The Wired Garage with Pops | Digital Innovation

Brian Clayton and Steele Harding
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The Wired Garage with Pops — the place where technology, outdoor activities, music, mixed with a few stories and a good pour of bourbon all meet.  The Wired Garage with Pops is a technology-driven podcast that blends deep IT expertise with real-world storytelling. Hosted by Pops — an enterprise architect, IT leader, and tech storyteller — the show explores how people and organizations navigate the evolving digital landscape. Each episode dives into topics such as ServiceNow innovation, digital transformation, agentic AI, and the intersection of IT operations and business strategy. The show highlights not just the technology itself, but the human side of building, leading, and adapting in complex enterprise environments. Listeners include IT professionals, executives, and technology enthusiasts who want practical insights and authentic stories from experts shaping the future of work and technology. Conversations are engaging, thoughtful, and often spiced with Pops’ down-to-earth humor and passion for the craft — whether that’s tech, BBQ, or leadership.

  1. 20 Oct

    Exploring ServiceNow's Strategic Portfolio Management

    S1E46 Exploring ServiceNow's Strategic Portfolio Management Steele plays "Joe Schmoe", submits an espresso machine idea, then flips roles to the demand manager and carries it through ServiceNow Strategic Portfolio Management. Along the way, Steele and Pops cover how ideas get in, what a demand has to capture, and why a project can be approved and still not be able to start. In this episode: - Two intake paths: the service catalog form and the idea portal with crowd voting - What a demand holds: sponsors, business justification, cost, risk, target dates - Why vendor approval and MSA status belong on the demand - Catching duplicate demands before they become projects - Scenario planning in place of spreadsheet one and spreadsheet two - The out-of-the-box business case tab Pops hates the most - After launch: benefit plans, cost plans and the feedback loop If you don't put the data in, the platform can't help you. That is the thread running through the whole episode. KEYWORDS: ServiceNow SPM, ServiceNow Strategic Portfolio Management, ServiceNow demand management, ServiceNow idea portal, ServiceNow business case, ServiceNow scenario planning, ServiceNow Strategic Planning Workspace, ServiceNow goal framework, demand intake, portfolio management, value realization, project portfolio, IT leadership, ITSM, enterprise IT, The Wired Garage with Pops See ya later.

  2. 13 Oct

    Portfolio Management vs Project Management: Which Matters More?

    The conversation explores the significance of portfolio management, its challenges, classic tools and frameworks, the impact of technology, and the role of AI in reshaping portfolio management. It emphasizes the importance of strategic decision-making, governance, and the shift from manual reporting to continuous intelligence. Takeaways Portfolio management bridges strategy to executionAI shifts decision-making from project tracking to strategic investmentPortfolio managers focus on strategic decision-making and organizational change managementChapters 00:00 – Intro & Series Kickoff00:42 – What Is Portfolio Management?01:47 – Why Organizations Struggle02:23 – Tools & Frameworks04:03 – What's Changed Recently04:53 – The Bottom-Line Impact06:05 – The Human Element & Change Fatigue07:07 – The Endurance-Race Analogy07:55 – Case Study: The $30M CIO10:05 – The Building-Blocks Analogy11:00 – Enter AI: Real-Time Intelligence12:40 – AI Easing PM Burnout14:30 – Agentic AI in Action15:45 – Are Portfolio Managers Still Needed?16:53 – Wrap-Up & Next Episode Tease

  3. 6 Oct

    Why Your AI Strategy is Failing (And How To Fix It) with Chad Mattix of Kinnetix

    The conversation with Chad Mattix delves into the concept of AI as an operating model, emphasizing the importance of human oversight and decision-making. It explores the integration of AI into business operations, the impact on scalability, and the need for clear governance and context. The discussion also highlights the challenges and considerations in deploying AI, including token consumption, cost evaluation, and the role of AI as a co-pilot rather than an autopilot. Takeaways AI as an operating modelHuman oversight and decision-makingIntegration of AI into business operationsChallenges in deploying AIToken consumption and cost evaluation Chapters 00:00 Introduction to AI as an Operating Model01:13 AI as an Operating System for Kinetics05:00 Data Governance and AI Integration06:31 Impact on Business Scalability22:54 Challenges in Deploying AI35:09 AI as a Co-Pilot, Not an Autopilot

  4. 29 Sept

    He Built an AI Employee for His Home Lab (And Tested Disaster Recovery in 22 Minutes

    Toby shares insights into managing a home lab, the challenges faced, and the transformative impact of leveraging AI to improve management and automation. He discusses disaster recovery testing, observability, and the applicability of home lab learnings to enterprise IT. Takeaways AI can transform home lab managementDisaster recovery testing is essential for home lab resilienceChapters 00:00 Introduction to the Home Lab03:01 Challenges of Managing a Home Lab06:19 Leveraging AI to Improve Home Lab Management15:30 Testing and Implementing Disaster Recovery24:25 Observability and Future Plans26:01 Applicability to Enterprise IT

  5. 22 Sept

    Meet Fred - Why Your AI Needs a Job Description

    The conversation with Chad Mattix delves into the concept of AI as an operating model, emphasizing the importance of human oversight and decision-making. It explores the integration of AI into business operations, the challenges of AI governance, and the need for a balanced approach to automation. The discussion highlights the role of AI in enabling scale and efficiency while empowering human workers to make informed decisions. Takeaways AI as an operating modelHuman oversight and decision-makingBalanced approach to automationAI governance and challengesEmpowering human workers Chapters 00:00 AI as an Operating Model05:00 The Role of Human Oversight06:10 Challenges of AI Governance09:00 Balanced Approach to Automation17:17 Empowering Human Workers22:54 AI Integration and Business Operations38:06 The Future of AI in Business

  6. 1 Sept

    Cost of Doing Business with David Cram

    S1E41 Cost of Doing Business with David Cram David Cram, founder of ValSync, joins Pops and Steele to take aim at one phrase: "that's just the cost of doing business." He argues that organizations exaggerate the cost of change until it becomes a kind of prison — and that phrase becomes the excuse for staying trapped in it, at the expense of productivity, profitability, and digital transformation. The conversation digs into where costs quietly slip through the cracks — auto-renewals, shelfware, unused licenses, scope creep — and why most organizations' inventory management is still stuck on spreadsheets rather than tools like ServiceNow's SAM module. David breaks down how to negotiate vendor contracts without breaking the supplier's revenue recognition (the thing that actually keeps them motivated to deal with you), then turns to AI: why so many companies are chasing ROI without a real plan, why "token" is a moving target nobody's pinned down, and why token cost surprises are shaping up to be the next cloud sticker-shock crisis. He closes with a challenge to the audience — before calling something "just the cost of doing business," ask why change actually feels scary, and go pull your renewal dates and license utilization this week. Keywords / Tags IT cost optimization, ValSync, David Cram, cost of doing business, digital transformation, contract negotiation, auto-renewal, shelfware, unused licenses, scope creep, software asset management, ServiceNow SAM, revenue recognition, RevRec, vendor negotiation, AI ROI, AI governance, token costs, AI observability, cloud cost management, IT leadership, enterprise technology spend Chapters 00:00 – Intro / David returns to the garage 00:20 – Why "cost of doing business" is a trap 01:08 – Hidden contract costs: auto-renewal, shelfware, scope creep 01:44 – Why inventory management still fails at most orgs 02:30 – Negotiating without killing the supplier's RevRec 04:19 – How AI is changing tech spend conversations 04:36 – The AI ROI blind spot 06:45 – Late adopters, fast followers, and the token cost crisis 09:30 – Final words: ask why change is actually scary 10:27 – Closing challenge and where to find David Take one thing from this episode — pull your renewal dates and license utilization this week. You might be surprised what you find. Subscribe and drop a comment with one line item in your budget that no one's ever questioned. Support the show

  7. 28 Jul

    Your AI Agents Need a Background Check

    S1E40 Your AI Agents Need a Background Check Pops and Steele tackle a problem most IT and finance leaders haven't caught up to yet: AI subscriptions and API spend are becoming the new shadow IT. Teams are subscribing to AI tools on corporate cards with zero governance or intake process, token-based consumption is replacing predictable licensing, and nobody's tracking the "blast radius" of what these tools can access. They walk through why AI spend breaks the old software asset management playbook (or doesn't — they debate this), how to treat AI subscriptions like governed IT assets, what review cadence makes sense (monthly until you understand it, then quarterly), and how to open the budget conversation with finance before finance opens it with you. Along the way: a $2,000-in-24-hours cautionary tale, a Lexis Nexis printer-page analogy, and Steele's line that becomes the episode's thesis — "whoever ignores the budget conversation loses the seat at the table." Key Takeaways Shadow AI hides wherever there's no intake and governance process. If you don't have a formal way to bring AI tools in, someone already brought one in without you.AI spend is jagged and consumption-based, not predictable like traditional per-seat licensing — auto-approval settings and "set it and walk away" agent usage can generate runaway bills.Wrong tool, wrong job costs money. The $2K/24-hour example: using a frontier model for basic tasks is "driving a Ferrari to the grocery store."Treat AI subscriptions like governed IT assets — track what models, datasets, skills, and prompts are in use, ideally surfaced first in a spreadsheet, then a CMDB.Ownership is shared, but accountability isn't optional — the business owns the risk, but the team that brought a tool in without process owns the consequences.Review cadence: monthly until you fully understand a new tool's usage pattern; only then step back to quarterly/biannual. New capabilities may need daily/weekly checks at rollout.Bring numbers to finance before they ask. Go in with an annual spend estimate, a value narrative, and a straight answer — don't let finance find out from the invoice.Read the fine print on new model releases — usage multipliers (like a new model consuming 50% more of your quota) can quietly blow through limits.Keywords / Tags AI spend management, shadow AI, shadow IT, AI governance, ServiceNow ITAM, IT asset management, AI subscription tracking, token consumption, CMDB, AI budget, finance and IT alignment, agentic AI risk, AI cost governance, enterprise AI adoption, frontier models, AI ROI, IT leadership, CAB governance, AI sprawl, security risk AI tools, AI procurement Is AI spend already a line item at your shop — or are you still finding out from the invoice? Drop a comment. If you're the one who has to explain the AI bill to finance, hit subscribe — this is the show for you. Tag the person on your team who needs to see this before the next invoice lands. Want the one-sheeter framework Pops uses to pitch new AI tools to finance? Link in bio. Support the show

  8. 21 Jul

    Someone Racked Up $2,000 on AI in 24 Hours. Here's What They Did Wrong

    S1E39 Someone Racked Up $2,000 on AI in 24 Hours. Here's What They Did Wrong Pops and Steele dig into a problem hiding in plain sight: uncontrolled AI subscription spend. As teams experiment freely with AI tools — often on personal corporate cards with zero IT or finance visibility — costs are quietly compounding into what could become a governance crisis. The two draw parallels to the early days of cloud computing and Shadow IT, arguing that AI subscriptions, tokens, and usage-based billing need to be tracked like any other IT asset, ideally landing in a CMDB. They walk through real-world cautionary tales (a $2K/day AI bill, a Meta token-spend anecdote), debate who actually owns AI risk within an organization, and lay out a practical cadence for reviewing AI spend — monthly until you understand it, then scaling back. The episode closes with concrete advice: read the fine print on your AI tool's usage limits, bring a real cost forecast to finance early, and don't wait for the invoice to start the conversation. Key Takeaways Shadow AI hides wherever there's no intake and governance process — not in one department, but across every team running its own point solutions. Usage-based billing breaks traditional software asset tracking. Unlike flat licensing, token/consumption-based spend is jagged and hard to forecast without active monitoring. Treat AI subscriptions like governed IT assets — track what models, datasets, and prompts are in use, ideally inside a CMDB, the same way you'd track any other asset with blast-radius risk. Review cadence should match maturity, not comfort: monthly (or even daily/weekly for new capabilities) until the org actually understands its usage pattern — then it can stretch to quarterly. Ownership of AI risk is shared, but accountability isn't. The team that brings a tool in without going through proper process still owns the consequences. Bring a number to finance before they ask for one. Proactive cost forecasting protects the relationship — and the budget. "Ferrari to the grocery store" problem: using frontier/premium models for simple tasks is where a lot of runaway spend comes from — match the model to the job. AI spend management, Shadow AI, Shadow IT, AI asset management, CMDB, IT asset management, ITAM, AI governance, token-based billing, usage-based billing, AI budget, finance and IT alignment, AI subscription tracking, consumption-based licensing, AI cost governance, enterprise AI adoption, CAB governance, AI risk management Suggested CTAs Is AI spend already a line item at your shop — or are you still finding out about it from the invoice? Drop a comment and let us know. If you're wrestling with AI governance at your org, hit subscribe — we're covering this space every week. Tag someone in IT or Finance who needs to hear this before the next invoice lands. Support the show

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About

The Wired Garage with Pops — the place where technology, outdoor activities, music, mixed with a few stories and a good pour of bourbon all meet.  The Wired Garage with Pops is a technology-driven podcast that blends deep IT expertise with real-world storytelling. Hosted by Pops — an enterprise architect, IT leader, and tech storyteller — the show explores how people and organizations navigate the evolving digital landscape. Each episode dives into topics such as ServiceNow innovation, digital transformation, agentic AI, and the intersection of IT operations and business strategy. The show highlights not just the technology itself, but the human side of building, leading, and adapting in complex enterprise environments. Listeners include IT professionals, executives, and technology enthusiasts who want practical insights and authentic stories from experts shaping the future of work and technology. Conversations are engaging, thoughtful, and often spiced with Pops’ down-to-earth humor and passion for the craft — whether that’s tech, BBQ, or leadership.

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