Return on Intelligence

Daniel Anderson
  • 5.0（1則評分）
  • 科技

Return on Intelligence is the go-to show for forward-thinking business leaders, IT professionals, and decision-makers who understand that AI isn’t just a trend—it’s the ultimate investment in the future of work. While most AI discussions stay theoretical, we cut through the noise to focus on real-world applications, success stories, and strategies that drive productivity, efficiency, and business growth. From scaling businesses and optimizing operations to leveraging Microsoft Copilot and automation, we explore how AI-powered intelligence delivers tangible returns. If you’re ready to turn AI from a concept into a competitive advantage, this is your roadmap to making it happen.

集數

  1. 6月30日

    Copilot Tuning, Multi-Agent Systems, and Live AI Agent Creation

    In this episode of Return on Intelligence, Abram and I dive deep into the transformative announcements from Microsoft Build 2025, exploring how AI agents are fundamentally reshaping workplace productivity. Fresh from his experience at Build, Abram shares exclusive insights on Microsoft's revolutionary multi-agent orchestration capabilities and the new Copilot tuning features that are set to change how businesses approach AI automation. We explored Abram's firsthand experience at Microsoft Build 2025, where he presented on stage about the latest developer tools for AI agents. The heart of our discussion focused on two groundbreaking capabilities: Copilot tuning, which allows businesses to fine-tune models with their specific data and formats, and multi-agent orchestration, which enables agents to work together in sophisticated hierarchies to accomplish complex tasks. We discussed how Copilot tuning differs from traditional knowledge grounding by actually training models to consistently output in specific business formats, making it ideal for structured processes like legal file notes or financial reports. Meanwhile, multi-agent orchestration represents a paradigm shift from monolithic AI systems to specialized agent teams that can handle increasingly complex workflows. The episode culminated with a live demo where Abram built a functional Microsoft Build reception desk agent in real-time, showcasing just how accessible and powerful these new tools have become for everyday users. Key Insights Fine-tuning revolution: Copilot tuning creates models that reliably output in specific business formats, moving beyond simple knowledge grounding to ensure consistent, structured results for critical business processes.Multi-agent architecture: The shift to multi-agent systems enables AI to handle complex, multi-step tasks through specialized agents working together, potentially accessing hundreds of tools through hierarchical organization.Microservices for AI: Multi-agent systems mirror the microservices architecture revolution, allowing different teams to build and iterate on specialized agents that communicate through natural language rather than rigid APIs.Democratized agent building: The new agent builder in Microsoft 365 Copilot makes creating powerful AI agents accessible to end users in minutes, not hours or days of development work.Human-AI collaboration evolution: The future workplace will feature humans as both managers of agent fleets and co-founders working alongside AI thought partners in collaborative relationships.Professional development pathway: Agents can evolve from simple no-code solutions to sophisticated pro-code implementations, allowing successful agents to scale across entire organizations with proper governance.Timestamps 00:00 - 03:15: Build conference overview and Abram's presentation experience 03:15 - 12:30: Deep dive into Copilot tuning capabilities and business applications 12:30 - 18:45: Multi-agent orchestration and the future of AI workplace integration 18:45 - 22:00: Discussion on AI's impact on jobs and the augmentation vs replacement debate 22:00 - 39:00: Live demo building a Microsoft Build reception desk agent 39:00 - 48:50: Agent sharing, scaling, and the evolution from no-code to pro-code development Connect with the Hosts Daniel Anderson: LinkedInAbram Jackson: LinkedIn

    48 分鐘

  2. 6月28日

    ChatGPT vs Copilot: I was completely wrong about this

    Summary In this conversation, Daniel Anderson and Abram Jackson discuss the evolving landscape of AI, particularly focusing on Microsoft's Copilot and its comparison with ChatGPT. They delve into the quality of responses generated by these AI tools, the significance of reasoning models, and the introduction of new agents like Researcher and Analyst. The discussion highlights the practical applications of these technologies in enhancing workplace productivity and the future implications of AI in various industries. Takeaways The quality of AI responses varies significantly between different models.Microsoft 365 Copilot is designed for workplace productivity, not creative writing.Reasoning models are a new frontier in AI development.Deep research capabilities can drastically reduce the time needed for information gathering.The Researcher agent can access and analyze all work-related data.AI tools are meant to assist, not replace human jobs.Governance and security are critical in deploying AI in organizations.The orchestrator plays a vital role in modern AI functionality.AI can help identify gaps in knowledge and improve decision-making.The future of AI in the workplace is focused on enhancing human capabilities.  Chapters 00:00 Introduction and Context Setting05:05 Quality of AI Responses: Copilot vs ChatGPT12:04 Understanding Reasoning Models in AI25:08 Deep Research and Its Impact on Productivity26:32 Introduction to Microsoft 365 Copilot Researcher27:30 Utilizing Researcher in Work Contexts29:33 Security and Data Management in Researcher34:03 Exploring the Analyst Agent39:01 The Future of AI Agents in Business43:32 Upcoming Features and Enhancements at Build

    48 分鐘

  3. 6月27日

    Agent Swarms and Beyond

    In this conversation, Daniel Anderson and Abram Jackson explore the rapid evolution of AI interfaces, focusing on the transition from traditional search to conversational AI and the emergence of agent swarms. They discuss the importance of understanding the differences between automations and agents, the significance of prompt engineering, and the challenges of integrating AI into daily workflows. The conversation emphasizes the need for users to adapt to new habits rather than skills, as well as the potential of specialized agents working collaboratively to enhance productivity. Takeaways AI interfaces have evolved from transactional to conversational.Agent swarms represent a new frontier in AI collaboration.The rapid pace of AI development can create feelings of falling behind.Specialized agents can work together to perform complex tasks.Understanding the difference between automations and agents is crucial.Conversational AI is becoming essential in business applications.Prompt engineering is important for developers, not end users.Chat interfaces are both powerful and challenging to navigate.Integrating AI into daily workflows requires new habits.The future of AI is promising and not a passing fad.

    45 分鐘

  4. 4月16日

    The Doer Mindset - Why AI Rewards Action-Takers

    Join Daniel Anderson and Abram Jackson in this insightful episode of the Return on Intelligence podcast where they explore why a "doer mindset" is crucial for success in the AI era. Learn how executives can drive AI adoption, why perfect implementation plans are the enemy of progress, and get insights on the future of AI from Microsoft's Abram Jackson. TIMESTAMPS:00:00 - Introduction and welcome back03:12 - Shopify CEO's leaked letter on AI adoption05:59 - The importance of executive leadership in AI implementation08:24 - Microsoft's approach to AI adoption11:28 - The "Doer Mindset" concept explained15:43 - Why people get stuck in inaction traps18:46 - Process, frameworks, and data: necessary but not sufficient20:01 - Why waiting for perfect AI implementation is a mistake22:40 - Building a culture ready for AI innovation24:09 - AI memory features and their potential impact in work contexts26:10 - Balancing governance with implementation speed28:12 - Preview of Microsoft Build and upcoming agent capabilities29:39 - Why AI agents are becoming better entry points than chat-based experiences LINKS: Read Abram's article on "The Doer Mindset": https://www.abramjackson.com/analysis/doers-those-that-will-benefit-from-ai/Learn more about our podcast: https://returnonintelligence.ai/ Follow us on social media:Daniel Anderson on LinkedIn - https://www.linkedin.com/in/danielandoAbram on LinkedIn - https://www.linkedin.com/in/abramj

    30 分鐘

  5. 4月14日

    Copilot Agents That Work Together

    In this episode of Return on Intelligence, Abram and I dive into Microsoft's groundbreaking AI agent developments that are revolutionizing workplace productivity. Fresh from the MVP Summit in Seattle, Abram shares exclusive insights on Microsoft's vision for Copilot's new Researcher and Analyst agents. We explored Abram's experience at the recent MVP Summit in Seattle, where he gained insights into Microsoft's long-term vision. The heart of our discussion focused on Microsoft's new Researcher and Analyst agents for Copilot, which represent a fundamental shift in AI interaction patterns—moving from simple chat interfaces to a 'set up a task and let it work' approach that saves hours of effort. We discussed how Researcher connects with your entire Microsoft 365 ecosystem and can even interact with other agents, creating true multi-agent functionality. Meanwhile, Analyst focuses on structured data analysis across various formats using Python code interpreter capabilities. We wrapped up by exploring the future of image generation in workplace tools, with Abram sharing how he's creating custom 'style agents' that maintain visual consistency across all content types. Key Insights Agent-based interactions: The shift from chat-based AI to agent-based interactions represents a fundamental evolution in how we'll work with AI systems, potentially saving hours of human effort on complex tasks.Ecosystem integration: Microsoft's new agents connect deeply with the M365 ecosystem, including Teams, emails, SharePoint, and now over 25 graph connectors to enterprise applications.Multi-agent collaboration: Researcher's ability to interact with other agents opens up new possibilities for handling complex, multi-step tasks through true multi-agent functionality.Democratized data analysis: Analyst brings sophisticated data processing capabilities to everyday users without requiring specialized knowledge, potentially transforming how organizations handle data.Visual consistency automation: Custom 'style agents' are enabling consistent visual branding across all content types, streamlining creative workflows and maintaining brand integrity.Timestamps 00:00 - 03:15: Introduction and MVP Summit discussion03:15 - 12:30: Deep dive into Microsoft's Researcher agent capabilities12:30 - 18:45: Exploring multi-agent interactions and ecosystem integration18:45 - 25:10: Analyst agent and its data processing capabilities25:10 - 30:00: Future of image generation and style agents in workplace tools

    31 分鐘

  6. 4月14日

    The Evolution of AI in the Workplace

    In this episode of Return on Intelligence, Abram and I explore how AI is transforming workplace productivity and changing the fundamental nature of work. We discuss the shift from traditional tools to AI-powered agents that can work together to accomplish complex tasks. Key Insights AI interaction evolution: The shift from chat-based AI to agent-based interactions represents a fundamental change in how we'll work with AI systems, enabling more complex and autonomous task completion.Ecosystem integration: Microsoft's new agents connect deeply with the M365 ecosystem, including Teams, emails, SharePoint, and enterprise applications, making them exponentially more powerful in work contexts.Multi-agent collaboration: Researcher's ability to interact with other agents opens up new possibilities for handling complex, multi-step tasks through true multi-agent functionality.Democratized data analysis: Analyst brings sophisticated data processing capabilities to everyday users without requiring specialized knowledge, potentially transforming how organizations handle data.Visual consistency automation: Custom 'style agents' are enabling consistent visual branding across all content types, streamlining creative workflows and maintaining brand integrity.Timestamps 00:00 - 03:54: Introduction and MVP Summit discussion03:55 - 11:10: Researcher and Analyst agents introduction11:11 - 16:14: Ecosystem integration and data processing16:15 - 24:03: Multi-agent functionality and future roles24:04 - 30:28: Image generation and visual stylingSubscribe to stay updated - https://returnonintelligence.ai Connect with Daniel Anderson | LinkedIn Connect with Abram Jackson | LinkedIn

    29 分鐘
  • 共 6 集

簡介

Return on Intelligence is the go-to show for forward-thinking business leaders, IT professionals, and decision-makers who understand that AI isn’t just a trend—it’s the ultimate investment in the future of work. While most AI discussions stay theoretical, we cut through the noise to focus on real-world applications, success stories, and strategies that drive productivity, efficiency, and business growth. From scaling businesses and optimizing operations to leveraging Microsoft Copilot and automation, we explore how AI-powered intelligence delivers tangible returns. If you’re ready to turn AI from a concept into a competitive advantage, this is your roadmap to making it happen.

資訊

  • 創作者
    Daniel Anderson
  • 活躍年代
    2025年
  • 集數
    6
  • 年齡分級
    兒少適宜
  • 版權
    © 2025 Daniel Anderson Consulting Pty Ltd
  • 節目網站
    Return on Intelligence