Howie Liu: preference

Transcript context

…Today's episode is brought to you by Anthropic, the team behind Claude. I use Claude at least 10 times a day. I use it for researching my podcast guests, for brainstorming title ideas for both my podcast and my newsletter, for getting feedback on my writing, and all kinds of stuff. Just last week, I was preparing for an interview with a very fancy guest, and I had Claude tell me what are all the questions that other podcast hosts have asked this guest so that I don't ask them these questions. How much time do you spend every week trying to synthesize all of your user research insights, support tickets, sales calls, experiment results, and competitive intel? Claude can handle incredibly complex multistep work. You can throw a hundred-page strategy document at it and ask it for insights, or you can dump all your user research and ask it to find patterns. With Claude 4 and the new integrations, including Claude 4 Opus, the world's best coding model, you get voice conversations, advanced research capabilities, direct Google Workspace integration, and now MCP connections to your custom tools and data sources. Claude just becomes part of your workflow. If you want to try it out, get started at Claude.ai/Lenny. And using this link, you get an incredible 50% off your first three months of the pro plan. That's Claude.ai/Lenny. For people that work for you across Airtable, say the product team, PMs, maybe engineers, designers, how have you adjusted what you expect of them to help them be successful in this new world? One is really, really, really stressing this idea of go play with this stuff. And I mean, when I say play, I really mean play in the psychological sense of there's a difference when you go in and you're kind of just trying to check the box and get a job done. There's a difference when you come in with a curiosity and you're kind of exploring, right. And it's both more fun and energizing, but also, I think you learn more through that. And so I've really tried to stress the value of play with these AI products. And I kind of try to lead by example, by literally going and sharing out links or screenshots of the things that I'm doing in these various products. So, as an example, I will go into one of the prototyping tools and show, "Hey, I built a marketing landing page for this new capability we're launching." I created a landing page for it in Replit, let's say, and now I'm sharing that link. Instead of what typically we would've done in the past is like, okay, we're going to write a doc about it and then share the doc, I'm just going to show you an actual landing page with visuals and everything in there. Or I'll share the actual link to my deep research reports. Or instead of me writing a perfect memo on a topic, I'll actually just prompt my way into getting a chat thread or a chat output that basically covers all the content that I care about and maybe even ask it to, "Okay, summarize this all into a final memo output," and then intentionally share that rather than expose the fact that I'm using AI in this way and here's literally how I'm prompting it so you can follow along as well. But really trying to encourage everyone to go and just play with these products. And I've even said, "Look, if anyone wants to just literally block out a day or frankly even a week and have the ultimate excuse, you could use... you could say that I told you to do it, right. If you want to cancel all your meetings for a day or for an entire week and just go play around with every product, AI product that you can find that you think could be relevant to Airtable, go do it. Period. So I think that's the most important thing is this play, this experimentation. I think there's also a lot of other kind of shifts in how we execute prototypes over decks. I want to see actual interactive demos because, again, it's hard to... In a deck or in a PRD, you could say, "Okay. Well, we're going to make Omni really good at handling this kind of app building." Okay, those are just words. The real proof is in the pudding of like, "Okay, let me try it out on a few realistic prompts that I can imagine." And in a demo, in a real prototype, you can instantly try it out on unrealistic rather than golden pathy scenarios and see how it feels too. Does it feel too slow? Do we need to expose more of the reasoning or steps that are happening behind the scenes? Create a progress bar or something like that. pathy scenarios and see how it feels too. Does it feel too slow? Do we need to expose more of the reasoning or steps that are happening behind the scenes? Create a progress bar or something like that. But it's really hard to get that feel of the product with anything but a functional prototype that really does, in an open-end way, use the AI to do whatever you put in. So I think it's more like a experimentation playground it feels like how we need to execute, versus I think, in the past, it sometimes felt like a more deterministic resourcing and kind of timelines view of execution. We're going to put this many people on this problem, and this is the eight-week timeline to this milestone, and then we're going to ship in a quarter from now. And I think now the whole thing is just a lot more experimentation and iteration-driven.…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.