Builders use the Canvas Builders Program to move from a rough agent concept to something people can actually use within two weeks. You start by turning your idea into a concrete job the agent must do, defining inputs, outputs, and success checks so you can test quickly instead of debating scope. From there, you choose an implementation path that matches the task—retrieval for knowledge-heavy agents, tool calls for actions, or multi-step flows when the work needs planning—and wire up the minimum set of components to get a first version running.
During the sprint, you build in short cycles: implement a small slice, deploy it on Canvas, run it with real users, then revise based on what breaks or confuses them. Live build hours and mentor feedback are used to unblock decisions, review prompts and tools, and close the gap between a nice demo and a reliable production behavior. Typical work includes setting up data sources, adding guardrails, handling errors, logging key events, and tightening the agent’s responses so outcomes are consistent.
Teams often use the program to ship internal helpers like support triage agents, research assistants, onboarding copilots, and workflow automations that connect to existing systems. By the end, you have a deployed agent, a simple process for collecting feedback and measuring usage, and a routine for iterating after launch. After graduating, recordings, templates, a private Slack, and monthly office hours support continued maintenance and upgrades.
AI Agent Build Credits
$50
One-time payment for equivalent credits to cover your AI agent build cost during the sprint.
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