Autonomous delivery infrastructure

Code generation is solved.
Delivery isn't.

AI agents can write code — but shipping software requires spec decomposition, independent review, deployment, CI repair, and audit trails. We build the orchestration layer that governs the full pipeline.


The pipeline

A product brief goes in. A deployed, governed repo comes out.

01

Brief intake

File a product brief as a GitHub issue. Plain language, rough scope — the pipeline structures it.

02

Decompose into tasks

Planner agent breaks the brief into parallel issues with dependency ordering.

03

Agents implement

Builder agents open PRs, react to CI checks, and keep the repo moving.

04

Independent review

A separate reviewer agent inspects every PR. Identity separation — builder ≠ approver.

05

Deploy and self-heal

Merge, deploy, and if CI breaks, agents detect, diagnose, and repair autonomously.


Built with the pipeline

First client build

Aurrin Ventures Crowdfunding Platform

Calgary accelerator replacing their static site with a 12-module platform for founders to build in public and raise money. From idea to working product in 6 days — 80 agent-merged PRs across 133 issues.

80 PRs merged
133 issues
12 modules
6 days
  • Top 3 contributor to GitHub Agentic Workflows — 28 issues filed, 15 credited by name across 8 releases
  • Open source, MIT licensed — full pipeline source code. You own the repo, the pipeline, and the governance layer.

Who this is for

Founders with ideas

You have a product brief or a clear idea. You need it built and deployed — not a prototype, a real repo with CI, review, and a deploy pipeline you own.

Teams starting new projects

You have engineers but want to start agent-first. We install the pipeline in your repo, run a proof-of-concept, and hand off the governance layer.

Where the industry is heading: GitHub shipped Agentic Workflows. Vercel added Mitchell Hashimoto to the board. Factory raised $70M from Sequoia. The infrastructure layer for autonomous delivery is being built right now — and we're one of the deepest implementations running in production.