Chip Huyen
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9 June
29 March
From one piece Chip Huyen: Building when it feels like there's nothing left to build - The Pragmatic Summit 9 beliefs, in the piece's order there
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Their words
And the question nowadays is less about like how to build because if you can describe the problem in the solution you want, usually AI can do it. Maybe not today, but maybe like two or three years from now on they can do a lot of those. The question is like what to build because we talk about like yes, if something exists, right? AI can replicate it.
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Their words
And I feel like it's a very human way of doing web search, right? Because we enter things in the Google and we see all the like citations, the quotations part. But like why would we limit AI to that? If AI already visit a page, why don't just pull the entire page out?
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Their words
So, I think that the whole workflow of like reviewing code is very outdated. Like, I don't think the I think that the senior member, instead of like giving feedback on the code, they should be giving feedback on like how you give instruction to AI to produce better.
+ 6 more
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So, I I think there's a lot of things we still try to imagine. What would be an AI-driven world look like, right? I think people are trying to like retrofit what already exists to fit what they think is a new workflow.
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But in Vietnam and also in a lot of other Asian countries, people are on the move all the time. Like people are on the motorbike all the time. So, they actually really don't like typing. So, the voice like a lot of the companies in Vietnam actually deploy voice bots before they do uh do chatbot.
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The problems worth a small builder's time are the ones too small for a big AI company to be motivated to solve.Their words
Like if it's a big problem, like everyone can see, then all these big companies will get into it. But whereas it's like there are a lot of problems that's like smaller, then maybe OpenAI won't be motivated to solve it, but maybe I can like all a lot of people can.
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Problems follow a long tail: AI will keep getting better at the common ones, and the edge cases will never go away.Their words
So, I think of them as the top of the long long tail long tail problem. Like, something very common issues that a lot of people experience. AI will get really good at it. And over time AI will cover more more edge cases, but the edge cases will never go away.
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Their words
And the more you build, right? The more you put things out there, you remove the need for imagination. You can say, "Okay, now I like that website. Do that for me."
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Their words
if you can describe a style, AI can generate it. And the same with software. If you can describe a software, then AI can build it for you.
8 August 2025
16 January 2025
From one piece Common pitfalls when building generative AI applications 3 beliefs, in the piece's order there
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korrents.com
AI judges used to evaluate AI outputs need ongoing validation and iteration, just like any other AI system.Their words
AI judges must be evaluated and iterated over time, just like all other AI applications.
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Building a working AI demo is far easier than turning it into a reliable production product.Their words
This is perhaps one of the first painful lessons anyone who has built an AI product quickly learns. It's easy to build a demo, but hard to build a product.
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Their words
Because everyone uses the same models nowadays, the AI components of AI products are similar, and the differentiation is product.
7 January 2025
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korrents.com
Most real-world AI agent systems are actually multi-agent systems made of multiple components.Their words
Because most agentic workflows are sufficiently complex to involve multiple components, most agents are multi-agent.
25 July 2024
From one piece Building A Generative AI Platform 2 beliefs, in the piece's order there
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AI models are probabilistic, making their outputs unreliable.
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Context construction for foundation models is equivalent to feature engineering for classical ML models.
14 March 2024
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Their words
Several people have speculated that we'll see many very valuable one-person companies (see Sam Altman's interview and Reddit discussion). I think they might be right.
28 February 2024
From one piece Predictive Human Preference: From Model Ranking to Model Routing 3 beliefs, in the piece's order there
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Their words
One pattern is that for simple prompts, weak models can do (nearly) as well as strong models. For more challenging prompts, however, users are much more likely to prefer stronger models.
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With more and more models being developed, each with different capabilities and a cost structure, model routing has clear economic values.
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Routing prompts to different AI models can improve response quality while lowering cost and latency.Their words
Model routing has the potential to increase response quality while reducing costs and latency.
16 January 2024
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Their words
This probabilistic nature makes AI great for creative tasks.
27 December 2019
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