Flag

We stand with Ukraine and our team members from Ukraine. Here are ways you can help

Get exclusive access to thought-provoking articles, bonus podcast content, and cutting-edge whitepapers. Become a member of the UX Magazine community today!

Home ›› Artificial Intelligence ›› Conversational AI

Conversational AI

Read these first

Forget chatbots — Agentic AI is redefining how work gets done. Discover the myths holding businesses back and what it really takes to build AI with true agency.

Article by Josh Tyson
Five Myths Debunked: Why Agentic AI Is Much More Than Chatbots
  • The article reframes Agentic AI not as a tool, but as a strategic approach to automating high-value tasks through orchestration and dynamic objectives.
  • It argues that success with Agentic AI lies in starting small, experimenting quickly, and integrating agents around outcomes — not traditional workflows.
  • The piece emphasizes the need for open, flexible platforms that enable multi-agent collaboration, rapid iteration, and seamless integration with legacy systems.
Share:Five Myths Debunked: Why Agentic AI Is Much More Than Chatbots
8 min read

Can AI agents fix the broken world of customer service? This piece reveals how smart automation transforms stressed employees and frustrated customers into a smooth, satisfying experience for all.

Article by Josh Tyson
AI Agents in Customer Service: 24×7 Support Without Burnout
  • The article explains how agentic AI can improve both customer and employee experiences by reducing service friction and alleviating staff burnout.
  • It highlights real-world cases, such as T-Mobile and a major retailer, where AI agents enhanced operational efficiency, customer satisfaction, and profitability.
  • The piece argues that companies embracing AI-led orchestration early will gain a competitive edge, while those resisting risk falling behind in customer service quality and innovation.
Share:AI Agents in Customer Service: 24×7 Support Without Burnout
6 min read

AI agents are getting smarter — but can they truly work together? Meet MCP, the open-source protocol quietly reshaping how machines connect, collaborate, and get things done.

Article by Josh Tyson
What to Know About Model Context Protocol (MCP)
  • The article introduces MCP — a new way to help AI agents easily work with business tools.
  • It shows how MCP could change how we use software by letting AI control all our tools through one interface.
  • The article sees MCP as a big step toward building smarter, more flexible AI systems in the future.
Share:What to Know About Model Context Protocol (MCP)
5 min read

Unlock the future of AI with open, modular systems that power hyperautomation. Discover how orchestrating LLMs and AI agents leads to smarter, scalable innovation.

Article by Robb Wilson, Josh Tyson
Orchestrating LLMs, AI Agents, and Other Generative Tools
  • The article explores how conversation connects LLMs, AI agents, and generative tools in business automation.
  • It stresses the need for open, modular systems over relying on single vendors for scalability and innovation.
  • The article highlights the drawbacks of isolated LLMs and emphasizes interconnected systems for effective AI-driven workflows.
  • It encourages embracing the complexity of AI ecosystems to enable flexibility, iteration, and hyperautomation.
Share:Orchestrating LLMs, AI Agents, and Other Generative Tools
5 min read

If we can automate a 787, why not an entire company? Discover how conversational AI and intelligent ecosystems are reshaping the future of work.

Article by Robb Wilson
You Can Automate a 787 — You Can Automate a Company
  • The article explores how automating a plane cockpit led to deeper insights about business automation.
  • It shows how conversational AI and agent-based systems can reduce cognitive load and improve decision-making.
  • It argues that organizations need intelligent ecosystems — not just tools like ChatGPT — to thrive in the age of automation.
Share:You Can Automate a 787 — You Can Automate a Company
8 min read

Discover how RAG, semantic search, and Graph RAG are reshaping AI-driven information retrieval.

Article by Daniel Lametti, Josh Tyson
Is RAG the Future of Knowledge Management?
  • The article explores RAG as a way to improve AI-driven knowledge management.
  • It explains how RAG helps LLMs pull in external data for more accurate answers without retraining.
  • The piece highlights semantic search and Graph RAG as key methods for organizing and finding information.
  • It shows how UX designers can use RAG to create smarter AI-powered knowledge systems.
Share:Is RAG the Future of Knowledge Management?
5 min read

Join the UX Magazine community!

Stay informed with exclusive content on the intersection of UX, AI agents, and agentic automation—essential reading for future-focused professionals.

Hello!

You're officially a member of the UX Magazine Community.
We're excited to have you with us!

Thank you!

To begin viewing member content, please verify your email.

Tell us about you. Enroll in the course.

    This website uses cookies to ensure you get the best experience on our website. Check our privacy policy and