Richardson Cloud, Rebuilt: Faster, Cheaper, AI-Driven
The blog moved off WordPress to a static site on Azure Static Web Apps — and I rebuilt it the way I think we should all be building now: with AI-driven DevOps.
Welcome back. Richardson Cloud has a new home — and a new way of being built.
For the last few years this blog ran on WordPress, which meant an App Service plan and a MySQL database quietly billing every month for a site that is, at its core, a collection of articles. That’s a lot of moving parts (and cost) for static content.
So it has been rebuilt as a static site on Azure Static Web Apps. The result:
- Negligible hosting cost — the Free tier covers a blog comfortably.
- Faster pages — pre-rendered HTML with no server round-trip.
- Same analytics discipline — lightweight, first-party page metrics captured to Azure Table Storage, plus Google Search Console for the search side.
That’s the what. The part I actually care about is the how.
Built the way I think we should build now
I didn’t just move the content — I rebuilt the delivery pipeline to practice what I preach about AI-driven DevOps. This site is a small, honest proving ground for the same processes I want my teams running at scale:
- Everything is code. The infrastructure is defined in Bicep, the site in a typed content model, the pipeline in a single workflow. Nothing important lives in a portal where it can’t be reviewed.
- Tokenless, automated delivery. Push to a branch and GitHub Actions runs
infra → build → deploy → test, authenticating to Azure with OIDC — no secrets sitting in a vault waiting to leak. Infra only re-deploys when infra actually changed. - AI in the loop, not just in the copy. I built this with AI as a pair — scaffolding, reviewing, and hardening the pipeline — and the same assistant can now draft, edit, and ship articles against a style guide. That’s the real unlock: AI compressing the boring parts of the loop so the judgment calls get more of my attention, not less.
None of that is exotic. It’s IaC, CI/CD, and a little AI leverage — the point is that it’s consistent and repeatable, from a one-person blog up to an enterprise platform. Cloud is a model, not a place; DevOps is a discipline, not a tool; and AI is most useful when it’s wired into how you already ship.
What’s next
More writing, and more of it — practical, opinionated pieces on Azure architecture, AI development and governance, AI-driven DevOps, and building the teams that ship. Same honest take you’ve come to expect, published on a cadence again.
How are you wiring AI into your delivery pipeline — or are you still deciding where it earns its place? I’d love to hear it. More soon.