Max Drake is a product engineer at tldraw, building interfaces for drawing, animation and agents that work on a canvas. Drake’s work includes the spatial harness for canvas agents and tldraw flash, developed with Audrey Leo and Leo Knudsen.[1][2][3]
Start with How we built a spatial harness for agents on the canvas →
Career
Drake studied mechanical engineering at MIT, earning a bachelor’s degree, and previously worked at Fermat across product research, design and engineering. Work during the MIT period included the Tangible Media Group, the Self-Assembly Lab, propelland and Mercedes Benz R&D. At tldraw, Drake combines product engineering with experiments in how people and agents can share a visual workspace.[1][5]
Contributions
Give agents a place to look and act
Drake’s spatial-harness article traces a series of tldraw experiments. The system supplies screenshots and structured shape data, provides canvas-editing operations and lets agents move their own viewport to inspect more of the document. Later iterations retrieve context when needed and allow code to manipulate the editor. A canvas linting system can warn about problems such as overlapping text shapes.[2]
Record an animation by performing it
Drake coauthored and helped build tldraw flash with Audrey Leo and Leo Knudsen. Users draw a scene and record movements by dragging objects. The tool records other canvas changes as well, including drawing and text edits. Existing shapes can be repositioned after recording, and customizable characters retain their underlying motion. The project builds on tldraw’s SDK mechanics to make short animations directly on the canvas.[3]
Ideas
In the conference talk, Drake demonstrates fairies, recognizable agent characters that share a canvas and delegate work. Their appearance distinguishes one agent from another, while animation communicates whether they are active or waiting. A later prototype places coding-agent tasks in a dependency graph, connecting an overview of work with actions outside the drawing environment. The examples explore interface behavior and coordination rather than establish that every generated result is correct.[4]
Tools, writing & talks
Writing, research & talks
Start here
Drake’s account of the representations, actions and feedback used by canvas agents.
Begin with the mouse-and-candle example before the later agent loop. It explains how a canvas becomes model input and executable edits; using the starter kit requires JavaScript development tools and a supported model-provider key.
Author and product engineer[2]tldraw's product engineer traces the progression from getting a model to read a canvas (screenshot plus shape JSON) to an MIT-licensed agent starter kit and 'fairies,' agents rendered as visible characters so multi-agent state can be read at a glance.
Catalog workOriginal sourceA demonstration of canvas perception, visible agents and spatial task coordination.
Speaker[4]- Introducing tldraw flashtldraw.dev
Introduces the team’s performance-based animation tool and its canvas workflow.
Coauthor and developer[3]