To have an AI agent, you need to build a harness first. But what exactly is an agent harness? The AI world doesn't seem to agree on a single definition for this, but this is how I've been thinking about it: an agent harness is the system that wraps around a model to turn it into an agent. This includes the orchestration loop, tool connections, memory, compute, observability, and anything else it needs. It's everything between "I have a model" and "I have a running agent." That sounds like a lot, and it can be. Teams spend days writing harness code for every agent they build using frameworks like Strands Agents SDK. But the tooling has now caught up and has made this all a lot easier. Services like the managed harness in Amazon Bedrock AgentCore lets you define your agent as configuration and it takes care of building the harness for you, taking you from idea to running agent with custom tools and capabilities in minutes.…