- Dive Club
- Posts
- 🤿 human truth
How do you stand out in a sea of talented designers?
What does it take to create a product that truly resonates when every day a dozen new startups are launched on Twitter?
I chatted with Sara Vienna (Chief Design Officer at Metalab) to find out…
Some highlights:
How to not get swept up in current design trends
How Metalab has adopted AI workflows internally
Strategies for leveraging AI to understand research data
What it takes to put meaning at the heart of a brand/product
How Metalab invests in the collective taste of the design org
Where Sara derives signals and how she filters out the noise
+ a lot more
🤝 WITH PAPER
So I’ve been playing with Paper for image editing and it’s pretty legit.
They support all the best models and everything exists on a persistent canvas so you can see your generation history and easily fork from old ideas…
Just select anything you want, type your prompt, and generate variations ♾️
And one of my favorite parts is you can then right click and vectorize that creation without having to use a separate tool.
It’s a huge unlock for creativity and just another reason why I’m so excited about Paper as the next great design tool.
Start using it today. Just click the link 👇
🔑 KEY TAKEAWAYS
An idea for using AI in research
One of the topics I dug into with Sara was how to get the most out of AI while doing research. Our conversation sparked an idea that I want to share with you today.
Take Inflight for example… back when we were navigating the idea maze, I ran 200+ interviews with designers, leaders, PMs, and so on. I then organized everything into a Granola folder.
From there, I’d ask things like “what feature ideas came out of this chat?” Or I’d run a prompt that ranked how excited someone seemed on a scale of 1–5, then used that score to decide who got a beta invite.
But here’s the angle I never thought of…
What if, instead of just extracting answers, I fed all the raw data into a model and said:
“I want you to ask me questions about these interviews. Push me to articulate the key insights I noticed, and the trends that stand out.”
Getting grilled on ICP and problem statements sharpens my own thinking and also allows me to use AI to highlight my blind spots.
Which leads me to the question I wish I would’ve asked AI earlier:
“Based on all this interview data, and what you now know about my understanding, what trends and takeaways did I miss? Or what else should I be paying more attention to?”
This way I can use AI to scale my perspective and maybe even arrive at a completely different set of conclusions.
It’s one of many nuggets I took away from this episode so I hope you enjoy the conversation as much as I did 👇
How much did you enjoy this issue?Never hesitate to reply with feedback too :) |
Meet the Dive partners
I made a list of my favorite products and asked them to come on as sponsors of the newsletter/podcast. They said yes 🥹
The #1 way to support Dive Club is to check them out👇
Framer → How I build my websites
Genway → How I do research
Granola → How I take notes during CRIT
Jitter → How I animate my designs
Lovable → How I build my ideas in code
Mobbin → How I find design inspiration
Paper → How I design like a creative
Raycast → How I stay in flow while I work
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