Alternatives
Products that do what One Human + One Agent = One Browser From Scratch in 20K LOC does
Related: https://simonwillison.net/2026/Jan/27/one-human-one-agent-on...
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Hi HN - we're Nithin and Nikhil, twin brothers and founders of nxtscape.ai (YC S24). We're building Nxtscape ("next-scape") - an open-source, agentic browser for the AI era. -- Why bother building a new browser? For the first time since Netscape was released in 1994, it feels like we can reimagine browsers from scratch for the age of AI agents. The web browser of tomorrow might not look like what we have today. We saw how tools like Cursor gave developers a 10x productivity boost, yet the browser—where everyone else spends their entire workday—hasn't fundamentally changed. And honestly, we…
2025 · github.com
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Hi HN! I want to share our latest project at NEXA AI. We developed AI agent foundation models designed to transform how developers create AI agent powered apps. One major challenge we've observed with current human-computer interactions is that many simple, one-step tasks become unnecessarily complex, multi-step workflows due to limitations of current GUIs. AI agents can solve this, but existing AI agent models are slow and costly. To tackle these issues, we built lightweight AI agent models based on our Octopus V2, small language models for function calling (You can learn more about our…
2024 · nexa4ai.com
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Hi HN, I forked chromium and built agent-browser-protocol (ABP) after noticing that most browser-agent failures aren’t really about the model misunderstanding the page. Instead, the problem is that the model is reasoning from a stale state. ABP is designed to keep the acting agent synchronized with the browser at every step. After each action (click, type, etc), it freezes JavaScript execution and rendering, then captures the resulting state. It also compiles the notable events that occurred during that action loop, such as navigation, file pickers, permission prompts, alerts, and downloads,…
Mar 2026 · github.com
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
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2024 · github.com
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I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…
May 2026 · github.com
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Hi, I've been watching the rise of AI agents with a mix of excitement and dread. We're building incredible tools that can browse the web, but we're forcing them to navigate a world built for human eyes. They scrape screens and parse fragile DOMs. We're trying to tame them to act like humans. I believe this is fundamentally wrong. The goal isn't to make AI operate at a human level, but to unlock its super-human potential. The current path is dangerous. When agents from OpenAI, Google, and others start browsing at scale and speed, concepts like UI/UX will lose meaning for them. The entire…
2025 · github.com
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I remember watching the AlphaGo documentary in 2017. What stood out to me was that the model got drastically better when it started competing against itself. GANs clicked for me similarly: a generator and discriminator competing, and somehow the competition is what produces something remarkable. I've been curious whether this principle generalizes to today's agents. So mehulkalia and I built Browser Brawl at the YC / BrowserUse hackathon last weekend and won first place. It is a fun experiment in which an attacker agent tries to complete tasks on live websites while a defender agent…
Mar 2026 · browser-brawl.com
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Hi HN, I’d like to share an open-source project we’ve been working on for a while: Browser4. The motivation came from a recurring frustration: most browser automation tools (Playwright, Selenium, Puppeteer) are excellent for human-written scripts, but start to show friction when used as a core execution layer for AI agents or at very high concurrency. So instead of building “another wrapper around Playwright”, we experimented with a different direction: designing a browser engine where AI agents are first-class citizens. ### What Browser4 is Browser4 is a browser automation engine built on…
Dec 2025 · github.com
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Hi HN, I'm one of the creators of Nanobrowser, an open-source Chrome extension that lets you automate web tasks using AI agents. We were inspired by the potential of tools like OpenAI's Operator, but we wanted something that was: -Open-Source:You can see the code, modify it, and contribute to the project. -Browser-Based:No complex setups or server deployments. It runs directly in your browser. -Customizable:You can tailor the agent's behavior to your specific needs. -BYO LLM:Bring your own large language model API key (OpenAI, Anthropic,or even local models), No vendor lock-in. -Privacy…
2025 · github.com
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Mar 2026 · github.com
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Hi HN – we're the founders of BrowserOS.com (YC S24), and we're building an open-source agentic web browser. We're a fork of Chromium and our goal is to let non-developers create and run useful agents locally on their browser. --- When we launched a month ago, we thought we had the right approach: a "one-shot" agent where you give it a high-level task like "order toothpaste from Amazon," and it would figure out the plan and execute it. But we quickly ran into a problem that we've been struggling with ever since: the user experience was completely hit-or-miss. Sometimes agent worked like…
2025 · github.com
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There's been some interesting work lately with BrowserAI (runs LLMs in the browser using WebGPU) enabling local, private AI processing. Now, the team has released BrowserAgent - a no-code tool built on top of it. BrowserAgent lets you create custom AI workflows using a drag-and-drop interface, all within your browser. This means personalized web summarizers, research assistants, or content generators can all run locally with no cloud costs and full data privacy. Check it out here - https://browseragent.dev Key features include: - No-Code Workflow Builder: Design custom AI agents…
2025 · browseragent.dev
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Jul 2026 · github.com
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Mar 2026 · github.com
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Mar 2026 · docs.firecrawl.dev
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I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural…
Jan 2026 · fabceolin.github.io
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Hi HN, Zidan here. I’ve been experimenting with AI-assisted debugging and noticed a recurring gap: most tools optimize for agent-led exploration (ex: giving claude code a browser to click around and try to reproduce an issue). But in many cases, I've already found the bug myself. What I actually want is a way to hand the agent the exact context I just saw - without retyping steps, copying logs, or hoping it can reproduce the behavior. So we built FlowLens, an open-source MCP server + Chrome extension that captures browser context and lets coding agents inspect it as structured, queryable…
Nov 2025 · github.com
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We just open-sourced the internal system we built at Assembled for running coding agents as a team. Coding agents worked well for individual engineers, but the surrounding workflow was a bit of a mess. We generally found that many engineers had different MCP connections and context for their agents, personal automations running that other people couldn’t access, and very little introspection for what a human’s input into the coding agent looked like. So we built an internal system that converted coding agents into shared team infrastructure. The system runs Codex, Claude Code, OpenCode, and…
Jun 2026
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Hi HN! Sean from MindStudio here. I wanted to share something we've been working on that I think introduces some new ideas into the "AI coding agent" space. Remy is an AI agent that builds full-stack TypeScript apps from a spec written in a new flavor of annotated markdown. The spec has two layers: prose describing what the app does, and annotations that carry the technical precision (data types, edge cases, validation rules, code snippets). The agent then "compiles" this into code: backend methods, typed schemas, frontends, test scenarios, and everything else are derived artifacts of the…
Apr 2026 · remy.msagent.ai
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100% stable headless browser kit for AI Agents(Linux, macOS)
Jun 2026 · github.com
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