Fixed-length chunking requires no external services, yet semantic chunking absolutely needs an Embedding API — why? The core idea of semantic chunking is to split text at semantic boundaries. Determining whether "two pieces of text belong to the same topic" requires converting text into vectors and computing similarity — that's exactly what the Embedding API does. Dimension Fixed-Length / Recur
Testing Firefox Extensions with Playwright: End-to-End Testing Guide Extension testing is one of those things everyone knows they should do but few actually do. I've been using Playwright for end-to-end tests on the Weather & Clock Dashboard extension and it's changed how I think about extension quality. Unit tests don't cover the biggest failure modes: Does the extension actually load in Firefo
Why I built another Ruby test runner inspired by Playwright Test Ruby already has great testing tools. If you are building Rails applications today, you probably use one of these combinations: RSpec + Capybara Minitest + Capybara Rails system tests Maybe Selenium, Cuprite, Ferrum, or Playwright through Ruby bindings These tools are mature, battle-tested, and widely used. So the natural question
I wanted to test my web app. That's it. A Next.js portfolio and a SaaS chat — run some accessibility checks, catch console errors, verify nothing's broken on mobile. The kind of thing you do before pushing to production. I opened Claude Code, connected Playwright MCP, typed "test the app" and watched it burn through tokens like there was no tomorrow. Then /compact fired at 18% text context. Then I
Why Does Switching Embedding Models Make Such a Huge Difference? In the first four articles, we built the RAG pipeline, tuned parameters, and mastered chunking strategies. But there's one question we haven't dived into: After your documents are chunked, how do they become vectors? This process is called Embedding. It transforms human-readable text into machine-computable vectors. The choice of E