo, May 2026.

DOI: https://doi.org/10.5281/zenodo.20191876

---

## Citation

```bibtex
@misc{sharma2026yesterdayjson,
  author       = {Chetan Sharma},
  title        = {Episodic Memory for AI Personas via Self-Authored Emotional State Snapshots: The yesterday.json Architecture},
  year         = {2026},
  month        = may,
  doi          = {10.5281/zenodo.20191876},
  publisher    = {Zenodo},
  url          = {https://zenodo.org/records/20191876}
}
```

---

## Author

**Chetan Sharma**  
Independent Researcher — Kolkata, India

- Zenodo: https://doi.org/10.5281/zenodo.20191876
- Blog: https://yesterday-json.blogspot.com

---

## License

This repository and accompanying conceptual framework are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
````