Building an AI agent that edits images based on natural language requires an orchestration loop, tool routing, memory management, and a compute environment to run it all. Amazon Bedrock AgentCore harness handles that entire stack with configuration. You declare what the agent does, and the harness runs it in a stateful, isolated microVM with built-in memory, tool routing, and observability.

This post walks through building a serverless image editor where users upload a photo, describe an edit in plain English, and receive the result in seconds. The agent runs on AgentCore harness without custom orchestration code. We deploy the full solution, including authentication, encrypted storage, three image editing tools, and a React frontend, with a single deployment command. The infrastructure is defined using AWS Cloud Development Kit (AWS CDK).

Image editing application

The application accepts prompts like “change the car color to blue” or “extend the image 200 pixels to the right.” An agent powered by Claude Sonnet 4.6 breaks the requirement into a series of steps and orchestrates the tool calling, each associated with a different Stability AI model. Then it executes the edit, applies a watermark using a shell command on the microVM (no token cost), and returns the result.