What Does an AI Agent Need to Remember?

Thu, 03 Sep 2026 17:02:58 +0000

TL;DR: We use “memory” as a catch-all, but an AI agent needs different information for different jobs. Context gives the model what it needs for the current decision. Memory brings useful information forward. State tells the application what is true and where the work stands. Understanding those roles matters more as the agent capabilities grow and work stretches across model calls, tool calls, waits on humans and failures. The separation is a tool for clarity. You could call all of it memory; the point is that each piece needs to be handled differently, and handling them well is what makes the agent more capable.

Durable, flexible multi-agent systems

Thu, 06 Aug 2026 00:00:00 +0000

An agent system is a distributed system. You get to choose the framework and how much durability and human oversight the case demands; the tradeoffs are the part you don’t get to avoid.

For the last few months, I’ve been building one system to make that concrete: the same multi-agent fleet on Google ADK, on LangGraph, and on both at once, with Temporal as a layer underneath.

Where this started

Ziggy’s is the playful imaginary ice cream shop I cooked up to show what it looks like when a multi-agent system handles fleet delivery around Las Vegas. We announced our ADK integration and wanted a demo for Google Cloud Next. The first version showed a multi-agent team assigning deliveries and dealing with an agent or driver disconnecting mid-route. For the AI Engineer World’s Fair, the fleet relocated to San Francisco, picked up LangGraph as a second framework, and got reframed around a harder version of “recover from a disconnect”: keeping a human in the loop. Disconnecting an agent is a machine failing. Waiting on a human is a machine succeeding at doing nothing, correctly, for as long as it takes. A human isn’t a function that returns in 200 milliseconds. They answer in minutes, hours, or after you’ve already redeployed twice.

Temporal on Nyghtowl

What Does an AI Agent Need to Remember?

Durable, flexible multi-agent systems

Where this started