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Unswappable: Why AI Can't Fake Being You on LinkedIn | Impact of AI: Explored EP51 "If you could swap your name for anyone else's, it's probably not a good post." Magali De Reu - Founder of the obvious yes (https://www.linkedin.com/in/magalidereu/) went viral with a screenshot showing that LinkedIn is basically all Claude now. Then hundreds of people copied it without credit, with her name still on it, proving her point twice. In this episode, we sit down with Magali, a personal branding strategist who helps people build a business on LinkedIn by showing who they are, not just what they do. We talk about why expertise has become table stakes in the age of AI, how she built her own AI operating system without losing her voice, and why human judgment is the one thing she will never hand over to a model. In this episode: - The story behind the viral "LinkedIn is all Claude" post - Why AI is commoditising expertise, and what that means for standing out - Personality first: why your brand should repel the wrong crowd on purpose - Building an AI system with named agents, and pushing back on its output - The "unswappable" test for every post you write - LinkedIn's AI writing tools, AI-written comments and the algorithm black box - AI agents, vibe coding and why human-in-the-loop still matters - AI fatigue: why the human element is about to get more valuable, not less - One thing to fix on your LinkedIn profile today 01:02 Magali's viral LinkedIn post and its impact 03:03 Magali's experience with AI and personal branding 06:33 Getting started on LinkedIn and building a presence 09:18 Lessons learned from early LinkedIn mistakes 12:38 The personality-driven AI operating system 15:18 The role of human judgment in AI content 19:01 The importance of human touch in AI-assisted posts 22:33 LinkedIn's AI features and content authenticity 24:51 The future of AI and human collaboration in social media you can find Magali here: https://www.theobviousy.es/ or on Linkedin offcourse :-) Support the show

We hit 50 episodes and we marked it by bringing together four experts for our biggest conversation yet. When the labs racing to build the world's most powerful AI systems start warning that the race is moving too fast, should we believe them? Is this genuine caution, a legal defense being built in real time, or something else entirely? Over the next hour, our panel dismantles the "should AI slow down" debate from every angle: economic incentives, geopolitics, liability, governance, and what "slowing down" would even mean in practice. It gets candid, it gets a little chaotic, and it does not land on easy answers  which is exactly why it's worth 50 episodes' worth of getting here. 🎙️ This episode's panel: Paul Slater — AI Enablement Advisor, Adobe (https://www.linkedin.com/in/paul-slater/) Louise Humpington — PGDL, LPC, AI Governance Consultant (https://www.linkedin.com/in/louisehumpington/) Dan Boyles — Founder, Hello AI Collective (https://www.linkedin.com/in/danhelloai/) Femke Cornelissen — Chief AI Transformation Officer, Wortell (https://www.linkedin.com/in/femcornelissen/) Gerjon Kunst — AI Lead, Interstellar Group (co-host) (https://www.linkedin.com/in/gerjonkunst/) James O'Regan — Lead Product Marketing Manager, Liquidware (co-host) (https://www.linkedin.com/in/jamesoreganeuc/) 🔑 Keywords AI development, AI governance, responsible AI, AI regulation, global cooperation, AI ethics, AI risk, AI innovation, AI slowdown, AI standards 📌 Key topics * The race to develop powerful AI systems — and the case for caution * Global cooperation and governance frameworks * Risks of unregulated AI development * Ethics and safety standards in AI deployment * AI's real impact on organizations, society, and individual workers * The risk of AI amplifying human bias and "stupidity" * Why diverse expertise matters in AI governance * The debate over pausing AI — and what would actually justify it ⏱️ Chapters 00:00 Introduction to AI development race and risks 01:47 The debate on slowing AI progress and safety concerns 04:08 Legal and ethical considerations in AI governance 05:57 The role of global cooperation and shared standards 07:50 Economic implications of AI slowdown and innovation 09:57 Understanding what 'slowing down' means in practice 12:01 The importance of testing, benchmarks, and accountability 13:58 The influence of geopolitics and international relations 16:06 The real impact of AI on society and business 17:49 The importance of human expertise and judgment in AI 19:49 Risks of homogenized AI outputs and loss of diversity 22:07 Media influence, misinformation, and public perception 23:47 Historical parallels: arms trade and nuclear treaties 25:53 The need for transparency, oversight, and collaboration 27:46 The challenge of responsible AI deployment in organizations 30:00 The future of AI regulation and ethical standards 32:07 The role of AI in organizational strategy and growth 33:58 Balancing innovation with safety and societal impact 36:08 The importance of diverse expertise and multidisciplinary approaches 37:54 The risk of AI amplifying human flaws and biases 39:56 The democratization of AI and its implications 42:01 Legal and ethical challenges in AI applications 43:59 Humor and human oversight in AI-generated content 46:01 The cultural and societal impact of AI 47:57 The importance of responsible innovation and leadership 49:59 The future outlook: collaboration, regulation, and innovation 52:05 Final thoughts and call for responsible AI development Support the show

In this episode we sit down with Lee Crossley - Consultant CTO | Overshow Co-Founder (https://www.linkedin.com/in/leecrossley/). Lee shares insights on the future of local AI models, their applications, and the evolving landscape of AI technology, emphasizing the importance of local models for privacy, security, and efficiency. Key topics * The evolution of local AI models and their applications * The importance of model routing and hybrid AI strategies * The role of hardware and device capabilities in AI deployment * Industry trends and the impact of major players like Apple, Google, and Microsoft * Security, privacy, and compliance considerations in local AI Links & resources mentioned Ollama – run local LLMs on your machine – https://ollama.com Google Gemma – open-weight models for local use – https://ai.google.dev/gemma Perplexity – hybrid/local model routing with PII handling – https://www.perplexity.ai/hub/products/portable-computer Anthropic Claude & Claude Code – https://www.anthropic.com Azure IoT Edge & on‑prem AI options – https://learn.microsoft.com/azure/iot-edge Apple Intelligence – on-device AI strategy – https://www.apple.com/apple-intelligence/ Support the show

In this episode, James sits down with Steve Wilson - Leading in AI and Cybersecurity - Exabeam, OWASP, O’Reilly (https://www.linkedin.com/in/wilsonsd/), who is stepping in for Gerjon while he's on holiday. Steve discusses the recent AI security incidents, the risks of AI agents escaping sandbox environments, and practical strategies for cybersecurity in the age of AI. He emphasizes the importance of basic security principles, understanding AI components, and fostering ongoing education to manage AI risks effectively. They cover: * The Hugging Face / “Steve” agent incident and what it reveals about AI risk * Why prompt injection is now treated as “inevitable as death and taxes” and how to design systems that survive it * Treating AI agents like digital employees: identities, job descriptions, least‑privilege access, and monitoring * AI FOMO vs. FUD: how business pressure and vendor fear‑mongering drive bad security decisions * Practical next steps for CISOs and security teams over the next 12 months Key takeaways * Stop trying to prevent prompt injection; instead, limit blast radius with tight permissions, unique identities, and clear “job descriptions” for agents. * Use existing identity and monitoring tools first; don’t wait for perfect “non‑human identity” products before you start governing agents. * Build an insider‑threat mindset for AI: malfunctioning, misaligned, and subverted bots are all variants of the same problem. Resources mentioned * OWASP Top 10 for Large Language Models (latest version) (https://genai.owasp.org/resource/owasp-genai-llm-top-10-2026/) * Steve’s open‑source agent security scanner: Prax2n (https://github.com/open-agent-ai-security/praxen) * Exabeam’s open‑source agent logging library: Observra (https://open-agent-ai-security.github.io/observra/) Nick Bostrom, Superintelligence (paperclip optimizer thought experiment) (https://cepr.org/voxeu/columns/ai-and-paperclip-problem) and the website of Nick Bostrom (https://nickbostrom.com/) Connect with Steve Wilson LinkedIn: https://www.linkedin.com/in/wilsonsd/ If you’re responsible for AI, cloud, or security in your organization, this is the “back to basics” episode you need before you deploy your next agent Chapters 00:00 AI agents escape sandbox to cheat on benchmarks 03:10 The importance of paying attention to AI security risks 05:01 Tools and strategies for securing AI applications 06:24 Monitoring AI agents and giving them clear job descriptions 07:20 The current state of AI monitoring in organizations 08:48 Prompt injection vulnerabilities and defenses 10:54 Building systems resilient to prompt injection 12:15 Controlling AI boundaries with role-based access 14:06 Using existing identity management for AI agents 15:09 Balancing FOMO and FUD in AI adoption 16:24 The need for cybersecurity education on AI components 17:22 Evaluating new cybersecurity tools for AI security 19:31 Lessons from cloud migration applied to AI security 23:00 The risks of experiments with dangerous AI models 24:23 The goal-seeking nature of AI and its risks 26:08 AI goal focus and the risk of unintended outcomes 27:27 The metaphor of releasing the genie and AI risks 28:22 The importance of basic security controls and education 41:26 The role of open source and transparency in AI security 45:01 The importance of internal discussions on AI risk management Support the show

In this episode, Gerjon sits down with Jim Moyle (Principal Product Manager for Windows Cloud (https://www.linkedin.com/in/jimmoyle/), stepping in for James while he's on holiday to unpack how combining a "second brain" with agentic AI has completely reshaped his day-to-day work over the past three months. Gerjon Mentions Chris Brear but that should be Dave Brear our guest from episode 40 (https://youtu.be/ZtI8kIfYTpY) The conversation covers: Windows 365 for Agents — a new flavor of Windows 365 built for AI agents (not humans) to log into and operate, complete with its own Entra ID identity, governance, auditability, and a real-time WebRTC observability feed so you can watch — and step into — what an agent is doing.Why "computer use" beats MCP sometimes — Jim explains when driving mouse, keyboard, and the accessibility tree directly is more practical than hunting for (or trusting) an MCP server, especially for one-off tasks or legacy apps with unreliable APIs.Consumption-based pricing — a pay-per-hour model for agent VMs, plus a real demo: 3,500 lines of legacy PowerShell for app packaging replaced by a 12-line agent instruction set, with better resilience to change than a brittle script.The Second Brain workflow — how getting context, audience, and constraints right up front (before going agentic) drastically cuts hallucination, and why Jim treats it as the essential foundation before automating anything.What it actually costs — Jim breaks down his own token usage (216 million tokens/month, ~95% cached) to land on a real-world estimate of roughly £80–90/month.Why EUC teams are made for this moment — Jim's case for why end-user computing professionals already have the security, compliance, and workflow skills to own the agentic AI wave inside their organizations, and how to get started.00:00 Introduction to Jim Moyle and AI Workflow Revolution 01:19 Jim's Journey into AI and Workflow Transformation 02:33 How Windows 365 for Agents Works 03:38 Scaling and Security in AI Workflows 05:34 Controlling and Observing AI Agents in Action 06:29 Unlocking Applications Without APIs 07:47 Error Handling and Human-in-the-Loop 09:37 Identity and Security for AI Agents 11:23 Error Reporting and Troubleshooting 12:49 Scaling and Cost Models for AI Agents 14:01 Getting Started with AI and Second Brain 15:29 Integrating Second Brain with Agentic Workflow 19:35 Enhancing Focus and Productivity with AI 22:58 Cost of Maintaining a Second Brain 26:09 The Role of EUC Professionals in AI Era 29:28 Adoption and Use Cases of Windows 365 for Agents 31:21 Automating App Packaging with AI 32:04 Resilience and Fault Handling in AI Workflows 33:21 Testing and Scaling AI Instructions 34:12 Getting Started with AI for IT Professionals 36:22 Final Thoughts and Future Outlook  resources Windows 365 for Agents - https://www.microsoft.com/en-us/security/business/endpoint/endpoint-manager Starting with windows 365 for agents: https://www.microsoft.com/en-us/windows-365/agents#Get-started playing around with Windows 365 agents: https://learn.microsoft.com/en-us/microsoft-copilot-studio/use-cloud-pc-pool Second Brain Methodology - https://fortelabs.co/blog/second-brain/ or https://www.gerjon.com/?p=1819 Support the show

Is AI Overhyped or Underestimated? Examining the Reality and Potential of Artificial Intelligence In this episode, we explore the gap between AI hype and reality, highlighting both the risks of overhyped claims and the genuine benefits AI offers across sectors. Join us as we discuss real-world failures, success stories, emerging trends, and practical principles to harness AI responsibly and effectively. Key Topics: The exaggerated promises and pitfalls of AI deployments in companiesCase studies of AI failures: data mishaps, security breaches, and unintended consequencesThe impact of AI on sectors like weather forecasting, healthcare, and cybersecurityThe importance of guardrails, governance, and ongoing oversight in AI projectsCost considerations: public versus private AI and the shift towards consumption-based modelsThe role of AI as a workspace interface and the evolution of agent-driven workflowsThe skills gap and human readiness for AI adoption in organizationsFuture predictions: multimodal AI, reasoning systems, and new AI interface paradigmsPractical principles for integrating AI into business securely, sustainably, and responsibly  Timestamps: 03:08 - How AI is perceived as overhyped and underhyped simultaneously 04:19 - The challenge of ROI and AI deployment in enterprise environments 05:14 - Case studys of AI getting it wrong 12:15 - Positive impacts of AI in weather forecasting, drug discovery, and energy grid optimization 16:56 - Private AI versus public AI: benefits and considerations 23:25 - Microsoft’s AI agent ecosystem and governance tools like Agent 365 28:35 - Realistic productivity gains: time savings vs. business value 36:20 - The talent war in AI and the skills gap in organizations 37:34 - The exponential growth of AI episodes and content knowledge base 39:10 - Analyzing top insights from over 40 episodes, summarized via AI 51:00 - Reflecting on AI predictions for 2025: what was accurate, what missed the  56:00 - Key insights for AI going forward Resources & Links: Podcast website: https://impactofaiexplored.com/Presentation from Expertslive: https://impactofaiexplored.com/wp-content/uploads/2026/07/Expertslive-2026-AI-Hype-vs.-Reality.pdfAgents 365: https://www.microsoft.com/en-us/microsoft-agent-365MCP server: http://mcp.impactofaiexplored.com/mcp   Support the show

In this episode we sit down with Matt Neil - Founder @ Artificia1 (https://www.linkedin.com/in/mnealaipro/) to talk about why AI isn’t really a tech project, but a business problem that most SMEs are still struggling to frame correctly. We dig into real‑world adoption stories, how to prove ROI with things like LLM leaderboards and management metrics, and why so many AI and agent projects are destined to be rolled back if they ignore fundamentals like training and change management. Along the way we get into Copilot, OpenAI/OpenClaw vs. Microsoft Scout, token costs, EU AI Act training requirements, and why “train the team and bring them on the journey” is still the most underrated AI strategy Key  topics * The importance of training and adoption in AI projects * Challenges faced by SMEs in AI adoption * ROI measurement and cost management in AI initiatives * The role of leadership and mindset in AI success resources Matt Neil - LinkedIn - https://www.linkedin.com/in/mattneil/ Matt's Company - https://artificia1.com/ Open Claw Video - Stripe CTO - https://www.youtube.com/watch?v=l9wzs_QIyp0 Microsoft Copilot - https://www.microsoft.com/en-us/microsoft-365/copilot Gartner AI Market Report - https://www.gartner.com/en/articles/strategic-predictions-for-2026 EU AI Act - https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52021PC0206 Support the show

In this interesting episode of Impact of AI: Explored, Gerjon and James talk with Rich  Gibbons  - Head of FinOps, GreenOps, and Microsoft Intelligence at Synyega (https://www.linkedin.com/in/rich-gibbons-microsoft-licensing/). Rich discusses Microsoft's new consumption-based AI licensing models, including CoPilot, CoWork, and Scout, and explores their implications for organizations. We delve into cost forecasting, management challenges, and strategic considerations for adopting AI at scale. Key  topics * Microsoft's shift to consumption-based AI licensing * Implications of Co-Pilot, Co-Work, and Scout for organizations * Cost forecasting and management challenges with AI * Strategies for controlling AI-related expenses * The impact of AI on enterprise software costs Chapters 00:42 Introduction to Microsoft's New Licensing Model 03:24 Understanding Co-Pilot and Co-Work 06:04 The Shift to Consumption-Based Billing 08:40 Cost Implications for Organizations 11:24 Evaluating ROI and Financial Discussions 13:50 The Future of AI in Organizations 16:54 Managing Costs and User Quotas 22:04 Navigating Credit Usage and Cost Management 26:12 The Complexity of Consumption-Based Models 29:47 The Evolution of SaaS Pricing Models 33:46 Understanding AI Cost Efficiency Claims 37:47 Strategizing AI Implementation in Organizations Resources Rich's Blog: https://cloudywithachanceoflicensing.com/ Microsoft Co-Pilot - https://www.microsoft.com/en-us/microsoft-365/copilot Microsoft Co-Work - https://www.microsoft.com/en-us/microsoft-365/copilot Microsoft Scout - https://blogs.microsoft.com/blog/2023/05/26/introducing-microsoft-365-copilot-scott/ Support the show

In this insightful episode of Impact of AI: Explored, Gerjon and James talk with Louise Humpingon (https://www.linkedin.com/in/louisehumpington/). We explore the strategic positioning of tech giants in AI governance, the importance of accountability, diversity, and responsible deployment of AI technologies. Lousie shares her diverse background from philosophy to AI governance, emphasizing the need for collaborative, adaptive, and inclusive governance frameworks to mitigate risks and maximize benefits. key  topics Strategic positioning of tech giants in AI regulationAccountability and liability in AI harmsDiversity and inclusion in AI design and deploymentThe need for adaptive, multi-layered governance systemsThe role of human oversight and autonomous agents in AI safety Chapters 00:00 Strategic Positioning in AI Governance 04:30 Louise's Diverse Career Path 06:44 The Need for AI Regulation 09:39 Rethinking Accountability in AI 11:58 Utilizing AI for Self-Governance 15:01 The Mycelium Network of Governance 18:39 Bridging Communication Gaps in Organizations 22:34 Navigating Disputes and Building Trust 23:47 Understanding Women's Hesitancy Towards AI 26:07 Addressing Concerns for AI Adoption 31:34 Generational Trust Issues with Technology 35:56 The Role of Ethics in AI Development 42:14 Key Questions for AI Deployment LinkedIn - https://www.linkedin.com/in/louisehumpingon/ Chirosynthesis - https://chirosynthesis.com From Intentions to Impact (Newsletter) - https://substack.com/@fromintentions2impact Support the show

In this episode of Impact of AI: Explored, Gerjon and James talk with Paul Slater -  Principal AI Technologist at Adobe (https://www.linkedin.com/in/paul-slater/). We discus the often overlooked costs of AI, including human, environmental, and societal impacts. We look at the importance of human control, responsible AI development, and maintaining human-centric values in the age of rapid AI evolution. We also dive into the Reverse Flynn effect which covers the decline in average IQ scores after peaking in the 1990s/2000s. key topics Costs of AI including human, environmental, and societal impactsThe reverse Flynn effect and declining intelligence indicatorsThe importance of human control and responsible AI developmentHabits and behaviors influenced by AI and technologySocietal fragmentation and echo chambers caused by AI Chapters 00:00 The Hidden Costs of AI 06:13 Understanding the Reverse Flynn Effect 10:19 Human Control vs. AI Dependence 14:16 The Impact of AI on Social Interactions 18:03 Cultural Reflections on Technology in Media 19:20 Patterns in Human Interaction with Technology 23:24 The Evolving Fear of AI 25:38 Generational Perspectives on AI 28:10 Safeguarding a Human-Centric AI Future 33:04 Addressing Societal Fragmentation through AI 38:00 Embracing Humanity in an AI-Driven World Resources Paul Slater's Book on AI Costs and Society (https://www.amazon.com/Your-Next-Job-Disappears-ebook/dp/B0C7V7X4X4) European Union Guidelines on AI (https://digital-strategy.ec.europa.eu/en/policies/ai-act) Responsible AI Guidelines by Microsoft (https://www.microsoft.com/en-us/ai/responsible-ai) South Park Episode on AI and Society (http://southparkstudios.com/episodes/8byci4/south-park-deep-learning-season-26-ep-4) Atomic Habits by James Clear (https://www.amazon.com/Atomic-Habits-James-Clear/dp/0735211299) The Reverse Flynn Effect (https://www.develop.bc.ca/the-reverse-flynn-effect/) Support the show

In this episode of Impact of AI: Explored, Gerjon and James talk with Rob Fawcett (The Human CTO) about the “boring but necessary” side of AI: governance, assurance and compliance. Rob explains why most organizations already have the skills from GDPR, ISO and data protection work – they just forget that AI is another governance problem, not a completely new universe. Topics we cover are the EU AI Act, the upcoming UK AI bill, and the real tension between moving fast with AI and staying compliant. Rob breaks down the three modes he sees in companies today: policy and forget, the waiting game, and speed vs compliance. He also argues IT – especially the service desk – is one of the most underused assets in AI governance. We dive into agentic AI (agents talking to agents with no human in the loop), data classification and anonymization, and who’s ultimately responsible when AI agents go wrong – vendors or the business. Rob introduces the ARIA framework (AI Readiness, Impact, Assurance), which scores and prioritizes AI use cases so you don’t just make bad processes faster, and explains how even small teams can start with something as simple as a spreadsheet inventory of all AI tools in use. Support the show

Welcome to the Impact of AI: Explored podcast. In this episode  James and Gerjon sit down with Dave Brear, Citrix Account Technology Strategist (https://www.linkedin.com/in/davebrear/) to unpack the idea of an “AI second brain” and why chain of cognition matters in a world of instant AI-generated content.  They talk about “AI slop” and what separates truly valuable, story-driven content from meaning-shaped noise, even when AI is involved. Dave shares his origin story with note-taking, Zettelkasten, and Obsidian, and how he accidentally built the perfect foundation for an AI-augmented thinking system. We then explore how he connects this personal knowledge vault to AI as a thinking partner, the implications for EUC and enterprise user profiles, and the risks around ownership, shadow AI, and companies potentially “bottling” employees’ cognition. Finally, Dave gives practical advice for knowledge workers who want to start their own second brain from a blank slate, and why reading How to Take Smart Notes might change how you think forever. Interesting links: The book Dave refers to: https://www.soenkeahrens.de/en/takesmartnotes more information: https://davebrear.ai Support the show

This episode with Phil Hobden Head of Customer Advocacy at Sage explores the realistic applications and limitations of AI in business, emphasizing the importance of good data, human oversight, and strategic integration. Phil shares insights on AI's role as a co-pilot, the necessity of foundational data, and the future of AI-driven efficiency. AI as a tool not a cure-allImportance of good data and governanceAI as a co-pilot, not a replacementChallenges of siloed AI systemsHuman oversight and strategic use of AI Support the show

What happens when you put a CTO from professional football in a room and ask them to be honest about AI? Joe Darkins, CTO of Burnley Football Club, joins the show for a grounded, no-hype conversation about what it actually takes to deploy AI responsibly inside an organisation. We cover a lot of ground. Joe breaks down why aligning AI to real business problems matters more than chasing the latest capability, how the CISO role is evolving as AI adoption accelerates, and what agentic AI looks like in a football club context. It's more complex than you might think. We also get into the harder questions. Who is accountable when AI gets it wrong? How do you build sandboxed environments that prevent misuse? And why are local models becoming a serious conversation for organisations that care about data privacy and environmental impact? If you're navigating AI adoption inside your organisation, this one is worth your time. Topics covered: Aligning AI initiatives to actual business problemsThe CISO's expanding role in AI governanceAgentic AI in sport and what it signals for other sectorsAI accountability and risk managementLocal models, data privacy, and sustainability Support the show

In this episode we’re at Arsenal’s Emirates Stadium at Hello AI Summit 2026 and James has a chat with Dan Boyles - Global AI stratigist and Founder at Hello AI (https://www.linkedin.com/in/danhelloai/), 11 months after he turned a rough idea into an AI summit. We dig into why most AI projects stall, how bad data and “glorified Google search” use cases kill ROI, and why fixing your data foundation (think Azure SQL + Fabric) unlocks real business outcomes in operations and customer experience. Dan also explains why AI agents are “really clever interns” on their way to becoming operational teammates, and why you still need proper governance, backups and a clear “why” before you unleash them on your business. Support the show