interception

This is a very quick post. I had an idea as I was walking the dog this evening, and I wanted to build a functioning demo and write about it within a couple of hours. While the post and idea started this evening, the genesis of the idea has been brewing for a while and goes back over a year to August 2024, when I wrote about being sucked into a virtual internet. WebSim has been on my mind for a while, because I loved the idea of being able to simulate my own version of the web using the browser directly and not via another web page. And a couple of weeks ago, I managed to work out how to get Puppeteer to intercept requests and respond with content generated via an LLM.

Introducing the OpenMemory Chrome Extension

AI memory Chrome extension for LLM memory and retrieval augmented generation. OpenMemory enables persistent AI agent memory across web browsing sessions.

mozilla-ai/any-llm

Communicate with an LLM provider using a single interface

elements

As much as I struggle with on-device processing and the quality of its output compared to server models, I am excited by some of the APIs that are being built into browsers that are backed by LLMs and other AI inference models. For example, the prompt API, along with a multi-modal version that can take any arbitrary combination of text, image, and audio and run prompts against them. These APIs are neat but not yet web-exposed and many developers struggle to know what to do with a generic prompt. It’s not a solution that is natural to many people yet.

[FOSDEM] Browser and Web Platform Devroom at FOSDEM 2026: Call for Participation

Stop Ignoring the Browser: The Biggest Frontend Shift in a Decade

Native browser APIs now provide powerful alternatives for routing, state management, and components. Never mind the frameworks, use the browser.

3W for In-Browser AI: WebLLM + WASM + WebWorkers

What if AI agents could run entirely in your browser? Not just the UI part—the actual model inference, agent logic, and response generation, all happening locally without a single API call.

Instant LLM Updates with Doc-to-LoRA and Text-to-LoRA

Recent LLM agents have shown impressive capabilities on complex computer use and long-horizon tasks. Yet, they still struggle with long-term memory and adaptation--two of the most important cognitive capabilities that still limit LLMs today. Without long-term memory, users have to provide LLMs with relevant content at the start of every new session, creating friction, discontinuity, and longer time-to-response. Additionally, due to the lack of adaptation, they do not learn from mistakes or user preferences from previous sessions, making each interaction as cumbersome as the first. Traditionally, these two problems are tackled by "updating" the model.

I Think I Have LLM Burnout

I didn't expect to get so tired of reading LLM output.

Protocol Handler Registration via Browser Extensions – make everything intensely

Custom URL schemes have traditionally served as an integration bridge between the browser and external capabilities. Schemes such as mailto: and tel: allow navigation to trigger actions beyond ordinary HTTP resource retrieval. The HTML Standard formalizes this mechanism through the Custom Scheme Handlers API, which enables websites to register themselves as handlers for specific URL schemes.

mozilla-ai/llamafile

Distribute and run LLMs with a single file.

mozilla-ai/llamafile

Distribute and run LLMs with a single file.

Sawyer Hood on Twitter / X

Introducing the new dev-browser cli. The fastest way for an agent to use a browser is to let it write code. Just `npm i -g dev-browser` and tell your agent to "use dev-browser" pic.twitter.com/U8VmsT5XVc— Sawyer Hood (@sawyerhood) March 25, 2026

State of Mozilla 2025

Doing for AI what we did for the web