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Hey everyone! Just spent my evening yesterday dissecting this fascinating interview with Scott White (Product Leader at Anthropic) about how they build AI products, and wow - there's some really interesting stuff in here. Let me break down the key insights:
First, something I found fascinating: Anthropic splits their product org into FOUR teams (not the usual product/eng split):
But here's what REALLY blew my mind - AI product development is COMPLETELY different from traditional software. Here's why:
Their product development process is wild too. Instead of the usual agile stuff, they:
The most interesting part to me was their take on "doubling down on surprises." Like, when they built their artifacts feature, it started as an internal prototype that people just fell in love with. They saw how people were using it in ways they never expected and just leaned into that.
Here's what I found most counterintuitive: They're actually NOT focused on efficiency gains (like most AI companies). Instead, they're all about enabling entirely new forms of creation. Scott gave this great example of building a side-scrolling dinosaur game in 5 minutes - something he'd never have been able to do before.
Hot take: I actually think this might be why Anthropic is pulling ahead in some ways. While everyone else is focused on "AI make thing faster," they're thinking about "AI make new thing possible."
Also interesting: The future vision isn't just "better AI." They're thinking about Claude as an expert co-worker who can help you do what would've taken a team of experts weeks to do, but in days instead.
Advice for builders (straight from Scott):
Honestly, this completely changed how I think about AI product development. I used to think it was just "regular product but with AI" but it's a whole different game.
Questions for discussion:
TLDR: Anthropic's product development is WAY different from traditional software. Focus on early prototypes, double down on surprises, and think about enabling new forms of creation rather than just efficiency.
Finest product post I came across on GV so far. Thanks for sharing this.
Hey, Interesting Insights, at the same time I feel the fundamentals remain the same. Putting my 2c to the discussion -
It depends on the use case(s), you can quickly build and move out a product where you don’t have high-risks. Think, how Zepto started in India, they took orders on watsapp. In fact, I would say, product isn’t still fully mature.
Yes, answer lies in the question. Any non-deterministic outcome needs human evaluations (read anecdote verifications) to bring some deterministic information.
It’s same as typical products, depends on the team size and velocity, if you want same person to do all 4 things or separate those out. Safety risks are higher in AI but remains true for any consumer company.
Overall, I consider current-AI to be enhancer than a stand alone entity. Think from first principles, a product is nothing but automation of repeated processes. How AI is contributing to it? If we can answer that, it will make understanding easier.
I completely agree with this take.
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Hi Grapevine,
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