Learn how Stripe's engineering team turns a simple Slack message into a complete pull request using AI agents. This workflow automates environment setup, coding, and testing, triggered by a simple emoji reaction, dramatically reducing the friction to start new development work.
Open-source AI agent by Block for automating tasks
Start by describing a task or an idea for a code change as a regular message in a Slack channel. This message will serve as the initial prompt for the AI agent.
I have this cool idea for docs at stripe.com/payment/machine. This is our new machine to machine payment work, which we'll look at later in our call. Um, and I want to make sure the landing page really sticks and gives a good code. Example of how to get started quickly.Add a specific, pre-configured emoji reaction to the Slack message to activate the AI agent. The emoji name can specify which repository the agent should work in, for example, :create-minion-payserver:.
Once triggered, the system automatically spins up a fully-configured, isolated cloud development environment. This includes checking out a new git branch, setting up databases, and installing necessary tools like a VS Code server.
The AI agent, using a harness like Goose, takes the original Slack message as its core prompt. It then enters a loop to solve the task: searching the codebase, identifying files, modifying the code, running tests, and committing the changes.
After completing its task, the agent creates a pull request for human review. Engineers can then review the AI-generated code, approve it, and merge it, shifting their focus from writing boilerplate code to high-level review.
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