Browser Agents

1. pip install browser-use (Browser-Use — open-source browser agent framework).
2. Install Ollama → ollama pull qwen2.5-vl:7b (~5 GB — vision-language model for seeing web pages).
3. Python script:

from browser_use import Agent
import asyncio

async def main():
    agent = Agent(
        task="Go to wikipedia.org, search for 'artificial intelligence', and extract the first paragraph of the article.",
        llm=ChatOllama(model="qwen2.5-vl:7b"),
    )
    result = await agent.run()
    print(result)
asyncio.run(main())

1. The agent opens a browser (Chromium via Playwright), navigates to Wikipedia, types the search, clicks the result, extracts text, and returns it. First run in 20-60 seconds.
2. For complex multi-step tasks: "Log into my email, find the latest invoice from Amazon, download it, and save to ~/invoices/." The agent handles login, navigation, dropdowns, file downloads.
3. The agent sees screenshots (VLM) + reads DOM elements (accessibility tree). The VLM decides "what to click" by analyzing the screenshot.

Used RTX 3060 12 GB (~$200-250, see /hardware/rtx-3060-12gb). Runs Browser-Use with Qwen2-VL 7B at ~20-40 seconds per agent step (see → decide → act). A 5-step task (search, click, scroll, click, extract) takes 2-4 minutes. For automation of daily web tasks (form filling, data extraction, monitoring): $400 handles 10-30 tasks/day. Pair with Ryzen 5 5600 + 32 GB DDR4 + 512 GB NVMe. Total: ~$390-440. The bottleneck is VLM inference speed (5-10 seconds per screenshot) and reasoning quality.

Used RTX 3090 24 GB ($700-900, see /hardware/rtx-3090). Runs Browser-Use with Qwen2-VL 72B at ~30-60 seconds per agent step — the 72B handles complex UIs (enterprise SaaS dashboards, multi-step forms, CAPTCHA workarounds) that confuse the 7B. For production browser automation (web scraping at scale, automated testing): Qwen2-VL 7B on RTX 4090 ($2,000, see /hardware/rtx-4090) achieves 10-15 agent steps per minute. Total: ~$1,500-2,500. Browser agents are a VLM throughput problem — faster screenshot analysis = faster agent.

The mistake: Running a browser agent on your personal Chrome profile (with saved passwords, cookies, banking sessions) — giving the AI access to your entire digital life. Why it fails: The agent can click anything. It can navigate to your email → forward sensitive messages → delete evidence. It can access your bank → initiate transfers. Even if the prompt seems benign ("check my Amazon orders"), the agent might misclick into account settings, change your password, or order 100 copies of a book. The fix: Always use a dedicated browser profile. Create a separate Chrome/Chromium profile with only the logins the agent needs. Use incognito mode + manual login per session for sensitive tasks. Never give a browser agent access to your primary browser with saved passwords and active banking/email sessions. The agent is a program executing LLM decisions — it has no judgment about what's safe to click. Sandbox it.