Tags

Machine learning systems and the engineering around them.

Large language models, prompting, agents and evaluation.

Threat models, hardening and secure defaults.

Delivery pipelines, infrastructure and operations.

The browser platform, standards and web performance.

CPUs, memory hierarchies and the low-level performance behind them.

APIs, services and the data layer behind them.

Metrics, traces, logs and everything they cost.

Storage engines, pipelines and query performance.

UI architecture, rendering strategies and tooling.

Measuring traffic, and what the measurements actually mean.

The Python ecosystem.

Container images and runtimes.

The OpenTelemetry standard, SDKs and Collector.

The Go language and its ecosystem.

TypeScript and the JavaScript runtime it compiles to.

PostgreSQL internals and operations.

Prometheus, PromQL and its storage engine.

Long-form analysis of how something actually works.

System design, trade-offs and failure modes.

Measured comparisons with reproducible numbers.

Step-by-step, follow-along walkthroughs.

Making systems cheaper without making them worse.