The AX Talent Verification Method for Interviewers — What 30 Minutes Truly Reveals
Wait — did the title catch your eye? ๐
๐ก The Real Problem with Hiring AX Talent
Recently, while commenting on someone's post, I had a realization:
"Why don't they know this? Oh right — you can't know it if you've never actually done AX."
That thought is what inspired this article.
More and more companies are seeking AX (AI Transformation) talent. But there's a fundamental problem: How do you verify AX talent if the interviewer has never done AX themselves? It's like asking someone who can't code to hire a software engineer.
๐ฏ The 30-Minute AX Talent Verification Framework
Here's the method I actually use:
Step 1: Give Them a Topic, Like a Coding Test
Just like a coding test, you give candidates a specific topic. But the rules are different:
- ✅ They can use any AI tool they want
- ✅ Or work within a designated AI environment
- ⏱️ Time limit: 30 minutes
Since they're AX candidates, 90%+ will produce a result. Those who produce nothing? Eliminated immediately.
Step 2: Don't Judge the Output — Judge the Structure
This is where it gets interesting. What matters far more than the output itself is this:
๐ The Folder Structure
✅ Good Example
project-root/
├── docs/ # Requirements, specs, work orders, history
├── src/ # Source code
├── .agent/ # role, rule, skill, workflow
├── .gitignore
├── .env.example
├── AGENTS.md
└── README.md
❌ Bad Example
project-root/
├── main.py
├── test.md (docs scattered in root)
├── config.json
└── result.html
Experienced practitioners can instantly tell: was this folder structure created by AI running loose, or did the candidate deliberately instruct AI to create it this way?
๐ What's Inside the docs/ Folder?
A true AX professional will produce these within 30 minutes:
| Document | Purpose |
|---|---|
| Requirements Definition | What to build |
| Specification | How to build it |
| Work Order | Recorded instructions to AI |
| Work Log | Progress history |
๐ค The .agent Folder
The heart of AX is agent environment configuration. Check if .agent/ contains:
role/— AI role definitionsrule/— Behavioral rulesskill/— Specialized skill definitionsworkflow/— Work pipelines
And whether AGENTS.md and README.md are written with genuine intent.
Step 3: Check Environment Setup Completeness
| Checkpoint | What It Reveals |
|---|---|
Clean .gitignore |
Version control understanding |
Standardized .env.example |
Environment management maturity |
| Dev/prod environment separation | Real-world experience |
Clean docs/ vs src/ separation |
Project structure fundamentals |
⏱️ "Isn't 30 Minutes Too Short?"
Not at all. It's actually comfortable.
In practice, I allow myself 30 minutes for initial client environment setups — enough to configure the agent environment and deliver the first output. (Excluding app/module installation, which adds ~10 minutes.)
The actual output? About 5 minutes.
The other 25 minutes go into building the proper AI working environment.
๐ What This Test Actually Measures
How does this candidate build their own agent environment within 30 minutes, and how do they instruct AI to deliver the result?
That is the true measure of an AX professional.
It's not about knowing how to use AI tools. It's about commanding AI.
๐ฅ Why This Matters: 20x to 100x the Output
One excellent AX talent = 20 to 100× the productivity of an average employee
Finding this person is not easy. Hire the wrong way?
It's like someone who doesn't understand coding hiring "game developers to build a game for 150 concurrent users." The outcome is predictable.
๐ฏ Conclusion: You Can't Hire AX Talent If You Don't Know AX
You have two options:
- Study it yourself — Get hands-on AX experience
- Call an expert — Let an AX practitioner do the verification
I can accurately verify the AX candidates applying to your company. ๐
(Oh no, this turned into a self-promotion post;;;)
Tags: #AXTalent #AIInterview #AXHiring #AgentEnvironment #AITransformation #TalentVerification
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