BrowseBrawl – What if browser agents battled to generate training data?
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…
In plain words
BrowseBrawl is an AI experiment where two browser agents compete against each other to generate training data. An attacker agent attempts to complete tasks on live websites while a defender agent injects JavaScript to interfere with its actions. Built on the principle that adversarial competition improves agent performance, similar to AlphaGo and GANs, the system is designed for researchers and developers exploring whether agents trained through competition produce higher-quality training data than those operating in static environments.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
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 injects JavaScript to sabotage it. The analogy isn't perfect, because browser tasks aren't zero-sum. But our hypothesis is that an agent faced with an adversary should produce more interesting training data than one navigating clean, static environments. Try it on: http://browser-brawl.com GitHub: https://github.com/RichardHruby/browser-brawl Demo Video: https://youtu.be/NIoFXv-JvBY (Skip to [0:55](https://www.youtube.com/watch?v=NIoFXv-JvBY&t=55s) to see the agents “brawling” in the arena :), [1:52](https://www.youtube.com/watch?v=NIoFXv-JvBY&t=1m52s) to see the browser traces generated) Would love to chat with anyone building or training browser agents. Happy to dive in below!
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