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Home/Agents
Agents

Scaling AI Agents with Redis Iris

Cole Medin·July 9, 2026·high confidence

Why it matters

  • →Redis Iris provides a scalable solution for AI agent memory management.
  • →Context Retriever and Agent Memory enable real-time data handling and multi-user access.
  • →This approach transforms static memory into a dynamic context layer, enhancing AI agent capabilities.
Scaling AI Agents with Redis Iris
©Cole Medin

Cole Medin discusses the challenges of scaling AI agents that use markdown files for memory, highlighting the limitations when these agents are deployed to multiple users. He introduces Redis Iris as a solution, focusing on its Context Retriever and Agent Memory features to handle real-time data and multi-user environments. This approach allows AI agents to scale effectively, supporting thousands of conversations and providing a robust architecture for production systems. Medin's work with Redis Iris represents a significant advancement in AI agent scalability and deployment.

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The story around this

Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.

Key Requirements for Production-Ready AI Agents — Sam Witteveen1Together AI's Inference Engine Outperforms Competitors — Together AI Blog2Scalable Enterprise AI Hinges on Agent Logic — Hugging Face Blog3Google Unveils Agentic RAG for Complex Queries — Google Research Blog4Persistent Memory Enhances AI Agent Performance — Lev Selector5OpenAI Paper Explores AI Agents in Work Transformation — OpenAI6MIT and Microsoft Enhance AI Workflow Efficiency — MIT News AI7Memora Enhances AI Memory for Long-Horizon Tasks — Microsoft Research8Scaling AI Agents with Redis IrisIntel Explores Agentic AI for Enterprise Workflows — MIT Technology Review AI9Grok Bot Simplifies AI Agent Adoption — The AI Daily Brief10Scaling AI Second Brains to Teams with Row-Level Security — Cole Medin11Jev: A Decision-Only AI Model for Agents — Cole Medin12Liquid AI releases efficient on-device agent model — Hugging Face Blog13Apr 15You are hereOct 13

How we got here

  1. 1
    Key Requirements for Production-Ready AI Agents

    Sam Witteveen · April 15, 2026 · Related

  2. 2
    Together AI's Inference Engine Outperforms Competitors

    Together AI Blog · May 19, 2026 · Related

  3. 3
    Scalable Enterprise AI Hinges on Agent Logic

    Hugging Face Blog · June 1, 2026 · Related

  4. 4
    Google Unveils Agentic RAG for Complex Queries

    Google Research Blog · June 5, 2026 · Related

  5. 5
    Persistent Memory Enhances AI Agent Performance

    Lev Selector · June 12, 2026 · Related

  6. 6
    OpenAI Paper Explores AI Agents in Work Transformation

    OpenAI · June 25, 2026 · Related

  7. 7
    MIT and Microsoft Enhance AI Workflow Efficiency

    MIT News AI · June 25, 2026 · Related

  8. 8
    Memora Enhances AI Memory for Long-Horizon Tasks

    Microsoft Research · June 29, 2026 · Related

What happened next

  1. 9
    Intel Explores Agentic AI for Enterprise Workflows

    MIT Technology Review AI · July 27, 2026 · Related

  2. 10
    Grok Bot Simplifies AI Agent Adoption

    The AI Daily Brief · August 13, 2026 · Related

  3. 11
    Scaling AI Second Brains to Teams with Row-Level Security

    Cole Medin · September 17, 2026 · Related

  4. 12
    Jev: A Decision-Only AI Model for Agents

    Cole Medin · September 21, 2026 · Related

  5. 13
    Liquid AI releases efficient on-device agent model

    Hugging Face Blog · October 13, 2026 · Related

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