Enhancing Collaboration Tools Through Better UX

AI products like Cursor, Bolt and Replit are shattering growth records not because they're "AI agents". Or because they've got impossibly small teams (although that's cool to see 👀). It's because they've mastered the user experience around AI, somehow balancing pro-like capabilities with B2C-like UI. This is product-led growth on steroids. Yaakov Carno tried the most viral AI products he could get his hands on. Here are the surprising patterns he found: (Don't miss the full breakdown in today's bonus Growth Unhinged: https://lnkd.in/ehk3rUTa) 1. Their AI doesn't feel like a black box. Pro-tips from the best: - Show step-by-step visibility into AI processes - Let users ask, “Why did AI do that?” - Use visual explanations to build trust. 2. Users don’t need better AI—they need better ways to talk to it. Pro-tips from the best: - Offer pre-built prompt templates to guide users. - Provide multiple interaction modes (guided, manual, hybrid). - Let AI suggest better inputs ("enhance prompt") before executing an action. 3. The AI works with you, not just for you. Pro-tips from the best: - Design AI tools to be interactive, not just output-driven. - Provide different modes for different types of collaboration. - Let users refine and iterate on AI results easily. 4. Let users see (& edit) the outcome before it's irreversible. Pro-tips from the best: - Allow users to test AI features before full commitment (many let you use it without even creating an account). - Provide preview or undo options before executing AI changes. - Offer exploratory onboarding experiences to build trust. 5. The AI weaves into your workflow, it doesn't interrupt it. Pro-tips from the best: - Provide simple accept/reject mechanisms for AI suggestions. - Design seamless transitions between AI interactions. - Prioritize the user’s context to avoid workflow disruptions. -- The TL;DR: Having "AI" isn’t the differentiator anymore—great UX is. Pardon the Sunday interruption & hope you enjoyed this post as much as I did 🙏 #ai #genai #ux #plg

For years, companies have invested in portals and central hubs full of knowledge articles, training, onboarding content, and support. But let’s be honest: the experience is often clunky. Customers don’t want to browse a library. They want answers. Now, AI-powered search promises a shortcut: ask a question, get the answer. I often find myself in healthy debates with UX teams—will everything just become a search bar? Do we even need structured design anymore? But here’s the reality: AI is only as good as the content, structure, and experience behind it. Without thoughtful UX, even the best AI surfaces irrelevant or confusing results. In complex B2B environments, that erodes trust instead of building it. Leading teams are taking a layered approach: Start with structure. Map what customers need at each phase: onboarding, adoption, troubleshooting. Design with intent. Build role specific, outcome-driven experiences not just content dumps. Then layer in AI. Use it to accelerate access, not replace design. The future isn’t “search bar over sitemap.” It’s purposeful UX amplified by AI so customers get what they need, when they need it. How are you evolving your self-serve strategy? #DigitalExperience #CustomerSuccess #AI #SelfService #B2B #CustomerJourney

Ensuring collaboration is central to a product's success during the UX strategy phase begins with uncertainty about where to start. ➡️ It's important to start by integrating resources and knowledge from various areas of expertise. Here's a combined approach on my experience to get a successful results and great user satisfaction rate 1️⃣ Get Smart Early in the Process: Involvement: Bring in PMs, Engineers, Designers, Researchers, and key stakeholders early to gain insights. Understanding: Focus on the "4W's" (Who, What, When, Where), technical impact, and project scope.
 2️⃣ Learn and Explore: Understanding Customer Needs: Identify customer pain points and their actual needs. Analysis and Metrics: Make assumptions, conduct competitive analysis, and define success metrics and current statistics.
 3️⃣ Define Problem: Validation and Conceptualization: Validate the problem, draft high-level concepts, and define hypotheses for testing.
 4️⃣ Design: Concept Creation: Develop low-fidelity (low-fi) concepts and involve researchers for testing. Collaboration: Show concepts to Tech and PMs, and address technical challenges.
 5️⃣ Re-iterate: Feedback and Refinement: Fix the main journey (happy path), take internal and external feedback, and implement changes. Testing: Conduct another round of testing.
 6️⃣ Hand off to Development: Finalization and QA: Design the final prototype, perform QA testing, and ensure all workflows are correct. Cross-Platform Check: Ensure designs are optimized for all viewports. Approval: Get sign-off from all parties before handing over to development.
 7️⃣ Launch and Monitor: Post-Launch Feedback: After launching, gather feedback through success metrics and third-party tools. Client and User Feedback: Seek feedback from real clients and conduct user interviews. Refinement: Address major feedback issues, prioritize, and monitor. Useful Resources ✅ Ux Vision — A vision is an aspirational view of the experience users will have with your product, service, or organization in the future. https://lnkd.in/gPPY-zPJ https://lnkd.in/g8Rc9pzp ✅ Outcome over Outputs — Work towards purposeful outcomes (problems solved, needs addressed, and real benefits) leads to better results. https://lnkd.in/gAFX_Wxw ✅ OKR in UX — Define objectives and measurable key results to guide and track UX work. https://lnkd.in/gDYvreN2 ✅ UX Goal Analytics — Focus on UX goals to drive analytics measurement plans, rather than tracking superficial metrics. https://lnkd.in/g3QmZqBd #UxStrategy #TransitionToUx #UxCoach #BeAvailable