A post that got me thinking
The other day I was scrolling through LinkedIn when I came across a post by Jorge, a former colleague. He was talking about a job listing looking for a GTM Engineer with proven experience in Claude Code, explicitly stating they didn’t want someone “figuring it out on the go.” They wanted an established expert.
Claude Code launched in May 2025. It’s been on the market for just over a year.
Jorge put it well: it’s like expecting to find LeBron James before the rules of basketball have been written.
That stuck with me. Because it’s not an isolated case. It’s a symptom of something bigger that’s happening.
The AI Experts plague
Open LinkedIn on any given day. Within five minutes you’ll find several profiles with “AI Expert” in the bio. Some have been in the field for months. Others for weeks. All of them present themselves as authorities on a technology that the very engineers building it don’t fully understand yet.
I don’t say this as a personal criticism. I say it because it’s literally impossible to be an expert in something that changes daily.
The most advanced models in the world spend months on the market before researchers understand why they work. OpenAI publishes papers about capabilities their own engineers didn’t predict. The benchmarks used to evaluate models become obsolete within weeks. In no other field does the frontier of knowledge move so fast that even its own creators can’t keep up.
Being an expert in something requires deep knowledge of the subject. And that takes years of study and practice on a stable foundation. AI doesn’t have that foundation. It’s under constant construction. What’s true today may be outdated tomorrow.
What exists in practice are not experts. They’re people who learn very fast and in public. Some honest about it. Others not so much.
The problem with pretending you’re keeping up
There’s real pressure behind all of this. Professionals across every sector feel that if they don’t get on the AI train now, they’ll become obsolete. That pressure has a name: AIxiety.
And that anxiety produces curious behavior. People who have been using ChatGPT for three months and call themselves experts. Companies demanding five years of experience in tools that are one year old. Executives who haven’t solved a concrete problem in five years but expect results in under a month, no infrastructure changes, no flexibility, no room to experiment.
As Jorge pointed out in his post: the “engineering” in GTM Engineer means precisely solving for the unknown. If you want someone who doesn’t need to learn anything, you’re not looking for an engineer. You’re looking for an instruction manual. And that manual doesn’t exist yet.
What you should actually be looking for
If someone has “AI Expert” in their LinkedIn bio, they’re not necessarily a bad person. But they’re probably telling you more about their anxiety than their knowledge.
What does exist, and is genuinely valuable, is something different: the person who learns fast, who is honest about what they don’t know, and who has the judgment to separate the hype from what actually works. That’s not called an expert. That’s called a good head on their shoulders.
The only real AI expert, if we’re being honest, is AI itself. And even it can’t explain very well how it works.
We’re all learning. The ones who admit it are the ones I trust the most.