The Workshop.
Notes on browser automation, local AI and building in public.
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Local AIWhy vector search misses exact terms, and what hybrid search fixed (measured)
Ask a vector search for ERR_4521 and you may get ERR_4512. How we added BM25 next to vectors with reciprocal-rank fusion in an in-browser knowledge base, what we measured, a SurrealDB full-text gotcha, and a filtering bug that gave small collections zero hits.
ProductWorkflows that survive a closed tab: durable waits with checkpoints and chrome.alarms
How a browser-extension workflow can pause for up to 30 days, survive a closed tab, a browser restart or an extension update, and resume where it stopped: checkpoints in storage, wake-ups owned by chrome.alarms.
ProductYour browser is quietly an operating system: the 4 WebAssembly engines in our extension
One Chrome extension, no backend for its core features: a real database, two AI inference engines and a full Python interpreter, all running as WebAssembly. What each engine does, how it's wired, and what it costs.
ProductYour context window is a budget, not a bucket
Most context-window bugs come from one assumption: the prompt is the chat history, so cut the oldest messages. In an agent, history is often the smallest part. Seven rules for budgeting a prompt, from a 128k cloud model down to a 2,048-token model in the browser.
Local AIAWFlow wants to be the OpenRouter for AI that runs in your browser
Three incompatible browser AI engines, a different model format each. AWFlow sits in front of all three so you choose a job, not a library. Where we are and why the web will get there.
TutorialsHow to use free AI inside AWFlow: Agents, Chat and Automation without an API key
Install a local AI model once and it powers everything in AWFlow: the chat assistant, your agents and your automation workflows. A practical walkthrough, step by step.
Local AIDo you need a big AI model? A one-hour test that tells you
The biggest model is a habit, not a requirement. How to tell which of your automation jobs a small, free, on-device model can handle, with a simple test on your own inputs that takes about an hour.
Local AIFree AI vs API-key AI: what an automation really costs
How to estimate an AI step's cost before you build it, why the page you feed in is usually the bill, and a simple design that sends only the hard work to a paid model. With a calculator for your own numbers.
TutorialsHow to pick a local AI model your laptop can actually run
One number decides whether an AI model runs on your laptop: the memory it needs. How to read model names like q4f16_1, why every fit label is an estimate, and how to install, test and keep a model, step by step.
ProductLangChain and LangGraph in the browser: how an AI agent builds your workflow
An agent is not one big prompt. It is a graph of steps with branches, loops and a memory of where it paused. Here is how that works, with the real graph behind AWFlow's assistant.
ProductThe 5-tab problem: let your browser do the copy-paste
One small job, five tabs: a competitor's price, a second shop, a spreadsheet, a chat assistant and your inbox. Here is why that adds up, and how one workflow in your browser does it for you.
Local AIThe airplane-mode test: the only privacy proof for AI you can run yourself
Every AI tool says it respects your privacy. One test settles it: switch off the internet and see if it still works. What offline AI really requires, how a workflow can fail the test, and how to run it in five minutes.
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