Help shape how teams verify what code changes actually did.

We're looking for teams who:

• ship production code quickly
• are feeling the pressure of AI-assisted development or high PR volume
• care about what code actually does, not just what changed line by line
• want to reduce uncertainty around trust, exposure, and dependency risk
• are willing to give direct product feedback

Shoulder helps teams answer questions like:

• Did a private route become public?
• Did authentication disappear?
• Did untrusted input reach a shell, database, or eval?
• Did a dependency introduce install-time or runtime risk?
• Did this change increase our attack surface?

This is not another security dashboard. It is a decision system for understanding code changes and dependency behavior before they become incidents.

What design partners get

• Direct access to the Shoulder team
• A fast feedback loop with product and engineering
• Early access to new capabilities
• Help applying Shoulder to your real repos and workflows
• Influence over how the product evolves

What we ask for

• Honest feedback
• Real workflow context
• Occasional time with your engineering or security leads
• Willingness to test early product changes
• Permission to learn from your use cases

We're not looking for volume. We're looking for a few strong partners with real problems.

Same founder. Same pattern. Different problem.

Before Shoulder, we built Katacoda, the interactive learning platform adopted by Red Hat, HashiCorp, Datadog, and Kubernetes, and acquired by O'Reilly Media.

Katacoda worked because it removed friction from learning by doing.

Shoulder applies the same pattern to a new problem: removing uncertainty from code changes.

Best fit right now

• Platform teams
• Application security teams
• Engineering orgs using AI coding tools
• Companies with active CI/CD and frequent deploys
• Teams that review a lot of pull requests and dependencies