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

Explorer of uncharted spaces. Twice voted in the UKTech50, Judge in Nesta's Open Banking and Netflix's Open Source competitions, Co-Chair of OSCON Europe, Cloud Camp and Map Camp. Regular speaker on the global tech circuit.

Simon Wardley

X : Is Eric Schmidt right about software engineers being replaced?

Me : Lol, yes he has gone very quiet on that subject. 

X : So, he is wrong?

Me : Well, software engineers will be replaced by computational product realisers, machine collaboration architects, digital workflow synthesisers, technology decision auditors, AI enablement strategists, Human-AI systems integrators, codebase curators, technical debt reconciliation officers, platform realisation facilitator ... I'm sure he'll pretend that is what he meant.

X : Who the hell are those people?

Me : AI wranglers / Agentic herders. 

X : What the hell is that?

Me : Software engineers wrangling agents. Just don't tell Eric or your board if you've said something daft like "we're getting rid of software engineers".

X : Any examples?

Me : It's still emerging but there is a slow and inevitable path to the AI wrangler. Welcome to Gas Town - https://lnkd.in/eWcXpuWD

X : What's missing?

Me : Understanding but for that we need to change tools and turn software engineering into an engineering topic (talk to Tudor Girba)

X : What tools do we need?

Me : Contextual ones. You can't buy them, you'll have to build them. Don't worry, you'll be wrangling the AI agents to build those as well. We've got a good few years to go before the practices really start to converge. It's early days.

X : Should I be putting this into production?

Me : Now? I'd caution you to be learning, experimenting, prototyping, adapting and developing the skills. You certainly don't want to become the next Knight Capital.

X : Who's that?

Me : A company that lost comprehension of its IT and paid the price for this. It lost over $400M in about 45 minutes. We'll need a few of those for the practices to converge, try not to be that example. 

X : But my company is getting rid of software engineers.

Me : Well, they can join the long list of companies that will learn the lesson of Jevons Paradox and be involved in the mad scramble to hire AI wranglers (aka, the software engineer you got rid of but at inflated prices).

X : But AI will replace humans.

Me : I think you'll find that AI will mostly replace tasks. This was pretty clear back in 2021 (attached). You might want to spend less time with Eric or ChatPPT consultants.

X : Who the hell are they?

Me : They're like PPT consultants but replaced with AI. This is one of those cases where replacement is probably a good idea.

X : PPT?

Me : PowerPoint. Think management consultants. Think McKinsey.

X : Aren't they being replaced with AI?

Me : Hopefully.

X : What will they do?

Me : What they always do, try and hide in Government by pretending they bring a unique blend of commercial skills ... with PowerPoint. Hmmm, we really should think about weaponizing them and then send them into Governments we don't like.

X : Anyone else?

Me : As I said back in 2016, the board is another good target - https://lnkd.in/e2jyeJG5 - but they will see themselves as a special case.

I like ducks, they’re fowl but not through choice. Professional Context Smuggler. Wardley Mapping by the inventor - swardleymaps.com

"Any realistic path to increased agency will be expensive and take years. To be sustainable, it must focus on commoditizing existing solutions through interoperability and de facto standards that will broaden the market (and enable effective) national champions. This should be our north star and direction of travel." ... spot on by David Eaves, and the keyword is de facto. 

Where possible, the de facto should be adopted in law and where necessary patent & copyright law adjusted to fit. The concept of compulsory licensing, public interest proportionality and even utility model patents in China are worth examining. Different stages of technological evolution require different legal instruments and thresholds. UK governance should be observing when systems are starting to become non substitutable, critical, socially embedded and infrastructural rather than discovering that dependency late due to rent seeking or other harm. The law needs to follow the technical realities of evolution early, with standards as tools of governance rather than instruments of markets. Our current IP processes are not fit for purpose but then again, they were designed for a different technological era. 

Learn from China’s systemic approach of early sensing dependency, coordinated use of standards, policy, regulation and courts with a willingness to recalibrate IP enforcement once technologies become infrastructural. Become more of a "market maker" than a "market taker" ... and start treating sovereignty seriously. ->

Chief Digital Adviser - UK Public Sector at Red Hat & Author of "Delivery Management: Enabling Teams to Deliver Value"

This is a fantastic read - Government doesn't need to own the trains and tracks (data centres) but it should mandate the gauge (standards).

I have used an analogy similar to this for a long time having seen a Director in the Civil Service, responsible for a large area of technology, confidently assert that "containers can run anywhere" without any consideration for the fact that the proprietary choices made in their Directorate would mean every train ran on different gauge tracks. 

They had zero portability in their "multi-cloud" which essentially amounted to nothing more than multiple clouds.

taplio

The Battle

Daniel Lemire

Simon Wardley

Followers

Posts

Engagements

Likes

Performance ScoreDaniel Lemire's LinkedIn Performance

Performance ScoreSimon Wardley's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Daniel Lemire

Simon Wardley

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Daniel Lemire's LinkedIn Performance

Performance ScoreSimon Wardley's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreDaniel Lemire's LinkedIn Performance