> For the complete documentation index, see [llms.txt](https://www.christiandussol.dev/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.christiandussol.dev/about.md).

# About

I build cloud-native solutions for Treasury & Capital Markets. This site is where I publish what I learn while doing it: the deep-dives, the experiments, the patterns that survived contact with production.

### How I got here

I've spent more than two decades in financial services technology. The last several years have been at the intersection of two domains that don't naturally meet: cloud-native and capital markets. Treasury platforms are conservative by necessity: they handle real money, real regulation, real consequences. Cloud-native engineering is fast-moving, opinionated, and assumes a tolerance for change that financial systems rarely have.

Bridging the two is the work I find most interesting. It requires holding two competing values at once: speed and stability, abstraction and accountability, innovation and audit. Most of what I write here comes from trying to live in that tension productively.

I'm Director of Engineering at Teciem, leading cloud and platform engineering. Outside that role, I serve on the KyvernoCon Europe 2026 Program Committee and contribute to the CNCF community.

### Why I write

I started writing because I wanted to make sense of what I was building. Internal documentation was never enough: it captured decisions, but not the reasoning that produced them. Writing publicly forced me to be honest about what I actually understood versus what I was just nodding along to.

What started as personal clarification became a public corpus. The CNCF Project Focus series, the Skills series, the FinOps deep-dives, they all share the same underlying question: how does this technology actually behave when you deploy it in a regulated, cost-conscious environment with real users and real constraints? That's the angle I find most absent in the cloud-native discourse, and the one I try to fill.

I write in English because that's where my technical community lives. I publish on Medium, LinkedIn, and GitHub because that's where engineers discuss this work. This site is the index: the canonical place where everything comes together.

### What guides the work

A few principles, less as slogans than as constraints I impose on myself.

**Substance over hype.** I don't write opinion pieces about technologies I haven't deployed. I don't claim "first ever" or quote fabricated statistics. If I'm uncertain about something, I say so. The cloud-native community has too much marketing dressed as engineering. I'd rather publish one careful article than ten breathless ones.

**Build before talking.** Every series I publish starts with running code, applied policies, tested artifacts. The repo on GitHub is the proof. The article is the explanation. Reverse that order and you produce theory dressed as practice, which is exactly what the field doesn't need more of.

**Discipline over speed.** I've published on a sustained cadence since September 2025. Not because volume matters, but because consistency is what compounds. A single post is a moment; a sustained corpus is a position.

**AI as amplifier, not substitute.** I work with AI tools, Claude Code primarily, but I treat AI as an amplifier of judgment, not a replacement for it. Every Skill I build, every article I publish, encodes expertise I've actually earned. Packaging knowledge you wish you had, rather than knowledge you've lived, produces confident mistakes at scale. I try not to make that mistake.

### What I'm working toward

The next decade of platform engineering won't look like the last one. The Helm charts and CI pipelines that defined the role are giving way to something different: AI agent architectures, governed Kubernetes platforms, and live composition of capabilities at runtime.

Kubernetes is being reshaped from the hardware upward to carry this. Allocation, serving, routing, and the agentic layer forming above them are converging into a single stack, one where the platform stops counting resources and starts reasoning about them. Whether that direction holds, and how fast, is still open. Mapping it, from a seat where deploying the model is the easy part and operating it under constraint is the real work, is what most of my current writing is about.

### Where to start

Navigation lives on the home page, which maps the series and the sections. If you want one recommendation instead: [**Field Notes**](/field-notes.md). The deep-dives prove what I know. Field Notes shows how I decide, including the times I got it wrong, and that is the faster way to work out whether we think alike.

If any of this resonates, if you're building at the same intersection, or thinking about it, I'd be glad to hear from you.

***

*Reach me on* [*LinkedIn*](https://linkedin.com/in/christiandussol) *or through the* [*GitHub repos*](https://github.com/christian-dussol-cloud-native) *linked across this site.*