The Charity in the Machine
The future of AI was supposed to be decided by models and chips. In Oakland, it is being tested by something older: a charitable promise.
The future of AI was supposed to be decided by models and chips. In Oakland, it is being tested by something older: a charitable promise.
The strangest AI story of May was not a model release. It was a rival's supercomputer becoming Claude infrastructure.
A mystery model appeared on OpenRouter and fooled the entire AI community. It turned out to be from a phone company. This is the story of how Xiaomi entered the frontier AI race — and why it matters more than the benchmarks suggest.
I went to Shenzhen to see how they were catching up. I found out they weren't catching up at all.
Anthropic tightened subscription rules around agentic harnesses. OpenAI pushed heavier Codex use toward higher tiers and credits. What changes when workflow-scale AI stops fitting inside a flat monthly plan.
Anthropic's most powerful model was leaked, then unveiled in a cybersecurity coalition with Apple, Microsoft, and Google. A data engineer's analysis of what Claude Mythos means for infrastructure security.
By the end of 2026, 40% of business workflows are expected to use autonomous agents. For data engineers, this isn't hype—it's a fundamental shift in how pipelines are built, monitored, and maintained. Here's how to separate the genuine opportunities from the dangerous assumptions.
Version 1 announces 250 AI jobs while entry-level tech workers face displacement. A Dublin data engineer's analysis of Ireland's bifurcated AI job market and what it means for career planning in 2026.
Navigating data sovereignty requirements under GDPR, the EU Data Act, and the AI Act. A practical framework for data engineers building compliant AI infrastructure in Europe.
Anthropic's Claude Opus 4.5 and OpenAI's GPT-5.4 are reshaping the enterprise AI landscape. A data engineer's perspective on which model fits which workflow, from code generation to pipeline orchestration.
The streaming landscape is evolving beyond pub/sub. With Flink CDC 3.6.0, diskless Kafka alternatives, and AI context engines emerging, data engineers need a new mental model for real-time data architecture.
After years of AI experiments and pilots, 2026 demands production-ready systems. A personal journey from AI experimentation to pragmatic deployment, and what it means for data engineering practice.