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What Will AI-first UX Look Like?
AI-first UX is evolving beyond chatbots to integrated, agentic systems that replace traditional forms and dashboards with conversational interfaces and collaborative AI agents.
What: The article, featuring insights from leaders like Vishal Sood (Typeface) and Hector Ouilhet Olmos (AWS Solutions), describes how AI-first UX will collapse enterprise app sprawl. It will shift from disconnected tools to orchestrated environments where AI agents carry context, enabling conversations to replace forms, AI to generate reports, and workflows to become agentic collaborations. Examples include Workday's Sana and Anthropic's Claude Cowork.
Why it matters: This signals a fundamental paradigm shift in enterprise software design, where AI moves from being an additive feature to the core interaction model, demanding new approaches to development, testing, and orchestration for AI agents.
Takeaway: Developers should begin exploring multiagent frameworks and orchestration platforms to prepare for building collaborative human-AI agent experiences rather than traditional form-based applications.
Deep dive
- AI-first UX aims to collapse enterprise app sprawl by integrating AI agents that carry context across workflows.
- The shift is from disconnected tools to orchestrated systems, blending conversational interfaces, visual workspaces, and agentic orchestration.
- Traditional user interfaces like forms will be replaced by adaptive conversations and "interviews" where AI pre-fills information and gathers data dynamically.
- Reporting and dashboards will evolve from static visualizations to narrative copilots generated by AI, explaining insights and suggesting actions.
- Workflows will transform into collaborations between humans and AI agents, with AI orchestrating multi-step processes across systems.
- This requires a fundamental shift from the "desktop metaphor" to designing interfaces that mimic human collaboration patterns like negotiation and interruption.
- New platforms like Workday's Sana (with 300+ skills) and Anthropic's Claude Cowork (with plug-ins for legal/marketing) are examples of this shift.
- Development teams will need to update observability standards, automate AI agent testing, and review multiagent frameworks and orchestration platforms.
Decoder
- Agentic AI: AI systems capable of perceiving their environment, making decisions, and performing actions over an extended period to achieve specific goals, often involving multiple steps and interactions.
- SaaS sprawl: The uncontrolled proliferation of Software-as-a-Service applications within an organization, leading to inefficiencies, increased costs, and data management challenges.
Original article
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