Practical, code-first walkthroughs on browser automation, test reliability, and local AI, written by the team behind LumaBrowser. No fluff; every guide ends with something working on your machine.
The beginner path: which of three kinds of machine you have, what to honestly expect from a local model, the one-click setup that picks the model for you, and the five problems everyone hits with their fixes.
Read the guide →A fair side-by-side of the four names that come up when someone asks how to run AI on their own computer: who each is for, what the first fifteen minutes look like, and what is included beyond chat.
Read the guide →Why selectors rot on modern frontends, the locator hierarchy that survives redesigns, proper waits, and how an LLM fallback keeps suites green when class names change anyway.
Read the guide →Drive a real browser from n8n's built-in HTTP Request node: open pages, extract data, fill forms, and trigger workflows from page changes, all without a metered cloud browser.
Read the guide →What actually fits in your RAM and VRAM, what GGUF quantizations mean, the trade-offs between the popular local runtimes, and the one-click path if you'd rather skip all of it.
Read the guide →Three strategies for scrapers that survive redesigns: intercepting the site's own API, writing selectors that age well, and letting an LLM resolve the element when they break anyway.
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