This is a question I get a lot when mentoring designers on ADPList. From my experience building AI-driven products at Adobe, coding knowledge is not necessary. However, it can help differentiate yourself as someone with a more versatile skill set and improve your collaboration with engineers. Coding can be helpful for quickly prototyping ideas, but I've found that static images are typically sufficient to convey an idea for stakeholder buy-in and user testing without a significant time investment.
Coded prototypes may prove more effective when you're past initial user testing and validation and need to demonstrate how the final experience will behave in higher fidelity, especially for micro-interactions. My go-to vibe coding recommendation is Cursor in combination with hosted models from HuggingFace, Replicate, and Fal. Let me know if you have any more questions.
The most important strategy to gain confidence and build your skillset is to play with the latest AI models and grow your understanding of how they work and what they are capable of. Don't let ideas sit restless in your mind; bring them to life through sketches, prototypes, and presentations. Then share these concepts widely with people you admire, colleagues, and online communities to quickly gather feedback. You'll be surprised how far an idea will go once it is out of your head and you share it with others.
Immerse yourself in what people are creating by following companies and influencers who share valuable content. Some people that I follow on X (Twitter) for personal inspiration: @fofrAI, @icreatelife, @gizakdag, @Pinsky, @cantrell, @jerrod_lew, @bilawalsidhu, @Swopes, @acostin, @lucatac0, @doronstudio, @philz1337x, @rufusd, @javilopen.
Staying current with emerging technology is a critical part of being an AI product designer because your designs are influenced by the latest AI models and trends. The right idea at the right time can make all the difference in your career and shipping a great product to your users. I regularly review what people are sharing on Pinterest, Instagram, X, LinkedIn and more and bookmark what I find interesting to reference it later to help validate an idea. It is beneficial to be an expert in what's happening so people come to you for advice and brainstorm ideas.
In addition, I’ve found it helpful to treat everyday interactions as chances to hear how people view AI and its impact on their lives. This brings a grounded read on what they’re feeling and what they want to see more or less of. It also surfaces blind spots that need attention, often around legal and ethical considerations in model training and datasets.
These are courses I've come across that offer a flexible way to start learning. I haven't enrolled in all of them, so check that content has been updated recently, technology moves fast.
