Learn from MISTAKES with AI | Tech Transformation | Innovation | Cloud | DevSecOps

Are you struggling to demonstrate the business value of technology?

With over 25 years of experience driving innovation and architecting complex systems, I've seen fantastic technology fail because it did not adequately address the user needs of the people it was built to serve.

I specialize in creating clarity amidst complexity - bridging the gap between technology capabilities and business priorities. My superpower is quickly grasping the heart of ambiguous problems and rallying teams to deliver solutions that create measurable value.

If you are a technology or business leader tired of:

❌ Chasing the latest hype while struggling to justify budgets

❌ Translating technobabble for skeptical executives

❌ Watching projects derailed by misaligned priorities

I can help you cut through the noise to build innovation strategies and technology roadmaps that move the needle for your organization and fully leverage AI and automation.

My approach combines systems thinking, design practices, and technical fluency to:

🎯 Uncover the root causes of business problems

🎯 Rapidly validate solution ideas

🎯 Deliver technology that users love

🎯 Continually optimize to drive outcomes

I've applied this formula to industry leaders like PepsiCo and helped clients build and integrate critical IoT, cloud, data, DevOps, and AI capabilities. 

Let's connect for a discovery call to explore if my expertise can help unlock value in your technology investments.

Daniel Lemire

83% of AI projects today focus purely on software, leaving a massive gap in the physical world that's about to change dramatically.

What if I told you we've been looking at AI through too narrow a lens?

This year at CES, NVIDIA's Jensen Huang highlighted something I've been thinking about for months:

2026 will be the year physical AI breaks through. 

But here's where most people are making MISTAKES in understanding this shift:

They're thinking robots. 
They're thinking manufacturing.

This isn't wrong, but that's missing the bigger picture.

Physical AI isn't just about machines that move.

It's really about AI that interacts with our physical world in ways we haven't imagined yet:

1. Smart materials that adapt to environmental conditions
2. Infrastructure that self-repairs
3. Buildings that optimize their own energy use in real-time

Transportation, Logistics, Energy, Construction, Service, and many undiscovered opportunities we all get to find!

Think of it like teaching a child. First, they learn to observe (current AI). Then they learn to speak (language models). But the real magic happens when they learn to interact with their environment (world models). 

[ Yes, I think Yann Lecun is right about the future of world models before we can acheive AGI. (but I also don't think that will be the last step)]

That's where we are with AI right now. We are on the cusp of a third breakthrough, we just don't know how quickly the breakthrough will come.

The most fascinating part? The MISTAKES we've made in software AI will actually accelerate the development of physical AI. We've learned a great deal about what works and what doesn't, and those lessons are invaluable.

I'm working on the latest newsletter addition, where I'll go into detail on the ways I will be exploring physical AI in 2026 with AI MISTAKES.

If you haven't taken action on this, don't wait. Get subscribed, and we can Learn from MISTAKES with AI in 2026.

📰 𝗦𝗶𝗴𝗻-𝘂𝗽 𝗳𝗼𝗿 𝗺𝘆 𝗳𝗿𝗲𝗲 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿
📺 𝗦𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗖𝗵𝗮𝗻𝗻𝗲𝗹 
👉 𝗦𝗲𝗲 𝗺𝘆 𝗽𝗿𝗼𝗳𝗶𝗹𝗲 𝗳𝗼𝗿 𝗱𝗲𝘁𝗮𝗶𝗹𝘀 𝗮𝗻𝗱 𝗹𝗶𝗻𝗸𝘀!

ServiceNow AI Consultant | AI MISTAKES | Transformation | DevOps

This is a thought provoking exchange.

We don't talk about today's 'digital labor', but that is a real thing.

Today, you don't need a lift operator to ride in an elevator. The machine handles that labor, but no one talks about those changes because almost no one can remember the time when an elevator required an operator to function. 

I keep going back to the idea that we are repeating the shift that happened at the beginning of the PC era when people began having access to computers.

Today, much of the digital revolution is founded upon the ways that we 'played' with PCs. 

I remember when I was a kid, getting the PC game to work was how I learned to (at first break, and then fix) configure, upgrade and manage computers.

I'm not certain about the age of abundance (we still have to build datacenters), but I do think that if we use the power of our imagination in the right way, we can bring positive change through the use of these great new tools.

What’s the real blocker to AI success? 

It’s no longer about access, now that everyone has the tools. Today’s barrier is imagination. In the age of resource abundance, we need to think bigger.  

So what’s holding teams back from turning AI ambition into action? 

Nick Tzitzon joined global leaders on this AI Skills Panel to unpack how Australia can move from scarcity to abundance and why skills, culture, and mindset will make this shift possible.  

#PutAIToWorkForPeople

Magic happens when brilliant people work together to make an even bigger impact.

I cannot pretend to speak words more succinctly than a highly successful CEO, but I CAN share those words.

Jeffrey shared some treasure today, and he even added a bit of elegant reframing.

I believe this restatement by Jeffrey is what we are all charged with, even if your role does not include responsibility for leading or managing teams.

"Your job is to provide the clarity, culture, and energy that allows a team to move."

This is probably the most valuable blog post I will read all week. 

Thanks for sharing this, Jeffrey Snover.

Open article: Welcome to the Room by jsnover.com

I help CIOs, CTOs, and infrastructure leaders modernize legacy environments into platforms that are ready for AI, resilient by design, and simpler to operate.

As VP of Modern Infrastructure at Arctiq, I lead strategy and customer engagements across hybrid cloud, data protection, and modern infrastructure transformation... aligning architecture decisions to business outcomes (risk reduction, performance, speed, and cost control).

My background spans enterprise architecture, presales leadership, and Field CTO roles, bridging exec priorities with what actually works in production. I’m strongest when the ask is complex: modernization, VMware crossroads, cloud operating models, data protection redesign, or building an AI ready foundation without creating security or cost chaos. 

If you’re evaluating modernization paths (stay/optimize vs migrate), tightening resilience, or building an AI ready infrastructure roadmap, I’m happy to compare options and pressure test the plan.
Best way to reach me: DM here or use the link/button on my profile.

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