The challenge
After several years building a device-management platform, a connected-device software company decided on a major pivot: a new embedded Linux operating system for device makers. The platform behind it had to change too, and the team needed a clear path from the old platform to the new one. It also had to run in three places: on each developer’s laptop, in AWS, and inside customers’ own air-gapped facilities with no connection to the cloud.
What we built
We designed one platform that runs the same way everywhere. Developers get a local copy that matches the AWS cloud environment, so what works on a laptop works in production. On-prem customers get an edition that runs on Kubernetes (K8s or K3s) inside air-gapped networks, managed without reaching the internet.
We scaffolded the initial infrastructure and platform as code, with reproducible environments and a one-command local setup, so every environment is built from the same definitions.
Then we put the guardrails in place that make AI-assisted development safe: agent instruction files that encode the project’s conventions, architecture docs and task specs that the team and its AI agents work from, and test suites and CI gates that block any change that doesn’t pass.
Finally, we walked the team through the new project and how to work in it AI-first, so they had a running start rather than a blank repository.
Scope
- Infrastructure and platform scaffolding as code
- Local developer environment matching AWS
- Air-gapped on-prem edition on K8s and K3s
- Agent instruction files and project conventions
- Test suites and CI gates as guardrails
- Architecture docs, task specs and team onboarding
The result
With the guardrails in place, the client’s own team finished the platform overhaul in under two weeks. The new platform runs in production on AWS and air-gapped on customer premises, and every developer runs the same stack locally.
