September 30th, 2024
The Leaderboard // Blog wars
Hello and Happy Monday! In today's Leaderboard: Beehiiv wants to make you rich through newsletters, Cheffie wants take the guess work out of dining, and a YC company wants to democratize access to data, but should it?
Blog wars intensify
Beehiiv paid newsletter feature: Allows you to set up multiple subscription tiers for readers and keep 100% of the revenue.
"Beehiiv is focused on building up individual creators, Substack is focused on building creator networks.” This is how a Beehiiv employee put the difference to me last week in Austin. The distinction makes sense: Substack plugs creators into its Twitter-like “Notes” feed to get organic distribution, while Beehiiv offers them an open API and granular analytics to help them aggressively monetize. I think it’s shrewd Beehiiv is doubling-down on the differences with its new paid feature — the appeal of keeping all subscription revenue could lure some of Substack’s biggest names away.
Perfect for picky eaters
Cheffie: an app that analyzes restauraunt menus and generates recipes to fit diet
Cheffie launched on Friday after demoing at the Product Hunt maker event. It generates custom recpes on the fly for you and analyzes local restaurent menys to match your dietary needs, allergies, health goals, etc. I can see this becoming a best friend for tourists, especially those who find eating out hard. Even for me as a former chef, having an app that does away with all the fluff that comes with recipes blogs is a huge win.

If your AI product has an onboarding step that says "tell us about your business" — your users are lying to you. Not maliciously. They just write whatever sounds good in the moment, skip half the fields, and click next.
Brandfetch's Brand Context API gives you structured brand data for 50M+ brands in a single call: voice,mission, positioning, audience, competitors, all of it. Pre-fill your onboarding before the user types a word.
Ground your AI features so they stop hallucinating about the brands your LLM barely knows. It's the scraping pipeline most teams never get around to building, already built. 100 free calls, no credit card.
Don't be quick and wrong
panda{·}etl: AI-powered data extraction software.
I started my career in data science, taught myself SQL and Python, and retain some strong opinions about the field. Such as: Learning SQL allows you to ask better questions of data, and I think it’s always much more important to prevent wrong analytics insights than it is to allow access to data. I don’t believe in democratizing access to data; you should have to work for it, refine your question, or work with someone data-literate. AI will potentially change this, and if we can build enough trust in AI data tools (Hex Magic and Julius come to mind), we might finally be free of SQL gatekeeping. But in the short term, I’m hesitant of spot solutions like Panda for key analytics use cases — it’s too easy to get a quick, wrong answer. And too hard to validate that answer.
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