Month: July 2026

Both Sides Now – Cloud and AI

“I’ve looked at clouds from both sides, now 

From up and down, and still somehow 

It’s cloud illusions, I recall 

I really don’t know clouds at all”

Those hauntingly beautiful lyrics from Joni Mitchell – recorded back in her 1966 live performance at the Second Fret – resonate with me today in a way they never did when I first heard them.

It has been 15 years since I led my first cloud implementation. Back then, the “cloud” felt like a radical experiment. I have vivid memories of the early days – days when I had to use my own personal credit card to shoulder the team’s cloud expenses just to keep our projects running while we fought for internal buy-in.

Back then, I thought I knew exactly what the cloud was. I was wrong.

Today, looking back from 2026, I realize that “knowing the cloud” isn’t a destination; it’s a continuous, evolving journey. We have moved from simple infrastructure migration to complex, distributed architectures, and now, we are in the era of AI-driven cloud computing.

If the last 15 years taught me anything, it’s that the technology will always outpace our current understanding. The “cloud” isn’t just about servers or storage anymore – it’s the foundation upon which the intelligence of tomorrow is being built.

In this era of rapid AI acceleration, the biggest risk isn’t the technology failing; it’s our own willingness to stop learning. Staying relevant means constantly “looking at the clouds from both sides” – the cost side and the innovation side, the technical debt and the architectural opportunity, the legacy systems and the generative future.

I started with a credit card and a dream of agility. Today, I’m still learning, still iterating, and still finding that the more I know, the more I realize there is to explore.

How has your relationship with the cloud evolved over the last decade? Are you finding the AI era to be the most challenging (or exciting) shift yet?

#CloudComputing #ContinuousLearning #AI #DigitalTransformation #CloudJourney

Learning AI

Many people ask me, “What’s the best way to learn AI?”

I always ask them a few questions in return:

 • How did you learn how to swim?
 • Did you learn by reading textbooks?
 • By watching YouTube videos?
 • By just walking around the edge of the pool?

Probably not. We all know the only real way to learn swimming is to dive into the deep end, start paddling, and figure out the doggy paddle before moving on to breaststroke or freestyle.

𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗔𝗜 𝗶𝘀 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲.

Too many people get stuck in “tutorial hell.” They read endless articles, bookmark 500-page books, and watch hours of videos without ever opening a single tool.

The secret to mastering AI isn’t theory – it’s execution.

If you want to actually build your AI skills, you need to get your hands dirty. Step by step:

 • 𝗣𝗶𝗰𝗸 𝗼𝗻𝗲 𝘁𝗼𝗼𝗹. Don’t try to learn 20 platforms at once. Start with Gemini, AI Studio, Midjourney, or a basic coding framework depending on your goals.

 • 𝗚𝗶𝘃𝗲 𝗶𝘁 𝗮 𝗿𝗲𝗮𝗹 𝗷𝗼𝗯. Don’t just ask it to tell you a joke. Use it to draft a proposal, analyze a messy spreadsheet, brainstorm marketing copy, or debug a piece of code.

 • 𝗙𝗮𝗶𝗹 𝗮𝗻𝗱 𝗶𝘁𝗲𝗿𝗮𝘁𝗲. Your first prompt will probably give you a mediocre answer. That’s your cue to swim harder. Tweak your inputs, adjust your constraints, and see how the output changes.

Stop standing on the edge of the pool watching everyone else swim. Pick a tool, jump in, and start paddling. The water is fine.

How did you first get started with AI?

#AI #ArtificialIntelligence #ContinuousLearning #Upskilling #Productivity

AI As Our Compass

“𝘕𝘰𝘵 𝘵𝘩𝘦 𝘤𝘰𝘯𝘧𝘪𝘥𝘦𝘯𝘤𝘦 𝘵𝘩𝘢𝘵 𝘐 𝘸𝘰𝘶𝘭𝘥 𝘢𝘭𝘸𝘢𝘺𝘴 𝘬𝘯𝘰𝘸 𝘵𝘩𝘦 𝘢𝘯𝘴𝘸𝘦𝘳. 𝘉𝘶𝘵 𝘵𝘩𝘦 𝘤𝘰𝘯𝘧𝘪𝘥𝘦𝘯𝘤𝘦 𝘵𝘩𝘢𝘵 𝘦𝘷𝘦𝘯 𝘸𝘩𝘦𝘯 𝘐 𝘥𝘪𝘥𝘯’𝘵 𝘬𝘯𝘰𝘸 𝘵𝘩𝘦 𝘢𝘯𝘴𝘸𝘦𝘳 𝘺𝘦𝘵 … 𝘐 𝘤𝘰𝘶𝘭𝘥 𝘧𝘪𝘨𝘶𝘳𝘦 𝘪𝘵 𝘰𝘶𝘵.”

When AMD CEO Lisa Su shared this during the 2026 MIT Commencement Address, she wasn’t just talking about engineering. She was describing the exact mindset we need to navigate the era of Artificial Intelligence.

Right now, there is a massive temptation to treat AI as an “answer machine.” Need a strategy? Ask AI. Need code? Let AI write it. Need to solve a complex business bottleneck? Prompt it out.

But if you are using AI to give you all the details, all the answers, and every single step to solve a problem, you are missing its true power – and putting your own growth at risk.

𝗔𝗜 𝘀𝗵𝗼𝘂𝗹𝗱 𝗻𝗼𝘁 𝗯𝗲 𝘆𝗼𝘂𝗿 𝗺𝗮𝗽; 𝗶𝘁 𝘀𝗵𝗼𝘂𝗹𝗱 𝗯𝗲 𝘆𝗼𝘂𝗿 𝗰𝗼𝗺𝗽𝗮𝘀𝘀.

When we rely on AI to hand us the final solution on a silver platter, we bypass the most critical part of professional development: the struggle of figuring it out. The messy, frustrating, iterative process of trial and error is exactly how we build genuine expertise and intuition.

The most effective leaders, builders, and creators don’t use AI to replace their thinking. They use it to 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲 their thinking. The goal isn’t to let the tool know the answer for you. The goal is to use the tool to help *you* figure it out. Because at the end of the day, the machine doesn’t carry the stakes. You do.

As Lisa beautifully concluded in that same address:

“Technology itself does not decide what the future looks like. People do.

For all the promise of AI … AI cannot decide which problems are worth solving. It cannot make the hard judgment calls with imperfect information. It cannot take responsibility for the outcome. These are our responsibilities.”

How are you balancing AI assistance with your own critical thinking? Talk to us about implementing Gemini Enterprise in your organization to achieve both.

#ArtificialIntelligence #Leadership #CriticalThinking #TechLeadership