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Home ›› Artificial Intelligence ›› Conversational AI

Conversational AI

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Orchestrating LLMs, AI Agents, and Other Generative Tools

  • AGI, AI Agents, AI Ecosystem, AI Integration, AI Orchestration, Artificial Intelligence, Conversational AI, Digital Twins, LLM

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
IDEAS IN BRIEF
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.
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5 min read

You Can Automate a 787 — You Can Automate a Company

  • AI Agents, Artificial Intelligence, Conversational AI, Digital Transformation, Human-Centered Design, LLM, Organizational AI, User Experience, Voice Interfaces

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
IDEAS IN BRIEF
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.
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8 min read

Is RAG the Future of Knowledge Management?

  • AI-Powered Knowledge Management, Artificial Intelligence, Conversational AI, LLM, Retrieval Augmented Generation (RAG), Semantic Search

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

Article by Daniel Lametti, Josh Tyson
IDEAS IN BRIEF
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.
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5 min read
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