Sr. Content Developer at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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One Human + One Agent = One Browser From Scratch

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One Human + One Agent = One Browser From Scratch

embedding-shapes was so infuriated by the hype around Cursor's FastRender browser project - thousands of parallel agents producing ~1.6 million lines of Rust - that they were inspired to take a go at building a web browser using coding agents themselves.

The result is one-agent-one-browser and it's really impressive. Over three days they drove a single Codex CLI agent to build 20,000 lines of Rust that successfully renders HTML+CSS with no Rust crate dependencies at all - though it does (reasonably) use Windows, macOS and Linux system frameworks for image and text rendering.

I installed the 1MB macOS binary release and ran it against my blog:

chmod 755 ~/Downloads/one-agent-one-browser-macOS-ARM64 
~/Downloads/one-agent-one-browser-macOS-ARM64 https://simonwillison.net/

Here's the result:

My blog rendered in a window. Everything is in the right place, the CSS gradients look good, the feed subscribe SVG icon is rendered correctly but there's a missing PNG image.

It even rendered my SVG feed subscription icon! A PNG image is missing from the page, which looks like an intermittent bug (there's code to render PNGs).

The code is pretty readable too - here's the flexbox implementation.

I had thought that "build a web browser" was the ideal prompt to really stretch the capabilities of coding agents - and that it would take sophisticated multi-agent harnesses (as seen in the Cursor project) and millions of lines of code to achieve.

Turns out one agent driven by a talented engineer, three days and 20,000 lines of Rust is enough to get a very solid basic renderer working!

I'm going to upgrade my prediction for 2029: I think we're going to get a production-grade web browser built by a small team using AI assistance by then.

Via Show Hacker News

Tags: browsers, predictions, ai, rust, generative-ai, llms, ai-assisted-programming, coding-agents, codex-cli

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alvinashcraft
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Architectural Choices in China's Open-Source AI Ecosystem: Building Beyond DeepSeek

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Introducing Prism

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Prism is a free LaTeX-native workspace with GPT-5.2 built in, helping researchers write, collaborate, and reason in one place.
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Cost-Aware GenAI Architecture: Caching, Model Routing, and Token Budgets That Don’t Explode

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Shipping GenAI is easy. Shipping it without a surprise bill, latency spikes, and “why did it call the big model for that?” incidents is the hard part.

This article is a practical architecture pattern for cost control as a first-class system requirement — built around three levers:

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An Introduction to the Four Pillars of Observability

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It is a quiet Tuesday afternoon until the latency spikes begin. In the world of modern software engineering, we have moved far beyond the era of simple server monitoring. We no longer just “build and hope.” Instead, we strive for Continuous Reliability, a state where our systems are designed to be interrogated, understood, and improved in real time. This is the essence of Observability.

To truly master a running system, we must look through four distinct lenses, often called the pillars of telemetry. Each provides a different chapter of the story, and together, they offer a level of visibility that transforms production from a “black box” into an open book.

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0.0.396-0

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Pre-release 0.0.396-0

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