Definitely would recommend the Rands Slack channel though only catch is you need to be in some sort of engineering leadership role (not sure if the criteria changed though). But I’m sure if you ask nicely, they’ll let you in. Lots of channels related to career advice there

Also would recommend just going through this huge list of tech companies that use Slack to see if any of them fits you: https://bloomberry.com/data/slack/

+1 for Rands Leadership Slack, it's a great community. While the general slant and audience are eng leadership heavy, there are definitely non-engineer and non-management folks there.

The web UI has become extremely slow. I am not sure if its that way for everyone or its because there are more people in our team using it. Many people dont like the UI too although that isnt my main concern

I guess to be explicit, how will they respond to the threat of it being designated a supply chain risk(edited title)

Thanks! Those are helpful!

For number one, any idea the best person to contact in those companies? They probably dont got a head of AI person so wondering if a VP of Engineering is the next logical person.

Also I haven’t thought of forums/communities! Any idea whether I am more likely to find small companies or big enterprises there?

I am actually not sure about the first.

For the 2nd, based on my experience you are likely to find developers from both big and small companies equally hanging out in communities. Most lean technical btw, so if you arent targeting developers, communities probably arent the best venue to find potential users.

I also forgot to add: finding followers of OpenAI in Linkedin might also be a good way to find ChatGpT customers. Or people who comment on their product announcemnts in Linkedin.

Would followers or commenters usually be recent customers though? Because that really is my target audience: users who just decided to purchase and use ChatGPT.

They probably wouldn’t be recent customers, that’s true. I would say if we were talking 4-5 years ago, followers/commenters would be a high signal they just started using ChatGPT; but it seems most of them are just bots now.

i dont even use a crm blushes. To be honest, im just starting out with outbound so im not doing anything sophisticated. Just want to import a list of leads, enrich with contact details and their tech stack data. Thats all.

Ppl keep recommending me tools like apollo and zoominfo but they way too powerful for me. I dont care about how many data providers they have because i just care about those 2 thinfs

The problem with not using Clay is that most of them dont do waterfall enrichment. So you’re just gonna end up with a list with 50% enriched instead of 90-95%…

It would be great if u could overlay a HN sentiment chart over all of these tools.

Examples?

Why are they going after the small fish?

If they really want to put a dent into this, go after the biggest players scraping LinkedIn: PeopleDataLabs and Apollo.io (and no, taking down their company page does not count)

Victory against small fish => establish legal precedence

legal precedence => Surer victory in the future for similar lawsuits

Reminds me of the Apple vs Pear law suit

https://www.entrepreneur.com/business-news/apple-sues-small-...

The dispute was settled because Pear agreed to slightly alter its logo, instead of continuing full litigation (maybe because of resources / dollars it would consume)

Seems there is a scraping precedent already, set by Linkedin v HiQ

https://www.fbm.com/publications/what-recent-rulings-in-hiq-...

Only if the case goes to trial.

If they settle, or the case got dismissed -- no precedent is set.

If that’s going to happen with a small fish then it was certainly going to happen against a big fish. Cheaper, faster, and easier to attack a smaller business first. There is literally no reason to go after a big dog unless they did something particularly egregious and/or distinct that you can anchor your argument with. Unless your goal is just to waste their time and that of their lawyers I guess, though I think we would all assume the goal is to win ultimately.

Even the legal filing and motions can help shape a case since they get rulings and such back. If a judge rejects a motion, maybe they need to approach it a different way when they go after big fish.

Only way this is not beneficial is if software company settle or gets dismissed right away.

Against bigger fish.

And there's always a bigger fish.

Go after small fish that no one cares about first to normalize the activity, then move up to bigger and bigger targets until you become inevitable.

Or, go after the small fish who can’t afford to have a biglaw team on retainer, bulldoze them to get a legal precedent set, and then use the example to extract concessions from the bigger players.

A smaller company without a big legal team is probably more likely to settle than a big company. Settlements don't establish precedent.

So you get money on the way up until you find a company willing to battle in court and lose.

Because they either have side deals with the big names, or they want to set precedent for going after them.

Not trying to be a conspiracy theorist here, but my bet is on having a deal with the big players, we allow you to scrape us (or we give you a pipe you can consume out of), and you pay us in monetary or non-monetary terms; like how many business exchanges work

I doubt they have side deals. They took action on some of them by removing their company page, but that is like a slap in the hand.

If you want to make a big deal about this, tell us you at least sent a letter to the big players too. Otherwise, dont put up such a huge show

They have a trademark ridealong whose chances improve against a less-recognized company.

I know someone who got addicted to the influencer money in Tiktok and dropped out of a med school program because making 5 figures a month, taking videos of you wearing fancy clothes was way better than slogging thru med school

I like this approach better TBH - more reliable and robust. It probably satisfies 80% of most customer queries too as most want to query against the same sources

Oh, I totally see your point.

We’re optimising for large enterprises and government customers that we serve, not consumers.

Even the most motivated people, such as OSINT or KYC analysts, can only skim through tens, maybe hundreds of web pages. Our tool goes through 10,000+ pages per minute.

An LLM that has to open each web page to process the context isn’t much better than a human.

A perfect web search experience for LLM would be to get just the answer, aka the valid tokens that can be fully loaded into context with citations.

Many enterprises should leverage AI workflows, not AI agents.

Nice to have // must have. Existing AI implementations are failing because it’s hard to rely on results; therefore, they’re used for nice-to-haves.

Most business departments know precisely what real-world events can impact their operations. Therefore, search is unnecessary; businesses would love to get notifications.

The best search is no search at all. We’re building monitors – a solution that transforms your catchALL query into a real-time updating feed.

So your customers just want to use this for their own internal data, not external data from the web. Is that correct?

no no, they want to use it on external data, we do not do any internal data.

I'll give a few examples of how they use the tool.

Example 1 -- real estate PE that invests in multi-family residential buildings. Let's say they operate in Texas and want to get notifications about many different events. For example, they need to know about any new public transport infrastructure that will make specific area more accessible -> prices wil go up.

There are hundreds of valid records each month. However, to derive those records, we usually have to sift through tens of thousands of hyper-local news articles.

Example 2 -- Logistics & Supply Chain at F100 Tracking of all the 3rd party providers, any kind of instability in the main regions, disruptions at air and marine ports, political discussions around the regulation that might affect them, etc. There are like 20-50 events, and all of them are multi-lingual at global scale.

thousands of valid records each week, millions of web pages to derive those from.