In this case, you know who claimed it. In most cases, you don't, because Google does not verify identity.
It's currently the rage in blackhat SEO: just say you're John Doe from Doeville and competitorsite.com is infringing on your copyright. Google will remove that specific URL from the SERPs and there's a 50/50 chance whether the target gets a notification from google or not.
If they do, they can counter claim directly and it takes 12-48 hours to be reinstated.
If they don't, they have to figure out what's going on by using the Lumen Database (the only way to receive that information because Google is horribly bad at basic legal matters) and finding the notice, which will contain the exact URL (because fun fact: the claim and counter-claim are case-sensitive, the removal-from-serp is case-insensitive), and then do manual counter-claim, and it takes anywhere from 3 to 30 days.
During that time, your competitor will just be gone from the SERPs.
> Where is the big browser, operating system, or other piece of work that has been able to quickly compete with the existing entries in the market due to LLMs?
Why would it "quickly compete"? What if AI gives you a 100x leverage but not a 100000x leverage?
With the 100000x leverage, you could spin up a full browser and compete, but not with the 100x. With 100x, you could use fewer people or do it in less time, but the amount of effort that goes into browsers still doesn't make it "an afternoon for one person".
I think it's undeniable that an excavator is ridiculously more powerful than a human at digging holes. Let's say it's 100x more efficient.
But if you had 1000 people work on a big hole every day for 5 years, the excavator wouldn't manage to do the same in a day, but it would allow you to do the same with 10 people and 10 excavators in 5 years, or with 50 people and 50 excavators in one year.
I don't think it scales linearly the more complexity grows, but "it hasn't been done, therefore it isn't possible" seems wrong. Maybe the big labs could build a browser, but they'd much rather spend the attention of 50 engineers on something else.
I found that agents help, even if you don't parallelize. Having one agent control another and verify its results against rules you set has worked well for me because the controlling agent has no incentive to cut corners, and the implementor might, but it is being controlled.
My usage might be much simpler than what you do, but it went from "but I gave a list of things to do, you only did 5 of them" - "okay, here are the other 7, oh btw, I skipped the verification rule because nobody has time for that" to good compliance, the orchestrator starts the sub agents, tells them exactly one thing to do, and makes sure they've done it afterwards.
makes sense on planning as well, I think. spend your tokens on the best model to explore the problem and design the solution, but the implementation and testing/verification cycles don't need the strongest model you can get.
I only get anything useful when I force extremely strict standards and opinions so that it is impossible to deviate from what I want. That only really works in some languages and some programming styles. Whenever I try to do something less constrained there is some sort of patina of stupid that can't be polished away mechanically.
I'm on the other side, and my main tip (at least if there's people like me!) is: avoid the usual AI signs.
For one role we got ~70 applications and all CVs looked obviously AI-written. I don't know whether the people did actually do any of the things mentioned and I don't have the time to find out, so the AI-written CVs are a discard-signal for me. (Either those people delegated a very important task to AI and didn't even bother to check, or they are bad using AI and don't know -- I want neither)
Any CVs that signal they were actually written by a person I will actually look at.
> For one role we got ~70 applications and all CVs looked obviously AI-written.
Were those ~70 applications all of them, or were those ~70 applications the result of an AI filtering from a larger amount?
If the latter, are you sure your AI is not filtering out the hand-written CVs and giving you the ones that have been AI-assisted or AI-written (with or without "the usual AI signs")?
Moats for software/web companies that are entirely "we've built it, it would be too expensive for you to replicate it" are getting much weaker. It's now quick to produce something that at least looks close to an existing product. You can't clone the backend, the know-how to handle some weird interactions etc, but still, you can get fairly far mimicking the frontend, and LLMs can write you the fancy marketing buzzwords too.
I think the part you can't easily clone will turn out to be the institutional processes that allow you to run at scale, onboard new people, deal with common requests that AI cannot on its own (e.g. legal compliance), the relationships you have with partners and vendors, the legal setups you have in place etc.
I'd assume that plenty of developers feel capable to building a better jira, and some try, and few/none succeed despite atlassian doing everything in their power to drive clients away, because cloning the project isn't the hard part with that type of product.
Are you sympathetic to a doctor who specialized in surgery and now always recommends surgery, even for a common cold? Or would you say they are in the wrong job, if they are anywhere but surgery?
Ridiculous example that does nothing to argue the original, fair point. Obviously health interventions demand more finely tuned solutions than information technology
FWIW, maintaining at least a moderate degree of empathy even in systemically frustrating situations is good for the empathizer and thus in one’s interest
That's obviously not the issue with that -- you don't see those comments on Google's AI announcements.
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