Last I wrote about the math behind those “5 years of LLM experience required” job postings.
If you missed it — the short version: a 2024 job posting requiring 5 years of LLM experience was asking for experience going back to 2019, when GPT-2 could barely finish a paragraph. Seven years took it back to 2017 — the same year the foundational research paper that makes modern LLMs possible was first published. The technology was being invented in academic labs at that exact moment.
Those requirements weren’t a bar. They were bluffing. Written fast, reviewed never, posted with confidence by people who didn’t stop to ask whether what they were requiring was even possible.
I got a lot of responses to that post. Engineers who’d been feeling quietly behind for two years. Hiring managers who admitted, off the record, that the requirements were basically aspirational. People who’d been staring at the same postings I had and wondering what they were missing.
What nobody could argue with was the data. The window for genuine, verified, source-level LLM credentials is still open. Barely — but open.
So I stopped writing about it and did something about it.
Going Straight to Anthropic
I didn’t go find a Udemy course. I didn’t find a bootcamp’s interpretation of how Claude works. I went to Anthropic’s own Academy — the people who actually built the thing — and I completed two courses.
Claude 101 — the foundational course. How Claude actually thinks. What it’s optimized for. Why it behaves the way it does. How to work with its design rather than constantly fighting it. This isn’t “here’s how to write a prompt” territory — it’s the underlying philosophy of how the model is built and what that means in practice.
Building with the Claude API — the implementation course. This is where it gets real. Actual API integration. Authentication. Structuring requests correctly. Managing the context window at an architectural level — not just knowing the limitation exists, but designing systems that account for it. Building agentic workflows where Claude takes a goal and pursues it autonomously. Handling the edges where production systems break down because the model did something unexpected. Because it will.
Both completed. Both verified by Anthropic. Both on my LinkedIn profile with credential IDs if you want to check.
Why “Anthropic Academy” Is the Right Answer to Those Job Postings
Most certifications are one step removed from the source. Someone learned the tool, built a curriculum around what they learned, and now teaches it to you. That’s fine — that’s how most education works.
But when the question on the job posting is “Do you know Claude?” — the most direct possible answer is a credential issued by the people who built Claude.
Not a third party’s interpretation. Not someone’s Udemy course. Anthropic saying: yes, this person understands how our tool works and how to build with it.
A random cert says: someone taught this person about Claude.
An Anthropic Academy cert says: Anthropic taught this person about Claude.
That’s not a subtle distinction when you’re a hiring manager trying to evaluate AI credentials in a market full of people who’ve been using ChatGPT for six months and calling it “extensive LLM experience.”
The Timing Is Still Real
We established this in the data two weeks ago — but it’s worth connecting the dots here.
Daily LLM adoption only cracked a majority of professional developers in 2025. The entire industry has roughly two years of real-world experience with these tools. As recently as 2024, nearly one in four developers had zero plans to use AI coding tools at all.
The window for being genuinely early — with verified, source-level credentials from the actual vendor — is still open. Not wide open. But open.
Two years from now, Anthropic Academy certs will be table stakes. Every bootcamp will have an “AI module.” Every LinkedIn will have three AI badges. Right now, in May 2026, it’s still a differentiator.
That window closes gradually and then suddenly.
This Is the Entrance Ramp, Not the Finish Line
Two certs. Two courses. That’s not the destination — it’s the proof of concept.
The Anthropic Claude Code Academy is a full curriculum. Six or seven courses. I’m two in and I’m going all the way through it. Not because I need more badges — I’ve already said what I think about cert collection as a proxy for competence. But because the curriculum is genuinely teaching me things I’m immediately applying, and the projects I’m building alongside it are getting more interesting with every course.
What those projects look like. What the next courses cover. What I’m actually learning as I go deeper into the API — that’s what the next few posts are about.
We’re just getting started.
For Hiring Managers Reading This
I know you’re here. Some of you have connected with me after these posts, which I appreciate more than I’ve said.
Here’s the direct version: if your team is building AI-integrated products — and at this point, the question isn’t if, it’s how fast — the credential that actually answers your question isn’t “years of experience with LLMs.” It’s “can they build with the API, understand the architecture, and ship something that works in production?”
That’s what “Building with the Claude API” actually covers. And Anthropic just said I know it.
The certs are on my profile. The credential IDs are there. The projects are coming.
Previously: 5 Years of LLM Experience Required 🙄 — the math that started this whole conversation.
Next up: What is the Anthropic Claude Code Academy — and why I’m going all in on the full curriculum.