Maheen Sohail’s Post

Lot's of great discussion here about AI. I'm a fan of the practical application of a technology. One example of disruption in real time: In Product Dev, engineering scarcity is our biggest obstacle. Lots of great ideas die on the vine because the economics don't pencil. GPT+4 Vision can now convert Figma designs into working react components. This is huge. We are one step closer to being able to bring ideas to market without engineering bottlenecks. Why is this interesting? Successful products need to test ideas/experiments quickly. People with the best ideas will suddenly become the most valuable resource in the company.

Just finished the course “Design to Code: Using AI to Build Faster” by Drew Falkman! Check it out: As a student of computer science, I've always looked for methods to learn more about the newest developments in my area of study. With a focus on how AI can improve design intelligence, accelerate design workflows, and facilitate developer handoffs, the course provides a thorough overview of AI's revolutionary role in design. Among the many AI-powered tools Falkman skillfully analyses are industry mainstays like Figma, Magician, and Sprout as well as lesser-known but equally potent design suites like Wondershare Mockitt, Visily, and Uizard.  https://lnkd.in/gseqtxab #softwaredevelopment #artificialintelligence.

How Notion uses RAG and AI Native UX to power its new workspace feature. But what is RAG? RAG (Retrieval-Augmented Generation): → accesses and processes information from various sources. → Improve and include answers from external sources RAG in Notion: → Surfaces relevant information from your workspace based on queries. → retrieves relevant sources of information with Notion pages What are the AI-Native UX elements used in Notion AI? Generated Response with Feedback: → Thumbs up/down for rating AI-generated responses. → Feedback helps the AI improve over time. Reference Pages: → AI surfaces relevant information from your Notion workspace. → Allows verification and deeper understanding. Re-try Button: → Regenerate responses if the initial one isn't satisfactory. → AI formulates a new answer based on your query and workspace context. Copy Button: → Easily copy AI-generated responses. → Share quickly with your teammates IC: Product School --------------------------------------------------------------------- #ai #genai #aipm #pms #pm #productmanagement #productmanagers #DataScience #MachineLearning #RAG #python #data #notion #ux #ui #design

Elicit AI is really a game changer when it comes to doing desk research for ux or really anything. For those who don't know....basically like a google scholar that summarizes articles. I can see it being used by graduate students that want to quickly know if their thesis idea is on the right track or what has been done before. And the ability to just type in normal jargon for what you're looking for is faster than typing all the academic words you have to know if you were to look up articles in google scholar.

AI is like nothing we've ever done. Continuous rapid adjustment is the key. That is why, in the AI-First Product Development Process, the core is a cycle of rapid problem definition & solution development. SPIKE + RITE (Rapid Iterative Testing and Evaluation). Vision Prototype --> Data --> AI Model AI-based solution can start with a simple Python notebook. UX = Glue. UX Provides: - Efficiency - Cost savings - Problem analysis - Customer evaluation - Ideas + Patents. -- Learn to lead AI Projects with UX for AI via 5 unique learning opportunities: https://lnkd.in/gW5FPfVg #UXforAI #UXDesign #UX #Workshop #userexperience #userresearch #AI

How can you apply the design thinking process to build AI-powered products and services? Design thinking is an iterative process of innovation that begins from user understanding to launch and monitoring 🔄. Does the process and methodology remain untouched when it comes to AI? Some steps need to be adapted to be effective in working with AI and to collaborate with data scientists and engineers. 📈 Start 2024 investing in yourself by learning how to apply design thinking to AI. 📖 I address this topic (and much more) in my book Human-Machine Learning https://shorturl.at/hlx48. #desingthinking #artificialintelliegence #book #innovation #design #2024goals #2024planning #2024ready

I couldn't make it to Figma Config this year, but learning about the capabilities of their AI has been super exciting this week. As a frequent user, I really feel like Figma takes the time and does their research to create an intuitive experience in their products. I'm currently on the UI3 + AI waitlist so I haven't gotten to take a crack at it myself yet- but if you have I would love to hear about your experience in the comments! - Have you gotten the chance to try out Figma's new AI? - What are your first impressions? - How do you see the new features improving your workflow?

Exciting thoughts on the dynamic nature of AI and the importance of UX in AI-first product development! 🚀💡 As technology evolves, continuous adaptation becomes paramount. The SPIKE + RITE approach underscores the significance of rapid problem-solving cycles in the AI landscape, enabling efficient problem analysis and solution development.

If Figma's new AI tool upset you, you need to reconsider what value you bring as a designer. AI will replace a lot of these execution-focused tasks to a degree, and if it's not happening now, it'll definitely happen in the future. Start learning how to provide more value past pixels.

“We do not fear the unknown. What we fear is giving up the known.” – Anthony de Mello Many people worry that AI will take over our jobs, but I see it as an exciting opportunity. AI can help us work more efficiently, save time, and boost creativity. If you're concerned about the pace of AI development, I suggest learning the basics in a field you love. For me, it's image generation. Understanding how AI works in one area can give you insights into its broader applications. Figma presented a lot of AI related features yesterday at Config: