Andrew Hogan, Head of Insights at Figma, talks to Bob Baxley, SVP of Design at ThoughtSpot, about his view on AI’s impact, why it’s so important to design tools well, and what we can learn from history and huge projects like the Apollo Mission.

Weavely is the AI form builder for Figma. You can design a form in Figma, and Weavely will generate a working web form from it. It supports answer piping, conditional logic, AI form generation, and more.

Now you can use the power of AI to generate and expand mindmaps and create visual timelines in FigJam. See examples in the gallery of ready-made FigJam AI prompts.

“Researcher Gus Griffin recently completed one year on artificial intelligence work at Figma. In this conversation with Figma’s Head of Insights, Andrew Hogan, Gus walks through AI feature fatigue, what people really want from artificial intelligence, and how his anthropology background helps him do his work.”

Fast Company calls Figma one of the ​“most innovative companies in applied AI” for boosting creativity and digital collaboration with the OpenAI-powered Jambot plugin for FigJam. Wild to think that it was born out of an internal two-day AI hackathon just eight months ago. (For additional context, see the above interview with Nilay Patel.)

In this episode of the Designing with AI podcast, Mia Blume chatted with Noah Levin, VP of Product Design at Figma, about the emotional ups and downs of the recent acquisition announcement and how it impacted the team, explored the implications of artificial intelligence on creativity and curiosity, leading teams through times of change and learning, decision-making, democratized access to information, and even the concept of love.

Replit Vice President of Marketing and Design David Hoang talks about how AI is reshaping the future of product design and development, and the role it’s playing in the company’s team and products. On synergy between design, engineering, and AI: ​“Whether you currently work more in engineering or design, AI offers augmentation for you to do both. Engineering and design are on a course to become one tightly woven discipline.”

On hiring with regards to their Artificial Developer Intelligence (ADI) strategy: ​“At Replit, we’ve always leaned towards hiring multidisciplinary designers who understand the technical depth it takes to create software and bring it into the world. Each designer has the output of three to five designers that you’d ordinarily work with. They code, prototype, review pull requests, do unit testing, facilitate research sessions, and run workshops, too.”

A similar concept, but inspired by the Lighthouse web dev tool. This plugin ensures your designs are ​“polished and stakeholder-ready every time, saving you from potential revisions and boosting your design confidence”. 3rd Product of the Day at Product Hunt on December 26th, 2023.

“From lifelike portraits to objects and animals, craft any image you can imagine in just 5 seconds.” Won 2nd Product of the Day at Product Hunt on December 14th, 2023.

An interesting new plugin — get the AI design feedback on either the UX or UI of your mockups. I tried it on an unfinished design, and while some points were somewhat irrelevant, others were spot on. It’s free to play with and worth giving a shot.

A large profile of FigJam AI in Fast Company. ​“Figma’s AI ambitions are clear. Singer noted that ​‘we really do think of AI as playing a central role across the entirety of the platform.’ In theory, that could mean not just better meetings, but more capable coworkers. ​‘In a collaborative environment where you’re working with many people on a project,’ Singer says, ​‘AI really up-levels everyone.’”

Fascinating side-by-side comparison of Midjourney 5.2 and the newly released version 6. The generative art from Midjourney has always felt more realistic and interesting compared to other services, and now the gap appears even larger.

I wonder what that button on Jordan’s micro keyboard does?

Teddy Ni, a co-founder of Magic Patterns backed by Y Combinator, shares an experiment: ​“We taught an AI some Figma designs of a documentation site. It can now generate similar sites using my own custom components on ANY topic I want, ALL within Figma I can also click on any frame and request updates 🤯”. (This reminds me of the feature in Visual Copilot that I wrote about in #136.)

“Discover how you can import all of your existing Jamboard files to fully editable FigJams! From sticky notes to sketches, watch as we demonstrate how to seamlessly transition your Jamboard content into FigJam, where you can harness the full range of FigJam’s interactive capabilities.”

OMG! Figma window is streamed to GPT‑4 Vision, which then provides feedback on the fly narrated in the voice of Steve Jobs. Looking for a way to make this a part of our design crits.

Jordan Singer came up with another wild AI experiment — sketch or design anything in Figma or FigJam and turn it into a functional prototype with one click of a button. This demo is a great example — it built all the functionality correctly based just on a few text labels!

The AI is now integrated into FigJam to ​“help you instantly visualize ideas and plans, suggest best practices, and, of course, automate tedious tasks, so you can focus on the bigger picture.” What started as an experimental widget Jambot is now a first-class part of the product using GPT‑4. I used it this week to create a structure for a presentation which was a useful 0 to 0.1 progression. You can give it a try at the playground or check out how Zander Whitehurst uses it to create crazy flow charts.

I shared the teaser in issue #132, but last week Builder​.io introduced Visual Copilot, ​“a completely reimagined version of the Builder Figma-to-code plugin that will save developers 50–80% of the time they spend turning Figma designs into clean code.” The major difference between Visual Copilot and previous design-to-code tools is a specialized AI model that was trained to solve this problem. The features include one-click conversion, automatic responsiveness, extensive framework and library support, customizable code structures, and easy integration with the existing codebase.

One of the most exciting parts of this announcement is still in private beta and targeted at teams with well-maintained design systems. This feature in Visual Copilot uses AI to map reusable components in your Figma file to those in your code repository and generates code using your existing components when you have them. This could be genuinely useful to get the first rough version ready in no time.

I’m still waiting for access to GPT‑4 Vision, but examples like this make me so excited about possible use cases! Imagine using LLM for a heuristic evaluation or pairing design and sketching sessions.