Assign a Story. Wake Up to Merged PRs. No Developer Required for Boilerplate.
While your team sleeps, WalnutAI's Cloud Agent is clearing the backlog — reading stories, understanding your codebase, writing code, and opening pull requests autonomously. Ship faster without burning out your engineers.
Trusted by engineering teams shipping faster with AI
Of sprint work is predictable boilerplate the Cloud Agent handles autonomously
Faster time from story assignment to open pull request
More stories shipped per sprint without adding headcount
Ship more in every sprint without burning out your engineers
Industry research consistently shows that 80% of development work in a typical sprint — CRUD operations, API endpoints, form handlers, configuration updates — follows predictable patterns that require no architectural creativity. WalnutAI's Cloud Agent takes full ownership of this layer, so your engineers spend their time on the 20% that actually requires human judgment.
Run multiple agents in parallel across a sprint
Each agent has its own task queue and compute profile. Assign stories to multiple agents simultaneously and let the entire sprint’s boilerplate get implemented overnight — while your developers focus on architecture and complex logic.
Watch the agent work in real time
A live terminal streams the agent’s output via WebSocket as it runs — showing every tool call, file read, and decision in real time. Check the completion card when it’s done for a full summary of files changed, PR link, elapsed time, and token cost.
Reads your codebase before writing a single line of code
The Cloud Agent doesn’t generate code in a vacuum. It first maps your entire repository — folder structure, module boundaries, existing conventions, and framework patterns — so every implementation fits naturally into what you’ve already built.
Implements features end-to-end, not just snippets
From creating new files to modifying existing ones across multiple directories, the agent handles the full scope of a feature implementation. It follows your codebase’s patterns, runs existing tests to verify nothing is broken, and only commits once the work is complete.
Opens a draft PR on your Git platform automatically
Once implementation is done, the agent creates a feature branch (walnut-ai/[story-slug]), pushes it, and opens a draft pull request on GitHub, GitLab, Bitbucket, or Azure DevOps — with an auto-generated description covering the story, files changed, and acceptance criteria.
Responds to reviewer comments without developer involvement
When reviewers leave comments on an AI-generated PR, WalnutAI picks them up via webhook and re-runs the agent with the full feedback. A fix commit is pushed to the same branch automatically — no developer hand-off needed for standard review iterations.
Ready to ship with confidence?
See how WalnutAI connects requirements, code, testing, and deployment into one intelligent workflow.