So to make sure I am understanding this, even though a site update its selectors weekly for example like LinkedIn, your automation agent would still continue to work.
But if a website changes its UX and your recording no longer works then it will fail?
Working in the browser agent space myself, although you save on cost with these repeatable recordings the true disruption of browser agents is using one prompt on thousands of websites without having to worry about maintenance at all
Since it looks like you are built on FireCrawl, and FireCrawl itself has similar products like FireEnrich, how do you see yourself maintaining a differentiation and compete with FireCrawl directly, if they just decide to copy you?
As an aside, we are about to launch something like similar at rtrvr.ai but having AI Web Agents navigate pages, fill forms and retrieve data. We are able to get our costs down to negligible by doing headless, serverless browsers and our own grounds up DOM construction/actuation (so no FireCrawl costs).
https://www.youtube.com/watch?v=gIU3K4E8pyw
Good point. Our main differentiation is the shared workspace - users can step in and guide the agent mid-task, kind of like Cursor vs Claude (which can technically generate the same code that Cursor does). Firecrawl (or any crawler we may use) is only part of the process, we want to make the collaborative process for user <> agent as robust and user controllable as possible.
> Although the payment is enormous, it is small compared with the amount of money that Anthropic has raised in recent years. This month, the start-up announced that it had agreed to a deal that brings an additional $13 billion into Anthropic’s coffers. The start-up has raised a total of more than $27 billion since its founding in 2021.
Maybe small compared to the money raised, but it is in fact enormous compared to the money earned. Their revenue was under $1b last year and they projected themselves as likely to make $2b this year. This payout equals their average yearly revenue of the last two years.
Here is an article that discusses why those numbers are misleading[1]. From a high level, "run rate" numbers are typically taking a monthly revenue number and multiplying it by 12 and that just isn't an accurate way to report revenue for reasons outlined in that article. When it comes to actual projections for annual revenue, they have said $2b is the most likely outcome for their 2025 annual revenue.
It doesn't matter if they end up in chapter 11... If it kneecaps all the other copyright lawsuits. I won't pretend to know the exact legal details. But I am (unfortunately) old enough that this isn't my first "giant corporation benefits from legally and ethically dubious copyright adjacent activities, gets sued, settles/wins." (Cough, google books)
Personally I believe in the ideal scenario (for the fed govt.) these firms will develop the tech. The fed will then turn around and want those law suits to win - effectively gutting the firms financially and putting the tech in the hands of the public sector.
You never know, its a game of interests and incentives - one thing for sure - does does the fed want the private sector to own and control a technology of this kind? Nope.
But what are the profits? 1.5B is a huge amount, no matter what, especially if you’re committing to destroying the datasets as well. That implies you basically used 1.5B for a few years of additional training data, a huge price.
If it allowed them to move faster than their completion, I imagine management would consider it money well spent. They are expected to spend absurd amounts of money to get ahead. They were never expected to spend money efficiently if it meant taking additional months/years to get results.
If they are going to be making Billions in net income every year going forward, as many years as analysts can make projections for, and using these works allowed them to GTM faster/quicker/gain advantage against competitors, then it is quite great from a business prospective.
Yeah it does, cost of materials is way more than that if they were building something physical like a new widget or something. Same idea, they paid for their raw materials.
Isn't that how the whole system operates? Everyone is a conduit to allow rich people to enrich themselves further. The amount and quality of opportunities any individual receives are proportional to how well it serves existing capital.
So long as there is an excuse to justify money flows, that's fine, big capital doesn't really care about the excuse; so long as the excuse is just persuasive enough to satisfy the regulators and the judges.
Money flows happen independently, then later, people try to come up with good narratives. This is exactly what happened in this case. They paid the authors a lot of money as a settlement and agreed on a narrative which works for both sets of people; that training was fine, it's the pirating which was a problem...
It's likely why they settled; they preferred to pay a lot of money and agree on some false narrative which works for both groups rather than setting a precedent that AI training on copyrighted material is illegal; that would be the biggest loss for them.
> Isn't that how the whole system operates? Everyone is a conduit to allow rich people to enrich themselves further. The amount and quality of opportunities any individual receives are proportional to how well it serves existing capital.
You're joking, but that's actually a good pitch. There was a significant legal issue hanging over their heads, with some risk of a potentially business-ending judgment down the line. This makes it go away, which makes the company a safer, more valuable investment. Both in absolute terms and compared to peers who didn't settle.
It just resolves their liability with regards to books they purported they did not even train the models on, which is all that was left in this case after summary judgment. Sure the potential liability was company ending, but it's all a stupid business decision when it is ultimately for books they did not even train on.
It basically does nothing for them besides that. Given the split decisions so far, I'm not sure what value the Alsup decision is going to bring to the industry, moving forward, when it's in the context of books that Anthropic physically purchased. The other AI cases are generally not fact patterns where the LLM was trained with copyrighted materials that the AI company legally purchased copies of.
- Prompt injection risks combined with Debugger permission on user device is asking for trouble.
- Will trigger captchas/bot detection even on your normal browsing due to this permission.
- Kind of slow. Limited to current open tab as opposed to capability of multi tab action because only current active tab get rendered. For example rtrvr.ai can open a batch of tabs and take actions on background tabs.
- For some websites like Bloomberg asking to go to claude.com
- Prompt injection risks combined with Debugger permission on user device is asking for trouble.
- Will trigger captchas/bot detection even on your normal browsing due to this permission.
- Kind of slow. Limited to current open tab as opposed to capability of multi tab action because only current active tab get rendered. For example rtrvr.ai can open a batch of tabs and take actions on background tabs.
- For some websites like Bloomberg asking to go to claude.com
Its hard to tell without benchmarks how useful this is going to be, as Perplexity Comet landed as a dud.
Most of the other agentic chrome extensions so far used vision approach and sensitive debugger permissions, so unsure if Anthropic just repackaged their CUA model into an Extension.
We are working on a DOM/Text Only AI Web Agent, rtrvr.ai:
- an AI Web Agent that autonomously completes tasks, creates datasets from web research, and integrates any APIs/MCPs – with just prompting and in your browser!
I get it no one is using that, but like this just sounds like a rehash?
https://modelcontextprotocol.io/specification/2025-06-18/ser... https://modelcontextprotocol.io/specification/2025-06-18/ser...