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Home ›› Artificial Intelligence ›› AI Orchestration

AI Orchestration

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AI’s promise isn’t about more tools — it’s about orchestrating them with purpose. This article shows why random experiments fail, and how systematic design can turn chaos into ‘Organizational AGI.’

Article by Yves Binda
Random Acts of Intelligence
  • The article critiques the “hammer mentality” of using AI without a clear purpose.
  • It argues that real progress lies in orchestrating existing AI patterns, not chasing new tools.
  • The piece warns that communication complexity — the modern Tower of Babel — is AI’s biggest challenge.
  • It calls for outcome-driven, ethical design to move from random acts to “Organizational AGI.”
Share:Random Acts of Intelligence
5 min read

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

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

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