OpenAI researcher on why soft skills are the future of work | Karina Nguyen (Research at OpenAI, ex-Anthropic)
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What does Karina Nguyen do at OpenAI and how did she get there?
Not only are you working at the cutting edge of AI and LLMs, you're actually building the cutting edge.
When I first came to Andarin, I was like, Oh no, I really love frontend engineering. And then the reason why I switched to research is because I realized oh my god, cloud is getting better at front end. Cloud is getting better at like coding. I think Cloud can like develop new apps.
What skills do you think will be most valuable going forward for product teams in particular?
Creative thinking. And you kinda want to like generate a bunch of ideas and like filter through them in order to build the best product experience. I think it's actually really, really hard to teach the model how to be aesthetic or really good visual design or like how to be extremely creative in the way they write.
What do you think people m most misunderstand about how models are created?
When you taught the model some of the self-knowledge of you actually don't have a physical body to operate in the physical world, the model would get like extremely confused.
Today, my guest is Karina Nguyen. Karina is an AI researcher at OpenAI, where she helped build Canvas, tasks, the O1 chain of thought model, and more. Prior to OpenAI, she was at Enthropic, where she led work on post-training and evaluation for the Cloud 3 models, built a document upload feature with 100k context windows, and so much more. She was also an engineer at New York Times, was a designer at Dropbox and at Square. It's very rare to get a glimpse into how someone working on the bleeding edge of AI and LLMs operates, and how they think about where things are heading. In our conversation, we talk about how teams at OpenAI operate and build product, what skills she thinks you should be building as AI gets smarter, how models are created, why synthetic data will allow models to keep getting smarter, and why she moved from engineering to research after realizing how good LLMs are.
gonna be at coding. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It's the best way to avoid missing future episodes, and it helps the podcast tremendously. With that, I bring you Karina. Noen. This episode is brought to you by Interpret. Interpret unifies all your customer interactions, from gong calls to Zendesk tickets to Twitter threads to App Store reviews, and makes it available for analysis. It's trusted by leading product orgs like Canva, Notion, Loom, Linear, Monday.com, and Strava to bring the voice of the customer into the product development process, helping you build best in class products faster. What makes Interpret special is its ability
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This is a limited time offer that's interpret.com/slash Lenny. This episode is brought to you by Vanta, and I am very excited to have Christina Cassiopo, CEO and co-founder of Vanta, joining me for this very short conversation.
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Chapters
8 chapters
1
What does Karina Nguyen do at OpenAI and how did she get there?
0:00–9:51
2
Why do people misunderstand how large‑language‑model training works?
9:51–20:36
3
How is synthetic data used to keep AI models getting smarter?
20:36–29:33
4
What was the product thinking and engineering process behind Canvas?
29:33–39:38
5
What does a day‑to‑day AI research and product team look like at OpenAI?
39:38–49:17
6
Why are soft‑skill abilities like creativity and collaboration the future of work?
49:17–58:17
7
How do OpenAI’s and Anthropic’s approaches to model development differ?
58:17–1:07:11
8
What new AI‑agent capabilities (Operator) will change how we interact with computers?
1:07:11–1:14:29
Speakers
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