Agentic AI is the latest foray into big-bet promises for businesses and society at large. While promising autonomy and efficiency, AI agents raise fundamental questions about their accuracy, governance, and the potential pitfalls of over-reliance on automation.

Does this story sound vaguely familiar? Hold that thought. This discussion about the over-under of certain promises is for you.

Show Notes

The economics of LLMs and DeepSeek R1 (00:00:03)

Reviewing recent developments in AI technologies and their implications
Discussing the impact of DeepSeek’s R1 model on the AI landscape, NVIDIA

The origins of agentic AI (00:07:12)

Status quo of AI models to date: Is big tech backing away from promise of generative AI?
Agentic AI designed to perceive, reason, act, and learn

Governance and agentic AI (00:13:12)

Examining the tension between cost efficiency and performance risks [LangChain State of AI Agents Report]
Highlighting governance concerns related to AI agents

Issues with agentic AI implementation (00:21:01)

Considering the limitations of AI agents and their adoption in the workplace
Analyzing real-world experiments with AI agent technologies, like Devin

What's next for complex and agentic AI systems (00:29:27)

Offering insights on the cautious integration of these systems in business practices
Encouraging a thoughtful approach to leveraging AI capabilities for measurable outcomes

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Agentic AI: Here we go again