I want to talk about technical certifications. The AWS, Azure, GCP, Claude kind, the badges we all chase to prove we know a platform. But this isn’t really a piece about certifications. It’s a piece about focus, and it took a certification I couldn’t get to make me see that.
Here’s how it started.
Hitting the wall
I was recently working toward a Claude certification. I’m a heavy agentic user. I use AI for coding, I use it to help me dictate and write articles like this one, I lean on it every day. So getting certified felt like a natural thing to go do. I worked through the training material and, honestly, I learned a lot. It was good material and time well spent.
Then I got to the part where you say, “Okay, great, I’m ready. Let me go test.”
And that’s where I hit the wall. What I found out is that you can’t just take the exam as an individual. The Claude certification lives behind the partner network: you have to be part of an organization that’s an Anthropic partner, registering with a partner company email on a recognized domain. A personal email won’t get you in the door. There’s no standalone path where you, as a person, sign up, pay, and earn the credential.
That was frustrating. I did what you do, and sent an email to ask about it. And of course, what came back was their AI agent replying to me. No human ever followed up.
Now, let me be fair here, because this part matters. It’s their company. They get to set their own priorities and their own certification process, and it makes perfectly good sense that they’d aim this program at partner organizations. I’m not mad at them for it. The only thing I’d really push back on is that it wasn’t clear to me going in. I got pretty far down the road before I found out the door was closed.
But here’s the thing I keep coming back to: compare that to AWS.
The AWS model, and why it’s the right one
With AWS, anybody can sign up and take a certification. You register, you pay, you sit the exam. As you go, you can associate your certs with your employer, and if you move to a new company, they move with you, because they’re yours. You took the test. You paid for it. I pay for all my own certifications, and I like it that way. The credential belongs to the individual who earned it.
That’s the model that respects the person doing the work. The partner-gated model, whatever its business logic, doesn’t. It makes the credential a property of the organization, not the individual. And that’s a real philosophical difference in what a certification is even for.
I could have stopped there and just written a complaint. But the wall did something more useful than annoy me. It made me stop and think. And I’ll admit: maybe I hadn’t been thinking clearly enough about this in the first place.
The question I should have asked first
Here’s the honest reckoning. I’m far enough along in my career that nobody is hiring me to go build out an agentic platform for them, to wire up LangChain and a stack of tools into some custom AI system for a client. That’s who that certification is really for: the person or the shop that builds bespoke agentic solutions for other companies. That’s a great thing to be. It’s just not what I’m going to market.
I’m a heavy user of this technology, but I’m not going to be the guy they hire to architect a custom agentic platform. And once I saw that clearly, the frustration turned into something more valuable: I realized that while I’d learned a lot, I had lost sight of what my actual end goals need to be at this stage of my career.
The certification wall didn’t cost me anything. It handed me a question I should have asked before I started: does this credential map to where I’m actually going?
And then it wasn’t just Claude
Once I noticed the pattern, I couldn’t un-see it, because the Claude detour wasn’t the only one.
Around the same time, a company I was working with was going to do some GCP work. “Hey, we want you to go spin up GCP.” So I started in on some Udemy courses on GCP. I got partway through, and then they changed their mind. Then they came back: actually, we’ve got some major opportunities, we need you on Azure now. Different platform, different courses, different mental model. Off in another direction.
Meanwhile, my core expertise had been in AWS the whole time, and specifically in the Amazon Connect space.
Now, people like to say the clouds are all the same. And conceptually, sure, an S3 bucket has an analog in Azure and in GCP. The building blocks rhyme. But they are not the same when you actually sit down to architect something real. The details are where all the work lives, and the details are different everywhere you look. You can’t fake depth across three platforms by knowing that they each have “a bucket.”
And chasing every platform at once has a cost: it just means spreading yourself thin across tools you’ll never actually master.
So there it was: the Claude detour, the GCP detour, the Azure detour, each one pulling me off my mark. And I know myself. I tend to be highly focused, and I do my best work when I’m highly focused. All of this was doing the opposite.
The interview that made it concrete
I want to give you one more thing, because this is the part that turned my thinking from a feeling into a conviction.
I once interviewed a guy who had certifications in both AWS and GCP. Impressive on paper. But when we got to talking, his actual hands-on experience was in GCP. The AWS side was certificates. So I did what you do in a real interview: I got down into the AWS details. And he couldn’t talk about it. The certificate was there; the substance behind it wasn’t.
That’s the whole problem with treating a cert as the goal. A certificate with no experience behind it doesn’t survive the first real question. Nobody’s going to hire me because I hold a GCP certificate and zero GCP experience, nor should they. Depth is the thing. The badge is just supposed to point at it.
What companies actually wanted
There’s one more piece to this, and it comes straight from the engagements I’ve been doing lately. The companies bringing me in wanted agentic AI, but they very specifically did not want an AI specialist. They didn’t want me to teach them how to train a model, or explain what embeddings are, or walk them through vector databases. None of that. What they wanted was concrete: “We’ve got a knowledge base, and we need it wired up so that when someone talks to our chatbot, it can pull that information in.”
And here’s the quietly important part: that whole knowledge-base model is, at this point, a cracked problem. It’s a known pattern now. In AWS you can spin up knowledge bases all day long, and, being honest about it, it doesn’t take a highly technical person to do it. There might be some obtuse tuning at the edges, but for a general-purpose knowledge base, it’s close to trivial.
Sit with what that means for the specialist credential. The market in front of me isn’t asking for someone who can prove deep AI-platform expertise on an exam. It’s asking for someone who can take a solved pattern and apply it to their actual problem, cleanly and quickly. That’s not a knock on the deep expertise. It’s just not what’s being bought. And it lined up perfectly with everything else I’d been noticing: the value I bring isn’t in being certified as an agentic-platform architect. It’s in knowing my tools well enough to deliver the practical thing the client actually needs.
Where I landed
So here’s where I’m landing, and it ties back to something I wrote about in some of my earlier pieces: the idea I call micro AI .
Micro AI is the concept of people (me, you, all of us) using AI to make our own work easier and better. Not building a giant custom platform for a client, but reducing the cognitive overload of all the small tasks that suck up your time and don’t need to. Letting an agent quietly take that load off your plate so you can spend your attention where it actually counts. That’s where the everyday value of this technology lives, and it’s what genuinely excites me about it.
That’s the direction I’m choosing on purpose. I want to keep exploring and expanding micro AI. I already have a completely agentic workflow around my blog publishing, my book editing, my Amazon Connect practice, and more. That’s how I leverage AI to get more done. And I’ll stay in my core competency, which for me is AWS, where I’ve got over eight years of solid experience. I’m not going to go chase a GCP certificate for a platform I have no depth in, on the theory that the badge alone will open a door. It won’t. I’ve sat on the other side of that interview.
The irony isn’t lost on me that a certification I couldn’t get is what pointed me back to all of this. But that’s how it worked out. The wall didn’t stop me from doing something. It stopped me from doing the wrong thing, and sent me back to the work that actually fits where I am.
If there’s a takeaway in here for you, it’s this: before you pour weeks into the next certification, ask the question I skipped. Not “can I pass this?” You probably can. Ask whether the credential maps to where you’re actually going, and whether there’s real experience underneath it. If the answer is no, that’s not a wall. That’s a favor.