The Intelligence Age

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Ragnar Heil shares hands-on lessons from building and running autonomous agents with OpenClaw. He compares conversational, agent-first workflows with traditional automation tools, highlights real infrastructure and security trade-offs, and explains why this kind of experimentation accelerates deep understanding of agent architecture. The conversation explores where Copilot fits today, what breaks in early-stage agents, and why learning Linux, scripting, and model plumbing is becoming a core AI skill for practitioners.

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/816 

🎙️ What you’ll learn     

• How conversational interfaces like Telegram change the way agents are built and operated 
• Where traditional automation adds friction compared to autonomous agents 
• Practical infrastructure choices for running experimental agents safely 
• Real-world security and governance risks when working with agentic AI 
• Why hands-on agent maintenance accelerates architectural understanding 

✅ Highlights   

• “I literally talk into the microphone and then it builds it overnight without any effort for me.” 
• “They’re not really autonomous, most of them are retrieval agents.” 
• “Please don’t install OpenClaw on your PC or MacBook.” 
• “It could literally delete your whole C drive without your command.” 
• “I never learned so much around Linux scripts than in my whole life.” 
• “I’m losing my fascination because I have to fix it every single day.” 
• “It’s taken me further into understanding agents than I have ever been.” 
• “We are in a very, very early stage here.” 
• “The interface as we know it is going to go away.” 

🧰 Mentioned     

• OpenClaw: https://openclaw.ai/ [openclaw.ai] 
• Copilot: https://copilot.microsoft.com/ 
• Microsoft responsible AI standards: https://www.microsoft.com/ai/responsible-ai 
• Copilot Studio: https://www.microsoft.com/microsoft-365-copilot/microsoft-copilot-studio/ 
• Microsoft MVP YouTube Series - How to Become a Microsoft MVP - https://www.youtube.com/playlist?list=PLzf0yupPbVkqdRJDPVE4PtTlm6quDhiu7 

✅ Keywords      
openclaw, autonomous agents, agentic ai, copilot, copilot studio, power automate, telegram interface, linux scripting, ai security, governance, mcp servers, infrastructure 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM 

This episode features Martin Miller and explores the practical reality of using AI inside organisations. The conversation cuts through hype to focus on where AI genuinely adds leverage, where it breaks down, and why subject matter expertise, data quality, and critical thinking still matter. From AI‑generated code and agent teams to data governance, outages, and deepfakes, the discussion frames AI as a powerful amplifier rather than a replacement. The core message is clear: AI rewards clarity of intent, strong foundations, and human judgement. 

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/815

🎙️ What you’ll learn 

• How AI‑generated code fails without clear problem definition 
• Why data quality and governance are prerequisites for AI success 
• When AI amplifies expertise versus creating costly mistakes 
• How organisations misuse AI by chasing headcount reduction 
• Why critical thinking weakens when AI replaces core learning 

✅ Highlights 

• “It’s not about can you write a for loop. It’s about can you define what you’re trying to accomplish.” 
• “The more you know, the more you can use this tool.” 
• “Nothing like making a decision off of bad data.” 
• “AI is a power tool in the box of tools, and it’s a super tool.” 
• “It will confidently deliver you results that may or may not be what you need.” 
• “Headcount reduction and creating solutions are mutually exclusive.” 
• “If you can’t manage your data with or without humans, you need to know that.” 
• “You can generate the anomaly of the moment using AI all day long.” 
• “There’s no Brent to call when your AI isn’t working.” 
• “People that used AI couldn’t remember anything about the paper.” 

🧰 Mentioned 

• Claude: https://claude.ai/ 
• OpenAI: https://openai.com/  
• ChatGPT: https://chatgpt.com/  
• Gemini: https://gemini.google.com/ 
• DevOps: https://www.atlassian.com/devops 
• The Phoenix Project: https://itrevolution.com/product/the-phoenix-project/  
• Foursquare: https://foursquare.com/ 
• Book: AI in a Weekend: An Executive’s Guide: https://www.amazon.com/Weekend-Executives-Guide-Martin-Miller-ebook/dp/B0D4JPSRH2

✅Keywords 
ai strategy, ai coding, data governance, critical thinking, ai agents, devops, site reliability engineering, ai outages, deepfakes, prompt engineering, subject matter expertise, enterprise ai 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM 
 
Simon Doy and Mark Smith explore the rapid shift from experimentation to production use of AI agents. The conversation focuses on practical agent design, Copilot Studio, RAG quality, and where automation fits better than full agents. Simon shares real client work in the NHS, small business realities, and how partners deliver Copilot adoption and agent-led transformation. A recurring theme is choosing the right level of AI, from automation with AI sprinkles to long running agent workflows, while staying pragmatic about cost, governance, and user experience. 

🎙 Full Show Notes
https://www.microsoftinnovationpodcast.com/814

👉 What you’ll learn     

• How agentic workflows are moving from demos into real production use 
• When simple SharePoint grounding is enough and when Azure AI Search is required 
• How to combine automation and agents to avoid slow, interactive AI experiences 
• Practical approaches to Copilot adoption for leaders and teams 
• Why token usage, orchestration, and model choice are becoming operational concerns 

✅ Highlights     

• “On Friday, I let Claude Opus go and build me a Teams agent overnight.” 
• “The agentic side and being able to have these long running tasks is really shifting things.” 
• “Customers are now getting much more open to trying things out.” 
• “Copilot Studio is the first port of call.” 
• “You don’t get the quality back from the agent that you need with complex content.” 
• “How you chunk it is so important for RAG.” 
• “Not everything needs to be a full on agent.” 
• “Automation with AI sprinkles is sometimes the better option.” 
• “My world is fast becoming measured by tokens.” 
• “You don’t have to use the most expensive model on everything.” 

🧰 Mentioned     

• Copilot Studio - https://www.microsoft.com/microsoft-365-copilot/microsoft-copilot-studio 
• Azure AI Search - https://azure.microsoft.com/products/ai-services/ai-search 
• EmpowerM365 -  https://empowerm365.com 
• Microsoft MVP YouTube Series - How to Become a Microsoft MVP - https://www.youtube.com/playlist?list=PLzf0yupPbVkqdRJDPVE4PtTlm6quDhiu7 

✅ Keywords      
ai agents, copilot studio, microsoft 365, automation, rag, azure ai search, sharepoint, claude opus, agentic workflows, copilot adoption, power automate, tokens 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM 

Dani Kahil breaks down the growing complexity of Copilot and AI agents in the Microsoft ecosystem and how practitioners can make sense of it. The conversation focuses on practical mental models, minimum viable agents, and real-world use cases, including document-heavy processes in higher education. The core insight is that successful AI adoption depends less on tools and more on clear roles, scoped responsibilities, feedback loops, and realistic expectations of non-deterministic systems.
 
👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/813

🎙️ What you’ll learn   

• How to distinguish between Copilot experiences, products, and build tools across Microsoft platforms 
• Why diagrams and visual models help reduce AI and Copilot confusion for teams and leaders 
• How to define a minimum viable agent to prevent scope creep 
• Why treating agents like junior co-workers improves outcomes 
• How feedback loops and incremental task expansion make agents useful in production 

 ✅ Highlights 

• “It took me a lot of time to kind of process the information.” 
• “I always like visuals and kind of diagrams.” 
• “There are so many different versions of the different copilots.” 
• “These are completely separate products.” 
• “I started looking at them as roles and job functions.” 
• “Treat your agent like a co-worker.” 
• “In two minutes, you can build an agent, and it’s useless.” 
• “Start with a very simple instruction at the beginning.” 
• “It will never be 100%. That’s the nature of generative AI.” 

🧰 Mentioned 

• Diagram to download: https://danikahil.com/microsoft-copilots-and-ai-agents-ecosystem-diagram/ 
• Youtube video of my walkthrough of the diagram: https://youtu.be/nZ8g11YthYI 
• Microsoft Power Platform: https://www.microsoft.com/power-platform
• Azure AI Foundry: https://azure.microsoft.com/products/ai-foundry
• Windows Copilot: https://www.microsoft.com/windows/windows-11?wincampaign=Copilot

✅Keywords   
copilot, ai agents, power platform, microsoft 365, copilot studio, agent builder, azure foundry, power apps, automation, generative ai, minimum viable agent, ai adoption 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM 

In this episode of AI Unfiltered, Kristen Perdue explains why AI adoption fails when leaders treat it like standard software instead of a fundamental shift in how organisations operate. The conversation focuses on executive mindset, cultural alignment, and communication gaps that quietly derail AI initiatives. Kristen shares how to prioritise the right use cases, close AI literacy gaps, and re‑engineer processes so AI drives growth rather than amplifying broken workflows. 

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/812  

🎙️ What you’ll learn 

• Why AI adoption is a leadership and culture challenge, not an IT rollout 
• How executive misalignment undermines AI strategy and execution 
• How to prioritise AI use cases based on real operational bottlenecks 
• Why overconfidence in AI skills creates risk across organisations 
• When process re‑engineering must happen before automation 

✅ Highlights 

• “AI is a different way of doing business. It’s not really a tool.” 
• “It doesn’t work like software. It is a completely new way of doing business.” 
• “Most approached it going, well, should I roll out AI?” 
• “We started throwing darts at a dart board anywhere it landed.” 
• “AI multiplies good and it multiplies bad.” 
• “Only 21% of the companies deploying AI even touched re‑engineering their processes.” 
• “That lack of communication is the reason initiatives fail.” 
• “People are confident, but they score 40 out of 100.” 

🧰 Mentioned 

• Generative AI: https://en.wikipedia.org/wiki/Generative_artificial_intelligence 
• Process re‑engineering: https://en.wikipedia.org/wiki/Business_process_reengineering 
• McKinsey study on AI and process re‑engineering: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-how-organizations-are-rewiring-to-capture-value 
• Section AI literacy report: https://www.sectionai.com/ai/the-ai-proficiency-report 

✅Keywords 
ai adoption, executive alignment, ai strategy, generative ai, ai literacy, change management, process re-engineering, business transformation, leadership mindset, ai governance, organisational culture, applied ai 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM

🎙 Full Show Notes
https://www.microsoftinnovationpodcast.com/811
 
This episode explores how organisations can move from AI curiosity to real, everyday value through the practical adoption work of Carina de Vries. Drawing on hands-on experience, it reframes AI from a tool conversation to a problem-first mindset. The focus is on building trust, improving quality, and creating small habits that stick. Listeners will learn why one-off training fails, how behaviour change really happens, and how to design an AI adoption journey that fits daily work rather than disrupting it. 

👉 What you’ll learn     

• How to shift AI conversations from tools to real user problems 
• Why small, repeatable habits matter more than broad AI training 
• How to design an adoption journey that builds trust and confidence 
• Ways AI can improve both productivity and quality of work 
• How to help people move from experimentation to daily AI use 

✅ Highlights     

• “I discovered ChatGPT and it helped me get back to work in just an hour a day.” 
• “It’s just another tool in the toolbox, so what do you want it to deliver to you?” 
• “We talk too much about the tool instead of a daily problem a user can relate to.” 
• “People are already in a mindset that the current tool they’re using is better.” 
• “It’s about building the habit, not just doing a one-off training.” 
• “Make it small, because we tend to tell everything about the product all at once.” 
• “If you can continue it another 30 days, then it’s going to be a habit.” 
• “I wouldn’t know what to do without it because it’s saving me so many hours a week.” 

🧰 Mentioned     

• ChatGPT: https://chatgpt.com  
• Microsoft Copilot:https://copilot.microsoft.com 
• M365 Copilot: https://www.microsoft.com/microsoft-365-copilot  
• Copilot Chat: https://copilot.cloud.microsoft  
• Copilot Studio: https://www.microsoft.com/microsoft-365-copilot/microsoft-copilot-studio  
• Gamma.app: https://gamma.app  
• Microsoft Teams: https://www.microsoft.com/microsoft-teams 
• Tech Community: https://techcommunity.microsoft.com 
• Ignite: https://ignite.microsoft.com 
• Microsoft MVP YouTube Series - How to Become a Microsoft MVP: https://www.youtube.com/playlist?list=PLzf0yupPbVkqdRJDPVE4PtTlm6quDhiu7 

✅ Keywords      
ai adoption, copilot, chatgpt, user adoption, habit building, productivity, ai literacy, change management, microsoft 365, prompts, workplace ai, digital transformation 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM 

In this episode, Mark Smith speaks with Caleb Mattingly about how startups and enterprises should approach AI governance, compliance, and risk as AI adoption accelerates. The conversation focuses on ISO 42001, common misconceptions about AI security, and why compliance is less about badges and more about trust, data quality, and long term viability. You will hear practical perspectives on when compliance becomes essential, how it functions as a sales enabler, and why human oversight still matters more than autonomous agents in high risk environments. 

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/810   

🎙️ What you’ll learn 

• How ISO 42001 differs from traditional security standards like ISO 27001 
• Why AI compliance is primarily about data quality, bias, and risk anticipation 
• When compliance becomes a sales lever rather than a legal checkbox 
• Why most organisations are not ready for autonomous compliance agents 
• How startups should time compliance investments without killing runway 

✅ Highlights 

• “ISO 42001 does not prove that your AI system is secure at all.” 
• “Most of it is not security related, it’s about data quality and bias.” 
• “AI is only as good as the data that you give it.” 
• “Compliance acts as a sales lever before it acts as a security guarantee.” 
• “AI can make a lot of mistakes very quickly.” 
• “Most companies are not ready for AI agents with admin access.” 
• “SOC 2 in two weeks is not a thing.” 
• “Compliance and security are not one to one.” 
• “Enterprises care about whether you handle their data securely.” 
• “It takes a minimum of five months to get SOC 2 done properly.” 

 🧰 Mentioned 

• International Standards Organization: https://www.iso.org/ 
• ISO 42001: https://www.iso.org/standard/42001  
• ISO 27001: https://www.iso.org/standard/27001  
• SOC 2: https://www.aicpa-cima.com/topic/audit-assurance/audit-and-assurance-greater-than-soc-2 
• EU AI Act: https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng 

✅Keywords 
ai governance, iso 42001, ai compliance, startup compliance, data privacy, soc 2, iso certification, ai risk management, enterprise sales, ai regulation, security and privacy, responsible ai 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM

This episode explores how AI coding agents are reshaping how software is built, through the practical experience of Vardhaman Deshpande. The core insight is that pro-code developers using natural language with modern AI models can now build features and agents faster than many low-code tools. The conversation examines velocity gains, trade-offs between pro-code and low-code, and what this shift means for professionals building AI-powered solutions.
 
🎙️  Full Show Notes
https://www.microsoftinnovationpodcast.com/809

👉 What you’ll learn     

• When pro-code plus AI is faster than low-code tools 
• How natural language is becoming a new interface for software development 
• Where Copilot Studio fits, and where it may slow teams down 
• How AI agents accelerate feature delivery and testing 
• What skills matter as AI-driven development matures 

✅ Highlights     

• “My workflow is actually faster than doing something in a low-code, no-code environment.” 
• “Pro-code plus AI coding agents might actually be faster to build than low-code.” 
• “Recent models are amazing at translating natural language to code.” 
• “Earlier something that took weeks I can probably do in a couple of days now.” 
• “The velocity of creating features for products is going to explode.” 
• “Why do you need that middleware?” 
• “Prompting rather than configuring is the transition we’re starting to see.” 
• “How much of pro-code versus low-code is realistic remains to be seen.” 
• “Things which were prohibitively time-consuming have become possible now.” 

🧰 Mentioned     

• Microsoft Foundry: https://azure.microsoft.com/products/ai-foundry/  
• Azure AI Services: https://ai.azure.com/explore/aiservices 
• Copilot Studio: https://www.microsoft.com/microsoft-365-copilot/microsoft-copilot-studio/  
• GitHub Copilot: https://github.com/features/copilot  
• Power Virtual Agents: https://www.microsoft.com/microsoft-copilot/blog/copilot-studio/microsoft-power-virtual-agents-now-part-of-microsoft-copilot-studio/ 
• Microsoft MVP YouTube Series - How to Become a Microsoft MVP - https://www.youtube.com/playlist?list=PLzf0yupPbVkqdRJDPVE4PtTlm6quDhiu7 

✅ Keywords      
ai agents, pro-code, low-code, github copilot, copilot studio, microsoft foundry, azure ai, natural language coding, software velocity, ai development, microsoft ecosystem, automation 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM

In this episode, Esther Angell shares a grounded approach to adopting AI without hype or overwhelm. The conversation focuses on starting with real business problems, using the tools you already have, and improving efficiency without losing trust or human connection. Esther explains where AI delivers real value for small teams, the risks of misuse, and why culture matters as much as capability. The core message is simple: solve the work nobody wants to do, move fast, and stay purposeful as AI adoption accelerates.

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/808

🎙️ What you’ll learn   

• How to identify the right problems before introducing AI 
• Where small businesses can gain real efficiency with AI 
• Why overusing AI can damage trust and customer experience 
• How to reduce risk when using free and built-in AI tools 
• Practical ways to start small and fail fast with AI initiatives 

✅ Highlights 

• “You can't be in a state of curiosity and judgment at the same time.” 
• “AI shouldn’t be your decision-making platform.” 
• “We still have people making those buying decisions.” 
• “Most folks are using it, but at a preference level.” 
• “What tools do you own, and are you using them?” 
• “Content is great, but it can get you into trouble.” 
• “People are doing business with a small business because they feel connected.” 
• “Most AI projects are not successful.” 
• “Start with the thing nobody really wants to do.” 
• “Small businesses can be more nimble.” 

🧰 Mentioned 

• Microsoft Power Platform: https://www.microsoft.com/power-platform  
• Dynamics: https://www.microsoft.com/dynamics-365  
• Salesforce: https://www.salesforce.com  
• HubSpot: https://www.hubspot.com  
• Google Workspace: https://workspace.google.com  
• Gemini: https://gemini.google.com 

✅Keywords   
ai adoption, small business ai, automation, efficiency, digital transformation, crm, power platform, entrepreneurship, ai risk, ai culture, process improvement, human centred ai 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM
 
This episode features a conversation with Daniel Cohen‑Dumani on why many organisations feel stuck on AI despite rapid advances. The discussion focuses on agentic AI, the growing gap between consumer and business adoption, and why strategy matters more than experimentation. You will hear practical guidance on narrowing AI efforts to real business problems, building organisational memory for reliable agents, and avoiding paralysis caused by hype and fear. The conversation also challenges traditional systems like CRM and reframes AI as a tool to learn, not shortcut, building sustainable capability inside organisations.

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/807 

🎙️ What you’ll learn 

• How agentic AI is shifting from demos to real work execution 
• Why many businesses are still years behind practical AI adoption 
• How to identify one business problem where AI can move the needle 
• What organisational memory is and why agents depend on it 
• How to use AI to learn skills rather than replace thinking 

 ✅ Highlights  

• “There’s not going to be a slowdown. I think this is just a new normal.” 
• “I think business are more lost than ever.” 
• “We live in a bubble, but businesses are still two years back.” 
• “2026 is really the year where we’re going to see business start knocking off things using agentic AI.” 
• “Every business today have to be driving a bus on the highway and changing the wheels.” 
• “AI is going to disrupt your business. That is a fact.” 
• “Context is the key to having reliable agents.” 
• “An agent without memory is nothing.” 
• “Innovation has to come from the bottom up.” 

🧰 Mentioned 

• Agentic AI: https://www.ibm.com/think/topics/agentic-ai  
• OpenClaw: https://openclaw.ai/  
• Snowflake: https://www.snowflake.com/  
• Knowledge graph technology: https://www.ibm.com/think/topics/knowledge-graph  
• Artificial general intelligence (AGI): https://en.wikipedia.org/wiki/Artificial_general_intelligence 

✅Keywords 
agentic ai, ai adoption, organisational memory, business strategy, ai agents, knowledge graph, crm systems, enterprise ai, ai learning, automation, digital transformation, ai disruption 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith