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🚨 BREAKING: Claude 4 just made every dev tool outdated. If you’re building agents, coding copilots or AI workflows - pause everything and read this. Anthropic dropped code-native super intelligence and it’s wild: 🧵👇

Most product teams spend 80% of their time perfecting solutions and 20% defining problems. It should be the reverse. No amount of polish can save a poorly framed foundation. Stop optimizing solutions to the wrong problems.

The companies winning in 2025 aren't just building better products. They're building better systems for building products. What's the biggest flow blocker in your product org?

Design systems were built for humans. Your next user? Might be a machine. And it can’t parse vibes. It needs protocols. linkedin.com/pulse/design-s…

Design systems are evolving: 🔲 From components → structured protocols 🧠 From visual styling → encoded intent 🤝 From teams-only → AI agents + workflows If you're still documenting components, you're behind. linkedin.com/pulse/design-s…

Just read the state of AI in design by Designer Fund - 51% of design teams are building autonomous AI systems, yet 25% still desperately need "enhanced UI/UX generation." The issue isn't more AI tools—it's that your design systems weren't built for AI consumption.

AI-ready design systems unlock game-changing capabilities: 🎯 Contextual design generation ⚡ Automated design-to-dev pipelines 📚 Self-updating documentation 🔍 Proactive quality monitoring Stop managing tools. Start building infrastructure.

Forget “design system maturity.” The real question: Can your system teach an AI what good design looks like? If not, it's time to evolve it.

Your next design system user won't be human—it'll be an AI agent. Three priorities for design leaders: Audit your AI integration overhead Assess if AI can actually use your systems Invest in AI-native infrastructure The teams getting this right will define tomm's standards.

After working with a ton of enterprise design systems, we've learned this truth: depth beats breadth every time. Start narrow, go deep, and expand from a position of proven success. linkedin.com/pulse/power-pu…

Design system implementation should be narrow but deep: • Build credibility with quick wins • Reduce resistance with minimal change • Create momentum through early success • Establish patterns for expansion What core problem is your design system solving first?

Your design system isn't failing because of technology—it's failing because of ambiguity. The most successful systems solve ONE critical problem exceptionally well before expanding. Depth beats breadth. Focus on your Minimum Viable Purpose first. #DesignSystems #ProductStrategy

Most teams equate usage = design systems adoption. But the stories you hear from your org says something different. lnkd.in/g6-BdTaQ

The bottleneck won't be AI. It'll be your org chart. Your teams are ready to leverage AI, but is your organizational structure? When AI generates hundreds of variants in seconds, traditional hierarchies become constraints.

AI is here. The skills are developing. But who owns what in this new world? Who curates prompts? Who approves AI-generated variants? Who ensures compliance? These roles don't fully exist yet, and that's where the real bottleneck lives—not in the technology.

When responsibilities blur between design and development, when AI generates hundreds of variants instantly, your hierarchy becomes the limiting factor. The most successful organizations aren't just implementing AI tools—they're reimagining how teams collaborate around them.