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

Real Shift of AI

I have realized that the world has changed.

In the past, creating something meant weeks of manual execution, if not months. Today, with AI, generating a solution takes less than a few hours, if not minutes. For routine tasks, AI has accomplished what used to require years of specialized training.

Naturally, people are asking: “Will human skills still have value?”

I think this question misses the mark. The issue isn’t whether human skills have value, but how our definition of value has shifted from 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 to 𝘀𝗽𝗲𝗲𝗱.

Yet, while AI has allowed everyone to start creating, truly groundbreaking ideas haven’t increased. Because pressing “Generate” is easy. The real difficulty remains finding the right problem to solve and understanding human nuance.

The future competition is no longer between humans and AI.

𝗜𝘁 𝗶𝘀 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝘄𝗮𝘆 𝗲𝗮𝗰𝗵 𝗽𝗲𝗿𝘀𝗼𝗻 𝘃𝗶𝗲𝘄𝘀 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺.

When everyone’s tools are identical, what sets us apart is not the software, but 𝗼𝘂𝗿 𝘂𝗻𝗶𝗾𝘂𝗲 𝗽𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲, 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴, 𝗮𝗻𝗱 𝘃𝗶𝘀𝗶𝗼𝗻.

Technology never stops moving forward. But what is truly worth keeping around has never been a specific tool. It is the professionals who, through these tools, still bring genuine empathy, leadership, and insight to the table.

The real shift isn’t that AI is replacing human labor. It is that we are growing accustomed to solving problems in the fastest way possible, while slowly forgetting how to think deeply about what is actually worth solving.

Don’t Change People, Elevate Them

“People don’t resist change. They resist being changed.” – Peter Senge

This profound truth is the single biggest reason why so many corporate AI initiatives stall at the starting line.

When organizations introduce AI, the immediate instinct is to focus on the technology: the models, the data pipelines, and the infrastructure. But true AI adoption isn’t a technology implementation challenge. It is, first and foremost, 𝗮 𝗰𝗵𝗮𝗻𝗴𝗲 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲.

If we limit AI’s benefits to a single tech team or a short-lived Proof of Concept (POC), we aren’t driving transformation; we are just running expensive experiments. To capture real value, we must aim for structural change.

How do we achieve that without triggering natural human resistance?

𝗙𝗹𝗶𝗽 𝘁𝗵𝗲 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻

  • Stop asking, “𝘞𝘩𝘢𝘵 𝘤𝘢𝘯 𝘈𝘐 𝘥𝘰 𝘧𝘰𝘳 𝘶𝘴?”
  • Start asking, “𝘞𝘪𝘵𝘩 𝘈𝘐, 𝘩𝘰𝘸 𝘴𝘩𝘰𝘶𝘭𝘥 𝘸𝘦 𝘳𝘦𝘵𝘩𝘪𝘯𝘬 𝘵𝘩𝘦 𝘸𝘢𝘺 𝘸𝘦 𝘥𝘰 𝘵𝘩𝘪𝘯𝘨𝘴?”

𝗗𝗼𝗻’𝘁 𝗖𝗵𝗮𝗻𝗴𝗲 𝗣𝗲𝗼𝗽𝗹𝗲. 𝗘𝗹𝗲𝘃𝗮𝘁𝗲 𝗧𝗵𝗲𝗺.

The goal shouldn’t be to force people to change how they work just to accommodate a new AI tool. Instead, we should use AI to help people implement AI. We need to weave AI seamlessly into their everyday workflows so smoothly that it doesn’t feel like a disruption.

When done right, people aren’t “being changed” – they are being elevated.

By offloading the friction of execution to AI, your team moves up the value chain to become the orchestrators:
  • The 𝗣𝗹𝗮𝗻𝗻𝗲𝗿𝘀: Defining the vision and strategy.
  • The 𝗚𝗼𝘃𝗲𝗿𝗻𝗼𝗿𝘀: Ensuring quality, ethics, and alignment.
  • The 𝗔𝗽𝗽𝗿𝗼𝘃𝗲𝗿𝘀: Making the final, critical decisions.
  • The 𝗕𝗲𝗻𝗲𝗳𝗶𝗰𝗶𝗮𝗿𝗶𝗲𝘀: Enjoying the freedom to focus on high-impact, creative work.

AI shouldn’t feel like an incoming manager rewriting everyone’s job description. It should feel like a supportive colleague that lifts everyone to a higher level.

How is your organization approaching the human side of AI implementation? Talk to us to make this change happen, leveraging our #GeminiEnterprise Agent Platform, our enterprise-class, full-stack AI infrastructure, and our services.

#ArtificialIntelligence #ChangeManagement #DigitalTransformation #Leadership #FutureOfWork