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break. them. up.

my favorite idea from the article: "Markets are a function of law."

that's an under appreciated sentiment by lots of people that think economic markets as natural. in reality they're constructs from our politics. antitrust laws used to be enforced to prevent this type of consolidation of capital. i'm glad antitrust enforcements are coming back to decentralize the American economy


you can upload a csv of linkedin connections to a Clay table then use a data provider like FullEnrich to get emails and other profile info.

Could also use a tool like n8n instead of Clay or build your own system to read the csv and make api calls to enrichment service


What's Clay? Can't find the service you're referencing with a few quick searches


This is interesting! What would you recommend first?


ya there's got to be an awakening that this is not the way. i think it's coming


> Asset control and power in America is centered among old people with lots of assets. And they associate protecting the stock market with protecting America.

> The “number go up” rule is not a story of greed or economics, it’s a story of how we make decisions as a society.

well said!


my favorite quote from the article is from Lina Khan:

"we don’t need to protect our monopolies from innovation—we need to protect innovation from our monopolies. We need to choose competition over national champions"


this is an issue with companies being too big


how are you harvesting all this data?


It's just the Bing search API under the hood. The process is: Query -> Crawl -> Categorize profiles.


> For example you could almost build a new kind of Job Search Service that matches job descriptions to job candidates based on nothing but a vector similarity between resume and job description. That's probably so obvious it's being done, already.

Literally the next item on my roadmap for employbl dot com lol. we're calling it a "personalized job board" and using PGVector for storing the embeddings. I've also heard good things about Typesense though.

One thing I've found to be important when creating the embeddings is to not do an embedding of the whole job description. Instead use an LLM to make a concise summary of the job listing (location, skills etc.) in a structured format. Then store that store as the embedding. It reduces noise and increases accuracy for vector search.


Very cool! I like that you can send small batch sizes to do small marketing bets. Going to build a campaign to promote my b2c saas in my city


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