I am a software engineer with 20 years building and operating distributed systems, platforms, and cloud infrastructure at scale. I am currently building GPU infrastructure and AI workload orchestration for private clouds, and integrating agentic AI into our own engineering workflows.

A significant part of my career involved working with engineering leaders and executives on technology strategy and build vs. buy decisions, then leading engineering teams through implementation and operations. Below are some writings from both perspectives.

If you're facing a strategic engineering decision, most of the advice you're getting comes from someone with a stake in the answer. Mine doesn't. If you want an outside perspective from an operator who has been on the other side, reach out.

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Latest

DDoSing Software Delivery Pipelines

June 13, 2026

The real issue wasn’t having a bottleneck. It was pretending that there wasn’t one, treating back-pressure signals as a nuisance, and letting an AI-induced productivity anxiety run unchecked.

Highlights

AI-generated code will choke delivery pipelines

Everyone is measuring what AI does to code production. Nobody is measuring what it does to everything downstream: build, test, review, deploy, operate. The DORA data is already showing the strain.

Talk write-up: "How to build a PaaS for 1500 engineers"

The technical and organisational decisions behind building a Kubernetes-based platform serving 1500 engineers across Adevinta's marketplace portfolio.

Kubernetes made my latency 10x higher

Every time someone reports higher latency after migrating to Kubernetes, the root cause is an assumption that changed. This is one of those stories.

All writing