I asked clawdbot to scrape canada goose prices it grabbed an unblocked browser, bypassed kasada antibot, scrolled to load everything, and handed me clean json in 47 seconds skill is live on clawdhub if anyone wants it: clawdhub.com/alexander-sprin… @steipete @openclaw @aibrowsers

I just launched a SOTA stealth browser platform that lets anyone build their own browser agents and web scraping automations 🚀 Agents have been underwhelming: they hit CAPTCHAs, get blocked entirely, and most infrastructure is designed for the past, not the future. The idea here was simple, build a distributed browser network on real consumer devices so agents can see the web like humans do. With a single API call, you can spin up a real browser or agent on a real user device with a full, authentic fingerprint. This is the infrastructure you’d need to build a true Perplexity Comet style product, except this one actually reaches the content and doesn’t require your computer to be running. When you build the full stack from the ground up: deploying custom hardware profiles, real operating systems, and properly tunneling WebRTC; You get something that works by design, not something that breaks every few weeks. Try it out -> You can build shopping agents, account managers, travel planners, and workflows that weren’t possible before. All developers who sign up now get $25 in free credits at browser.cash/developers #browsercash #browseragent #webscraping

Comparison of @morph_labs vs. @aibrowsers browser infra 👇 Morph browsers: Blocked, Cloud IP address, Captchas Our browsers: Unblocked, Residential IP address, Appears Human @morph_labs we'll host your browsers for free Benchmarked using our playground, will be released to public next week for reproducing results

LLMs are failing to meet the standards required for intelligent browser agents. > high latency + low TPS = slow agents > bad tool calling or vision = incorrect actions > poor understanding of web workflows = failed tasks @aibrowsers is building the largest peer-contributed web workflow dataset. Real humans providing accurate data on difficult to navigate sites.

It's a case of constant reiteration and reverse engineering to build the correct set of humanistic variables required for web agents at scale. The first test I ran after these claims of "stealth" was against @aibrowsers internal systems 👇 Browser Use: Blocked instantly > Runs for 16:47 mins > Outputs wrong answer Our Agent + Infra: Unblocked access > Runs for 1:23 mins > Outputs correct answer