Applications and more...

I built MathQuizPrep as a free study tool for my daughter’s math competition prep. Once it existed, one question came up naturally: could this app also earn a little money, without being unfair to the audience, since the users are 10-15 years old? I did not want to research marketing, EU law about minors, SEO, and UI design all by myself. So instead of doing that research alone, I defined a small team of AI specialists and asked them to do it for me, with one of them working as a manager for the other four. Building the team: by prompting, not by writing the files myself Each “team member” is a Markdown file inside .claude/agents/ — a persona with a name, a short job description with a fixed list of tools it is allowed to use. Each agent also got information about which model it should use — the more complex ones (like the manager) got more capable models. I did not write any of these files by hand. I described the team in plain English, and Claude wrote and improved them over a shor...

  A lot of real-world problems boil down to the same shape: some scattered, unstructured source material exists (PDFs, archives, scanned documents), and what you actually need is a structured, usable product on the other end — categorized, searchable, and packaged for a specific audience. That transformation used to mean writing a pipeline by hand: a parser here, a classification script there, a templating layer to render the final output. With an LLM as a development partner, the same pipeline can be built through conversation — research, extraction, categorization, content generation and packaging, each step still a real, inspectable script or file, but designed and iterated on in natural language rather than written line by line. The part that changed the most for me wasn’t the coding — it was the analysis phase. Reading five years of exam PDFs, working out the syllabus scope, and deciding how to categorize dozens of tasks by topic and difficulty is the kind of manual review tha...

A scraper usually breaks the moment a website redesigns its layout. This one doesn't — it researches the page itself, and re-researches it when something changes  This article walks through building exactly that, with Claude Code. The business need Let's imagine a situation where parents have three kids in three different schools. None of the schools agree on how to publish a timetable. The formats are different: one puts up clean, per-class HTML pages. Another exports its entire grade level as a single PDF. What the parents want is one combined, printable schedule covering all three kids. Writing an HTML scraper for the first school and a PDF scraper for the second is an afternoon's work. What is more, the timetable structures may change in time. The process The solution I landed on with Claude Code was a self-correcting process based on LLM agents. There are two agents involved. The first, a research agent , studies a school's site and writes plain-English ins...