Intro

Speaking to Phillip Maggs on Design of AI had so many💡 moments:1. Want to use AI to get a career advantage? Consuming AI content isn't enough to get ahead, you need to experiment with the new material. Stretch what you believed was possible and you'll gain new capabilities.2. New careers and role are being defined right nowGenAI makes it possible for anyone to quickly learn about a topic or skill. You might think you're average but can quickly put together a unique skill profile that makes you a unicorn, especially if you're more committed to being curious about new technologies and how to leverage them.3. Much of design should be automatedWe forget that a lot of design tasks are literal assembly-line outputs: Banners, emails, ad variants. These rightfully should be automated because they exist in the world for such a short period. However, assets that represent your brand to millions or which will be in market for years must be hand-crafted.4. Design systems and brands are rulesThe more we codify what our products and brands should be, the more we unlock the augmenting powers of AI. Phillip imagines that a day will come when the LLMs about our brands will shine light on ideas we otherwise wouldn't have considered because of our own biases.5. A lot of AI design products are "party tricks"Sure a tool that can generate designs based on text prompts are cool but are they significantly saving time? Are they aware of what qualifies a good output for your brand? Do they understand how you communicate with customers? The outcome of these tools likely is not a significant ROI.Listen on Spotify | Listen on Apple

AI tool of the week: Cove.ai

Cove.ai is like Miro meets Claude. You can prompt and build assets, just like in Claude. But what makes this tool fascinating is that you can save our work to a visual board and invite others to collaborate with you.

The most surprising finding from using this platform is recognizing that in a typical project I’m outputting so many assets. The volume makes infinite scroll interfaces painful, and even makes Claude Project’s interface seem deficient. The visual board interface is much more functional since I can sort dozens of cards into a work surface that makes sense.

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Our First 20 Episodes: 20 Lessons for How to Advance Your Career in the Era of AI

We’re being taught to fear AI and how it is expected to impact our jobs and workplaces. But our guests see distinct opportunities for us to embrace this time as an opportunity to advance our careers.

Lesson 1: Embrace AI as a tool to enhance creativity, not replace It

Maarten Walraven-Freeling, our guest on Episode 3, highlighted how AI tools like AIVA and Google Deep Mind's LIA can empower musicians to generate new music and expand their creative possibilities. Rather than fearing AI as a threat, musicians can leverage these advancements to enhance their craft and explore uncharted artistic territories.

Episode: The future of music in the era of generative AIListen on Spotify | Listen on Apple

Lesson 2: Understand the evolution of AI interfaces to design better products

In Episode 4, Emily Campbell traced the history of AI interfaces, from early chatbots to voice assistants and brain-computer interfaces. By understanding this evolution, product teams can better anticipate future trends and design AI products that are intuitive and user-friendly.

Episode: How AI is reshaping UX and the new role for designersListen on Spotify | Listen on Apple

Lesson 3: Address the copyright challenges posed by generative AI

Virginie Berger, in Episode 5, shed light on the ethical and legal implications of AI models trained on copyrighted data. Creatives, businesses, and policymakers must work together to establish fair compensation models and licensing frameworks to protect artists' rights in the age of generative AI.

Episode: GenAI's copyright problem: Training & derivative copiesListen on Spotify | Listen on Apple

Lesson 4: Prioritize problem-solving over technology when building AI startups

Ben Yoskovitz, our guest on Episode 6, emphasized the importance of focusing on real-world problems and customer needs rather than solely on AI technology. Startups that prioritize solving genuine challenges are more likely to achieve product-market fit and attract investment.

Episode: Venture building: Why AI products may fail Listen on Spotify | Listen on Apple

Lesson 5: Approach emerging technologies as an enabler of people, not magic

In Episode 7, Dr. Llewyn Paine cautioned against blindly embracing the hype surrounding emerging technologies like generative AI. To find the value of a technology we need to understand how people and teams work. The most valuable opportunities are buried in behaviors and assessing what they’re willing to adopt.

Episode: The secrets to researching potential emerging tech productsListen on Spotify | Listen on Apple

Lesson 6: Leverage AI to create personalized behavior change journeys

Dr. Amy Bucher, our guest on Episode 9, discussed how AI can revolutionize behavior change interventions by enabling true personalization. By tailoring communication and interventions to individual needs and contexts, AI can drive more effective outcomes in healthcare, education, and marketing.

Episode: AI can innovate behavior change strategies & transform personalization Listen on Spotify | Listen on Apple

Lesson 7: Focus on AI native workflows and integrations to stay ahead of the curve

In Episode 1, Peter Van Dijck explored the rapid growth of the generative AI ecosystem, with a surge in AI-powered consumer web products. To thrive in this dynamic landscape, developers should prioritize building AI-native workflows and seamlessly integrating multiple AI tools into their products.

Episode: Designing AI products: Building effective products with LLMsListen on Spotify | Listen on Apple

Lesson 8: View AI as a design material that enables intelligent & radically adaptive experiences

Josh Clark & Veronika Kindred, our guests on Episode 19, introduced the concept of “sentient design,” where AI becomes an integral material in shaping intelligent interfaces. To effectively design with AI, product teams must understand its capabilities, limitations, and potential impact on user experience. What were once static user experiences can be radically adaptive.

Episode: Authors of Sentient design: AI-powered self-aware experiencesListen on Spotify | Listen on Apple

Lesson 9: Rethink organizational structures and embrace AI to remain competitive

JP Holecka, in Episode 1, emphasized the need for advertising agencies to fundamentally adapt their operating models in response to AI's transformative potential. Traditional agencies must embrace change, form new business units, and develop AI-driven solutions to meet evolving client needs and remain competitive.

Episode: How AI is changing ad agencies & the creative processListen on Spotify | Listen on Apple

Lesson 10: Start using AI as a material to see what possible and what isn’t

In Episode 10, Alexandra Holness highlighted the importance of viewing AI as a new tool within the designer's toolkit. The sooner you begin integrating it, the sooner you’ll learn how easy/difficult it is to work within your particular situation. Avoid the search for perfect because you’re going to need to adapt your expectations to meet what the technology can actually deliver.

Episode: AI is disrupting the design & product delivery process [Lessons for startups, enterprise & UX]Listen on Spotify | Listen on Apple

Lesson 11: Recognize your role as an innovator: Are you a sea captain or a pirate?

Nick Sherrard, in Episode 11, discussed who he has seen driving innovation. There are archetypes. Firstly, the sea captain is the leader who has a destination in mind but not the expertise. Secondly, the pirates are misfits exploring new places and trying wild new techniques. Which are you? How can build the right team and allies to be able to align vision + expertise, passion + experimentation?

Episode: Innovation lessons for brands and product teams investing into AIListen on Spotify | Listen on Apple

Lesson 12: Codify your experience to scale your impact

Trisha Causley, in Episode 12, shared how AI can empower content designers by automating repetitive tasks and scaling their expertise. You add so much more value to your teams than you understand. Find ways to codify that knowledge into specific guidelines, key insights, and specifications. You then can unlock the real potential of LLMs.

Episode: Content design: How creatives are leveraging prompt engineering to innovate ecommerce platformsListen on Spotify | Listen on Apple

Lesson 13: Avoid innovation traps and learn what the technology is good and bad at

In Episode 13, Scott Jenson cautioned against blindly chasing hype cycles and urged product teams to prioritize customer needs and sustainable business models when implementing AI solutions. And more importantly, be the person on the team that knows what GenAI can and can’t do well so you avoid innovation traps.

Episode: Unlocking AI product success: Coaching teams to navigate uncertainty & design risksListen on Spotify | Listen on Apple

Lesson 14: Need to be specific about how to use AI

Jess Holbrook, our guest on Episode 14, stressed the importance of understanding what AI is. It might be easy to tell a team to go build with AI. But can we grasp its strengths, limitations, and ethical considerations? Do we have guidelines and principles that guide our ethos related to leveraging AI and products overall?

Episode: Researching & building responsible AI within tech’s biggest platforms Listen on Spotify | Listen on Apple

Lesson 15: Embrace radical transparency and challenge assumptions to deliver impactful AI solutions

In Episode 15, Arpy Dragffy, the show’s co-host, discussed the value of “radical transparency” in consulting and AI product development. By engaging in honest and sometimes uncomfortable conversations, teams can uncover hidden assumptions and ensure they are building products that genuinely meet customer needs. Quite often we’re using the wrong solution and tackling the wrong problem. AI can unlock new horizons for teams that think beyond the bounds of the obvious.

Episode: Futures design: Build AI products that customers want & find valuable use casesListen on Spotify | Listen on Apple

Lesson 16: Treat this as a time to experiment

Yasemin Cenberoglu, our guest on Episode 16, detailed her journey of being the first designer working on Microsoft’s Copilot in secret with OpenAI. It required blue-sky thinking and plenty of experiments to identify unexpected outcomes of this new probabilistic technology. You’ll discover the need to create guardrails and shift your thinking about how a product should be released.

Episode: Service design of AI: Designing the first Copilot w/ Microsoft & OpenAIListen on Spotify | Listen on Apple

Lesson 17: Go beyond the usual KPIs and find a way to measure time well spent

In Episode 18, Dr. Kristie J. Fisher emphasized the importance of finding the right KPIs and ways of evaluating whether the experience of using AI is time well spent. Users want product experiences that are enjoyable. Find ways to leverage AI to make user experiences more enjoyable and supportive based on the situational user needs.

Episode: Immersive GenAI experiences: Video games' KPIs & path to joy Listen on Spotify | Listen on Apple

Lesson 18: Use AI to build expertise in areas that complement you

Phillip Maggs, our guest on Episode 20, challenged the assumption that you need to be great to succeed. He sees technology mixed with curiosity as your path of unlocking new capabilities. Learn how to be average in many areas but connect those capabilities into something distinct and powerful. Engineers can now explore their impact on design. And creatives can better explain and demonstrate their ideas.

Episode: Future of Design: Leveraging Design Systems & Brand to Automate WorkflowsListen on Spotify | Listen on Apple

Lesson 19: Leverage AI analyze data in bulk

Weidan Li, our guest on Episode 8, explained how GenAI is imperfect at analyzing data but that as the models get better it can greatly expand how much and how deeply we can analyze data sets. This opens opportunities to unlock insights that may have otherwise not been considered because of the effort required. Remember, it shouldn’t replace human insight generation.

Episode: Case studies: Leveraging AI to build conversational bots & analyze conversationsListen on Spotify | Listen on Apple

Lesson 20: Automation is coming and we need to prepare for it

A common theme from many guests has been that automation will happen. Many tasks, specifically low-level ones, will be taken over by AI. We need to treat this time as an opportunity to redefine the type of work and level of impact we want to have. We can either be operators of the AI automation platforms or we can envision new ways of using technology that will 10x our impact and 100x the possibilities for our teams. As Phillip Maggs said, have a bias for building with AI, not just consuming AI content.

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