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

You want a real AI mistake story?

I set up Claude Code on my new NVIDIA Jetson AGX Thor. Hit an issue immediately. In retrospect it probably not smart to run a coding agent on the same machine that's also running a local model. 

Ok, let’s try again and keep ‘em separated.

Got everything running. OpenAI Codex + GPT-5.2 as the main agent, Anthropic sub-agents for the heavy lifting. I tell Claude explicitly: "Use these agents for this project. Always refer to it by this name."

Claude says: great.

Time passes. I check in.

"How's that project going?"

"Oh, I haven't been working on that."

No alarm. No flag. No warning.

"Alright, let's get moving on it."

"Will do." 

Then proceeds to use GPT-5.2 !! (not the Anthropic agents I specified.)

What happened next? We exhausted the Codex tokens. And then everything broke. I had asked for a fallback to the local model but that wasn’t configured with a large enough context window to work with OpenClaw. 

This is the part nobody talks about when they say "just tell the AI what you want."

Context windows drift. Agents forget. Token budgets run dry in the background while you think work is happening.

I found a way to turn this into an asset. But first I had to live through the mistake.

That's the beauty of AI MISTAKES. Right?

Go make some.

ServiceNow AI Consultant | AI MISTAKES | Transformation | DevOps

GPT-5.3 instant. Gemini 3.1 Flash Lite. (That's just today)

Every week, we get a new capability. 

Skills. Agents. Interfaces. Apps.

Here's the problem: People often don't really know what to do with it all.

Model choice is a thing, as are all the other new things that arrive apace.

But if your team can't turn that choice into value, you're just adding complexity.

I see this constantly in enterprise AI: Companies and their knowledgeable experts obsess over which model to use rather than asking what problem they're trying to solve. 

Especially when it comes to advanced AI models, we all want the latest, the most accurate, the fastest, the cheapest...

The real problem is neglecting to define success.

The best AI strategy isn't about the model. 

It's about:
→ Knowing your use case
→ Picking the right tool for the job
→ Shipping something that works
→ Iterating based on real feedback

Stop optimizing for choice. Start optimizing for impact.

We are no longer talking about just an AI chatbot, or even an AI agent. 

This is the help I've been excited about Generative AI making real.

For years, people have been talking about AI as a tool – something you use, something you prompt. What we’re building at  ServiceNow is different – where AI is a true teammate working alongside you. 

We’re launching two new agentic innovations: ServiceNow EmployeeWorks, and near and dear to my heart (and team), ServiceNow Autonomous Workforce! 🚀  

With ServiceNow Autonomous Workforce, AI specialists are augmenting human teams by actually executing jobs – coordinating across systems, making decisions, acting with precision. Because ServiceNow combines AI intelligence with workflow orchestration, AI specialists can interpret a request, decide the right action using business context, and execute autonomously across systems with governance built in.

It’s a new class of digital workforce designed to earn trust every step of the way. Built on our AI Platform. Grounded in our Knowledge Graph. Orchestrated through Workflow Data Fabric. Governed by AI Control Tower.

We’re just getting started! Kudos to everyone on my amazing team who has been working behind the scenes to bring this to life for our customers. Julie Black Greg George Simon Fauvel Amanda Joslin  

Check out my video with Bhavin Shah below and learn more: https://lnkd.in/d56whgXh

Not AI hype. 

Not AI in theory. 

AI you can actually use. 

Register now and let's get to work. 

Seriously. I'll see you there, come on, let's go!

https://lnkd.in/gTj6hDXf

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You've seen it, you visit a website that gives you that great new chatbot experience, and it tells you what to do. 

What you probably haven't see is AI that does it.

Does what?

Expense reports.

Drafting emails.

Handling service desk tickets.

It's not just a platform. It works! 

Let's put AI to work, so you can focus.

Join us live on February 26 to see it in action. https://lnkd.in/gkhd-GGi

The future isn't waiting for your permission to arrive.

Right now, AI is rewriting the rules of work, creativity, and problem-solving at a pace that makes yesterday's innovations feel ancient. 

Some people are paralyzed by the speed of change.
Some are trusting AI blindly, copying and pasting their way to mediocrity.
Others are sitting on the sidelines, hoping it all goes away.

Here's the thing about transformation:
It doesn't care if you're ready.

It's not all good though, so the only way to know is start. 

You need to get started. 

Think about it this way:
→ Every breakthrough started with someone willing to experiment
→ Every innovation came from learning what didn't work
→ Every expert was once a beginner who kept going

MISTAKES aren't just acceptable in this new world.
They're the curriculum.

When you learn to work WITH AI instead of being replaced BY it, something shifts.

You stop being a passenger.
You become a pilot.

The world needs people who can think critically about AI, use it responsibly, and create real value.

What's one AI experiment you've been hesitant to try? 

What's holding you back?

How can I help?

REST is great. 

CRUD is essential.  

But neither of these things means you’ll come away with a functioning app that is easy to use while also data-model compliant 
with governance enabled. 

Build Agent solves this.

For those evaluating vibe coding on ServiceNow: I ran the same app through five approaches and documented everything.

Three paths used Claude Opus from outside the platform. Namely, raw REST API calls, REST to build a workspace, and the ServiceNow SDK with its Fluent API. Two used ServiceNow Build Agent from within. Same brief, a Travel Request app.

Every approach created the data model in minutes. The UI is the hard part.

REST took 2 hours and 4 failed iterations to land on a working UI. The workspace attempt never finished. The SDK deployed the entire backend from a single prompt in 18 minutes and its Workspace Fluent API successfully created a native workspace, something REST couldn't achieve at all. But the custom UI page and dashboard still couldn't reach parity with Build Agent despite multiple iterations.

Build Agent delivered a working custom UI from one prompt in 20 minutes. A full workspace with dashboard, charts, business rules, Polaris, mobile-ready, upgrade-safe. All within five prompts, under 15 minutes.

The AI models are equally capable. The variable is where the agent operates. Build Agent is fastest for interactive building. The SDK is the path for teams who need Git, CI/CD, and promotion pipelines. Both are platform-native. Both sidestep the friction that REST hits.

Full comparison, iteration artefacts, and every limitation documented, see comments for the GitHub repo in case you want to reproduce this.

The Cumaean Sibyl wrote her prophecies on oak leaves and let the wind decide how they landed. Most of us speak in vibes now.

Frito-Lay

System Analyst

•	Managed and optimized SAP order flow, troubleshooting IDOC failures and providing on-call support for mission-critical systems, ensuring seamless business operations
•	Administered and maintained Active Directory, overseeing user management, Group Policy configurations, and printer server deployments, while executing firmware upgrades and managing Microsoft 365 (Office 365) environments
•	Led infrastructure maintenance and automation, performing server reboots, OS installations, and VM patching to enhance system stability and performance. Implemented AWS CloudFormation to provision cloud infrastructure and leveraged AWS Code Pipeline for CI/CD automation, streamlining code deployment and testing workflows
•	Utilized ServiceNow to track, manage, and resolve incidents efficiently, ensuring high availability and minimal downtime for end-users through proactive support and continuous monitoring
•	Diagnosed and resolved Linux file system issues, troubleshooting disk space constraints, file system corruption, and mount misconfigurations. Used df -h and other system monitoring tools to verify disk health, correct file permissions, and manage user accounts for seamless access control

System Administrator

TEKsystems/Microsoft

· Resolved Azure issues: VM performance, disk latency, browser compatibility.
· Diagnosed VM issues using ASC logs, IOSTAT, VMSTAT, SAR.
· Assisted with Docker Containers and Terraform for VMs and VPC automation.
· Utilized S3 for storage solutions and aided customers in CodePipeline setup.

Cloud Engineer

Sovereign Lending Group Incorporated

· Supported 50+ local and 250+ remote users in Office 365 setup and MFA.
· Troubleshot origination software, VOIP, and DHCP issues.
· Performed LAN/WAN troubleshooting and server patching via WSUS.

System Support Analyst

Loan Depot

· Managed SAN servers, mailboxes, IP phones, and network hardware.
· Resolved LAN connectivity issues and used SolarWinds for network monitoring.
· Coordinated incident management and vendor escalation.

Desktop Analyst

•	Provided Tier 1 and Tier 2 support, troubleshooting hardware, software, and network issues while ensuring minimal downtime for end-users
•	Managed Active Directory user accounts, permissions, and Group Policies, supporting seamless access control and security compliance
•	Transitioned into a System Administrator role, overseeing server maintenance, OS deployments, and patch management to enhance infrastructure stability

I have worked in the IT industry for over 20 years, on many platforms, including Windows, Linux, Networking, and the Cloud. I'm currently a student at Level Up In Tech, where I'm enhancing my skills as a DevOps Engineer. I'm a very driven person who enjoys learning and the challenges that technology has to offer. IT is my passion, and I continue to strive to become even more proficient as an IT professional.

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Daniel Lemire

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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

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