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LLMs learned JavaScript from a web that never deletes anything. Now they generate 2013’s best practices at scale, publish them back onto the web, and the next model learns from that. The graveyard has a feedback loop.

Prestige can outlive the state that produced it. 1204 was not just a medieval atrocity — it was the receipt for a much larger transaction.

The moment you automate your home, everyone who lives in it becomes a user of a system they never agreed to. Here’s how to design for people who didn’t consent to being users.

Context isn’t what you paste into the prompt. It’s what the model sees, prioritizes, and is constrained by. That’s not prompting — that’s system design.

LLMs don’t ship software. They ship text. You ship software by constraining the problem until text reliably becomes change sets you can trust.

The bottleneck was never intelligence. It was instrumentation. Once we learn to define what systems should do, the execution becomes trivial.

Large Language Models are best described as GAC — Glorified Auto-Complete. If Google Search Suggest was the ape, LLMs are the upright-walking hominid.

Released imgc v0.1.0 - a cross-platform file processor with extensible plugin architecture. Built primarily for automatic image compression but designed to handle any file type through custom plugins.

“It depends” is not indecision, it reflects the core truth that every architectural decision involves trade-offs. Aim of this post is to show familiarize you with techniques like ATAM and decision matrices to make context-aware, defensible architecture choices.

Discover how to integrate ‘architecture as code’ using Structurizr and Architecture Decision Records (ADRs) to maintain version-controlled, living documentation for cloud and microservices architectures.