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Product Positioning & Context
What does the average YC company actually look like? I scraped 793 startups and 1,625 founder bios from the last 5 batches to find out. 27 interactive charts covering: which industries are surging, which are dying, what founders have in common, how partners pick companies, hidden themes in descriptions, and the exact statistical profile of a "default" YC startup. Some surprises: YC funds direct competitors in the same batch. And every partner has a type. Free. No login
Related Ecosystem & Alternatives
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Deep-Dive FAQs
What is What YC Is Really Betting On??
What YC Is Really Betting On? is a digital product or tool described as: An X-ray of 793 YC startups
Where did What YC Is Really Betting On? originate?
Data for What YC Is Really Betting On? was aggregated directly from the Product Hunt community ecosystem, representing raw developer and early-adopter sentiment.
When was What YC Is Really Betting On? publicly launched?
The initial public indexing or launch date for What YC Is Really Betting On? within our tracked developer communities was recorded on February 24, 2026.
How popular is What YC Is Really Betting On??
What YC Is Really Betting On? has achieved measurable traction, logging over 177 traction score and facilitating 18 recorded discussions or engagements.
Which technical categories define What YC Is Really Betting On??
Based on metadata extraction, What YC Is Really Betting On? is categorized under topics such as: Startup Books, Venture Capital, Startup Lessons.
How does the creator describe What YC Is Really Betting On??
The original author or development team describes the product as follows: "What does the average YC company actually look like? I scraped 793 startups and 1,625 founder bios from the last 5 batches to find out. 27 interactive charts covering: which industries are surging,..."
Community Voice & Feedback
There’s a lot of narrative about what YC is doing, but very little actual data behind it. The near-identical competitors in the same batch finding is especially interesting. Curious if you noticed any patterns in founder backgrounds across deep tech vs. so-called wrappers? Love data-driven myth-busting like this. :)
Nice analysis! Is there any way I can play around with the data you've already scrapped? Would love to know more about the founders' backgrounds.
Amazingly helpful tool for me while making the first steps with CoreSight. Congrats on the launch and the product!
Thanks :) I've been wanting an analysis like this, but never got around to doing it.And a sidenote, I'm not surprised education is at the bottom. Over the past five years, AI has been killing informal education platforms; Udemy, Coursera, Thinkific, etc., have all lost ~85% of their stock price. I've heard universities have been struggling as well.
just interested, is there any information on age?
This is seriously impressive work. I've been meaning to dig into YC trends like this for a while. If there's any way I can contribute or help, I'd love to be involved. I'm especially interested in understanding underlying YC patterns more deeply.
Great analysis for YC portfolios! now question is here - how could my start up successfully break into YC? lol
Hey PH 👋
I kept hearing "YC only funds AI wrappers now" and wanted to check if it's actually true. So I scraped every company from the last 5 YC batches.
793 companies. 1,625 founder bios. Every tag, industry, and partner assignment.
Some findings that surprised me:
🔸 Only 15% are thin wrappers - and it's declining
🔸 Deep tech jumped to 29% of the latest batch
🔸 SF startups hire LESS than remote ones
🔸 YC funds near-identical competitors in the same batch - on purpose
🔸 Each partner has a distinct type (Diana Hu = infra, Garry Tan = contrarian bets)
Built with Python (scraping + NLP analysis) and Chart.js. Single HTML file, no backend.
This is a side project - not a product, not a startup. Just a weekend rabbit hole that got out of hand.
Would love feedback, what patterns do you find most interesting?
— Krishna
I kept hearing "YC only funds AI wrappers now" and wanted to check if it's actually true. So I scraped every company from the last 5 YC batches.
793 companies. 1,625 founder bios. Every tag, industry, and partner assignment.
Some findings that surprised me:
🔸 Only 15% are thin wrappers - and it's declining
🔸 Deep tech jumped to 29% of the latest batch
🔸 SF startups hire LESS than remote ones
🔸 YC funds near-identical competitors in the same batch - on purpose
🔸 Each partner has a distinct type (Diana Hu = infra, Garry Tan = contrarian bets)
Built with Python (scraping + NLP analysis) and Chart.js. Single HTML file, no backend.
This is a side project - not a product, not a startup. Just a weekend rabbit hole that got out of hand.
Would love feedback, what patterns do you find most interesting?
— Krishna
Discovery Source
Product Hunt Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
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Deep Research & Science
No direct peer-reviewed scientific literature matched with this product's architecture.