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NirDiamant Organizes 30 LLM Agent Memory Techniques in Runnable Jupyter Notebooks

September 2, 2026 at 01:32 EDT

AI Agents
Open Source

NirDiamant's Agent_Memory_Techniques repository brings together 30 runnable Jupyter notebooks that show how LLM agents can retain, retrieve, organize, and evaluate information over time. The collection is designed as a hands-on map of agent memory patterns, from basic conversation buffers to framework integrations and production considerations.

2026 · NIRDIAMANT

30 techniques for agent memory

A runnable notebook collection moves from conversation buffers to long-term retrieval, framework integrations, evaluation, and production patterns.

The cookbook at a glance

runnable techniques

memory families

framework tracks

evaluation and production

How the 30 techniques are distributed

Each vertical stack represents one technique count within a family.

Short-term
5

Long-term
6

Cognitive
8

Retrieval
4

Frameworks
4

Eval + production
3

A learning path through the stack

Start simple
Buffers and summaries

→

Add structure
Stores, graphs, and recall

→

Measure
Evaluation and benchmarks

→

Adapt
Production patterns

Breadth with clear boundaries

Breadth

One collection covers context management, persistent recall, multiple frameworks, evaluation, and deployment patterns.

Limit

The project is educational rather than production-ready; deployment still needs engineering for cost, privacy, isolation, and reliability.

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