Is it an agent or not? Andrew Ng says that question is a distraction. Build instead.
Summary
Andrew Ng coined the term "agentic AI" to shift focus from definitional debates to practical development, acknowledging a spectrum of agency rather than a binary classification. He observed that while the term rapidly gained traction in marketing, leading to significant hype, genuine business progress in developing agentic AI systems has also been substantial, though not matching the pace of marketing adoption. Ng's intent was to encourage building and iterating on AI systems with varying degrees of autonomy, rather than getting bogged down in semantic arguments about what constitutes a true "agent."
Key takeaway
For AI product managers evaluating new features, recognize that "agentic AI" describes a range of capabilities, not a single product type. Prioritize understanding the specific degree of autonomy and problem-solving ability your AI system offers, rather than relying on broad marketing labels, to accurately communicate value and manage expectations for your users.
Key insights
Agentic AI describes a spectrum of AI autonomy, emphasizing building over definitional debates.
Principles
- Focus on building over debating definitions.
- Agency exists on a spectrum, not as a binary.
Topics
- Agentic AI
- AI Terminology
- AI Hype Cycle
- AI Development
Best for: AI Researcher, AI Engineer, AI Product Manager
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Editorial summary, takeaway, and curation by AIssential. Original article published by No Priors: AI, Machine Learning, Tech, & Startups.