Agentic AI: The Future of Intelligent Systems

Naveen Balani
  • 3.3（3則評分）
  • 科技
  • 每月更新

Dive into the fascinating world of Agentic AI—a podcast series exploring the cutting-edge evolution of intelligent systems. From plug-and-play AI marketplaces to transformative applications in smart cities, education, and creative domains, this series unpacks how Agentic AI reshapes industries, enables collaboration, and drives innovation. With a focus on ethical considerations, sustainability, and real-world applications, we navigate the opportunities and challenges of these autonomous agents. Whether you’re an AI enthusiast, a business leader, or simply curious about the future, join us.

  1. 6 天前

    Episode 63: Invest in AI Engineering, Not AI Tools

    Following our last episode on the Agent Economy, this conversation goes deeper into what truly drives success in AI — not tools, but engineering. Agentic AI isn’t a plug-and-play revolution. It’s built through architecture, measurement, resilience, ethics, and sustainability. Tools can spark experimentation, but engineering makes innovation last. Organizations don’t need to replace people; they need to augment engineering talent — strengthening the foundations of reliability, responsibility, and trust. Because the next AI revolution won’t be bought through tools.It will be engineered through people.

    5 分鐘

  2. 10月5日

    Episode 62 : Agent Economy

    In this episode, we explore the rise of the Agent Economy — a world where autonomous AI systems transact, collaborate, and negotiate directly with each other. From supply chains to finance, the possibilities are enormous. We also spotlight Google’s new Agents-to-Payments (AP2) Protocol, an early example of how agents can move beyond recommendations to secure, verifiable transactions. The future of AI is not just about building smarter agents. It is about designing the frameworks, trust systems, and standards that will enable an entire economy of intelligent actors.

    5 分鐘

  3. 9月28日

    Episode 61: Agentic AI is 90% Engineering

    Agentic AI demos often look like magic — agents planning, reasoning, and solving tasks on the fly. But beneath the surface, the reality is clear: building agentic systems is ninety percent engineering. In this episode, we unpack what that really means. From planning and memory to tool use, orchestration, and monitoring, the hardest challenges are not in the model itself, but in the systems built around it. Just as cloud adoption matured through disciplines like DevOps and FinOps, Agentic AI will demand its own engineering maturity. I believe a surge is coming — where the real differentiator will not be who uses the biggest model, but who engineers the most reliable, efficient, and sustainable systems. The magic of Agentic AI lies not in the demo, but in the discipline of the build.

    4 分鐘

  4. 9月21日

    Episode 60: Mobile Agentic AI Agents — Intelligence in Your Pocket

    In this episode, we shift the lens from the cloud to the palm of your hand. Mobile Agentic AI Agents, in my view, represent the next big leap — not abstract copilots in distant data centers, but intelligent collaborators that live on your phone. With sensors, context, and constant connectivity, mobile devices are uniquely positioned to host AI agents that reason, plan, and act. Imagine an agent that organizes your day based on carbon-aware scheduling, manages your health insights on-device, or translates conversations in real time while protecting your privacy. But this revolution comes with challenges. Leaner models, efficient memory, and secure design will be critical. And because adoption will spread fastest through smartphones, the impact will be social as much as technical — shaping lives across communities, cultures, and continents. The question is not whether mobile AI agents will arrive, but how quickly we design them to be smarter, greener, and more responsible.

    6 分鐘

  5. 9月14日

    Episode 59 : From Copilot to CoThinker

    In this episode, we move beyond the familiar role of AI as a coding assistant and explore its evolution into a reasoning partner. Starting with code may feel fast, but it often leads to building the wrong thing, beautifully. Copilots accelerate typing, but they do not challenge assumptions or highlight trade-offs. CoThinkers, on the other hand, help define intent, weigh options, and model choices before a single line of code is written. They collaborate on design, prioritize security, reliability, and sustainability, and ensure that clarity comes before execution. The future of AI is not about typing faster. It is about thinking better. This episode unpacks what that shift means for how we design, build, and collaborate with intelligent systems.

    4 分鐘

  6. 9月7日

    Episode 58 : 10 Actionable Strategies for Sustainable AI

    In this special episode, we pause the pace to reflect on what it truly means to build responsible AI. Beyond the buzz of agents and copilots lies a growing environmental cost — from energy and water use to emissions at scale. So how do we unlock AI’s full potential without compromising the planet? We walk through 10 practical, actionable strategies — from prompt optimization to carbon-aware scheduling, local execution, model right-sizing, and lean agent workflows — all designed to help you build AI that’s not just powerful, but sustainable by design. 🌱 A must-listen for developers, architects, and AI leaders looking to scale responsibly.

    7 分鐘

  7. 8月31日

    Episode 57 : Escaping the AI Content Loop: Compression Without Context

    We scroll. We consume. We share. But how much of what we engage with is truly original thought—and how much is just a reflection of a reflection? In this episode, we explore the AI content loop: how insights are compressed, repackaged, and rephrased until meaning fades. From policy reports to scientific research to thought leadership, we unpack what gets lost in translation—and how to break free from the cycle. Tune in to discover why thinking clearly and creating with intent is the new edge in an age of automated compression.

    6 分鐘

  8. 8月24日

    Episode 56 : Reasoning in Agentic AI: Open-Ended Thinking vs. Closed-Ended Execution

    This episode will explore how Agentic AI systems “think” and “reason”—examining the difference between open-ended exploration (creative, generative, speculative) and closed-ended reasoning (focused, deterministic, goal-specific). We’ll discuss: When to use each type of reasoning in AI workflows. The risks of open-ended thought (e.g., hallucination, inefficiency) vs. the limitations of closed-ended logic (lack of innovation, rigidity). How to design agentic systems that balance both—using open-ended reasoning for ideation and exploration, and closed-ended reasoning for execution and precision. The role of prompt design, planning agents, and model selection in shaping how “thought” happens inside AI systems. The podcast will also touch on environmental impact—how sprawling open-ended reasoning can drive up compute unnecessarily if not constrained—and how to architect for leaner, purposeful thinking.

    5 分鐘
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3.3
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簡介

Dive into the fascinating world of Agentic AI—a podcast series exploring the cutting-edge evolution of intelligent systems. From plug-and-play AI marketplaces to transformative applications in smart cities, education, and creative domains, this series unpacks how Agentic AI reshapes industries, enables collaboration, and drives innovation. With a focus on ethical considerations, sustainability, and real-world applications, we navigate the opportunities and challenges of these autonomous agents. Whether you’re an AI enthusiast, a business leader, or simply curious about the future, join us.

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