This site has had an llms.txt file since 2026-08-29. I've written about it twice already: once about the first version being robots.txt with a different filename, and once about AEO and GEO making the same mistake at industry scale.
On August 11, Anthropic started adding a machine-readable watermark to Claude's text output, everywhere, not just for EU users. It's compliance with Article 50(2) of the EU AI Act, which requires providers of synthetic content to mark it as machine-generated, and Anthropic signed the EU's Voluntary Code of Practice covering exactly this.
I'd deliberately deleted three unused modules from this site's codebase — old, disabled, doing nothing. A few minutes later, mid-conversation with the agent I was working with on an unrelated task, one of them reappeared on disk. Not because I'd changed my mind.
Artificial Intelligence has rapidly become one of the most important technologies of the modern era. Governments, businesses, universities, journalists, software developers, and ordinary citizens increasingly depend on AI systems for research, content creation, software development, decision making, and communication.
For years, convenience has been the driving force behind the modern internet. Cloud services became easier than running servers yourself, social media replaced independent websites, and smartphones turned into centralized gateways for communication, banking, entertainment, and work. Most people accepted this tradeoff without thinking too deeply about the long-term consequences.
In a previous article I covered getting GPTel running with LM Studio and a local Qwen model — a great setup when privacy and offline access matter. But the Emacs AI ecosystem has grown considerably, and there is now a whole family of packages targeting different parts of a coding workflow.
I recently spent an afternoon building an enterprise CRM from scratch using Claude Code — Anthropic's A I coding assistant that runs directly in your terminal. The stack: Symfony 7 on the backend with API Platform, React 18 with TypeScript on the frontend, PostgreSQL, and Docker Compose to tie it all together. Here's what I actually learned.
As artificial intelligence produces more and more online content, it’s becoming harder to tell what’s written by humans and what’s generated by machines. It’s convenient and efficient — but it also comes with a serious risk: the gradual loss of quality, depth, and diversity across the web.
Artificial Intelligence has become an integral part of the modern developer's workflow — from code suggestions to natural language search and data enrichment. But most of these tools come at a cost: constant internet connections, cloud-based APIs, and corporate monitoring of every token you generate.
Aider is a lightweight AI pair-programming assistant that runs in your terminal and edits your code in place. Running it in Docker keeps your environment clean and makes it easy to switch between models. This guide shows how to run Aider with: