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Shared Persistent Memory

When multiple agents work over days, chat context isn't enough. You need external memory: task state, decisions, retrievable documents, and a way to forget what's no longer useful.

  • Separate working memory, vector memory, and human wiki.
  • Prevent multiple agents from writing contradictory facts.
  • Design decay, permissions, and traces for shared memory.
Terminal
memory_layers:
  hot:
    storage: "task_board"
    content: "current state, blockers, owner"
  warm:
    storage: "qdrant"
    content: "decisions, summarized conversations, documents"
  cold:
    storage: "obsidian"
    content: "reviewed wiki, sources, and stable rules"
  rules:
    write_requires_source: true
    conflicting_fact: "create_review_task"
    decay_days: 30

What to Store

  • Decisions made and the rationale.
  • Repeated errors and the applied fix.
  • Explicit user preferences.
  • Task state and handoffs.
  • Stable sources with dates.
Terminal
memory_event:
  type: "decision"
  scope: "project:aulafy"
  fact: "Lessons must cite official sources when covering live tools."
  source: "editorial_policy"
  confidence: 0.95
  expires_at: null
  writer_agent: "planner"

Official Sources

  • LangGraph Persistence
  • Qdrant documentation
  • Obsidian Flavored Markdown
  • Hermes Agent documentation
Complete Aulafy mapSee how this lesson fits without leaving your path.

Complete Aulafy map

How all courses connect

This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.

  1. 1Understand
  2. 2Apply or build
  3. 3Operate with confidence
01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

Build with code

Prepare your environment, work with coding agents, and run models while keeping control of your projects.

This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

You do not need every course: choose the component your system needs and return as it grows.

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