In 2023 when I started, nobody said Anthropic and Claude and coding in the same sentence. I saw people were starting to use these models not just for code autocomplete, but actually writing long form code, and that was an opportunity for us to train Opus 3 to be better at coding. It ended up being a relatively smaller change from a training perspective but helped us differentiate competitively.
Diane identifies that early on, nobody associated Anthropic with coding, but she spotted users writing long-form code with models and pushed for Opus 3 to be trained on coding — a small training change that became a key differentiator. ✦ AI generated
Diane Penn · Lenny's Podcast · 2026-07-26 · original ↗
starts at this moment · 0:00
“What are some of the other big inflection moments as you think about just Anthropic going from just this lab that's trying to compete with this juggernaut of OpenAI at that point to what it is today?”
In 2023 when I started, nobody said anthropic and claude and coding in the same sentence. I think competitor models like GPT4 at the time was used a bit for coding but it was one of many use cases. And one thing that for example I saw was people are starting to use code these models not just for code autocomplete but actually writing long form code and is that an opportunity for us to train Opus 3 to be better at and it ended up being a relatively smaller change from a training perspective but it ended up helping us differentiate in the early days competitively for users and actually bring a lot of the very early Claude enthusiasts and developers because we were providing a value that they didn't really think was possible at the time.
verbatim transcript · starts at 0:00
0:00In 2023 when I started, nobody said anthropic and claude and coding in the same sentence. >> I want to go back to the beginning of anthropic. I remember dealing, man, these guys have no chance. OpenAI is so far ahead. >> At the time, I saw people were starting to use these models not just for code autocomplete, but actually writing long form code and [music] sat an opportunity
0:22for us to train Opus 3 to be better at. That was the inflection. [music] I always think about Opus 45 a year later during winter break when everyone was home able to code. >> What was magical about Opus 45 is we also now not just had a model but a vehicle a great product experience like cloud code. Opus 45 wouldn't have had that moment without a product like cloud
0:44code and cloud code wouldn't have had that type of adoption accelerated without opus 45. >> I want to talk about how the product role is changing >> for my team. The way to drive user value is to figure out the right user feedback. The evals, we actually have a saying on the team of evals are the new PRDs. >> Something Gary Tan's been talking about. If you are willing to spend $100,000 a
1:06year right now in tokens, you are living the way somebody in 2028 is going to live. >> You have to sweat the tokens as much as you sweat the pixels. You have to be using the models to come up with good and great and better ideas. And there's no substitute for that. People need to be more ambitious with AI tools these days because they're just capable of so
1:25much. >> One thing I ask the team is let's say Claude 8 comes around. What changes in what users do? What does that mean for how you're building today? >> Today my guest is Diane Penn, head of product for the AI research and labs teams at Anthropic. She joined Anthropic as the first technical product manager over three years ago, which is a lifetime [music] in AI time when the