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Staff Stack
AI-Native Certified Staff

AI-trained operators, proven before you interview

Every Staff Stack operator is certified on the AI tools their role actually uses — and shows the receipts. 15+ AI tools, role-specific practical tests, an AI workflow proof artifact, and a scorecard you see before the first call.

The gap isn't access to AI. It's capability.

75% of knowledge workers already use AI at work, but 71% of leaders say their team still isn't ready to get real value from it. Buying tools is easy; staffing people who use them with judgment is the hard part — and it's the entire reason "AI-trained" has to mean something testable.

Source: Microsoft & LinkedIn 2024 Work Trend Index; Gartner Workforce Readiness 2025.

What "AI-trained" means here

AI-native operators aren't magic — they're disciplined. We certify for these specific behaviours:

  • Turn a messy brief into a clean plan — and ask the right questions early
  • Use AI to draft faster, then verify and improve before shipping
  • Catch what the model gets confidently wrong — hallucinations and brand drift
  • Document decisions and edge cases so work doesn't get lost in Slack
  • Use AI safely — brand-voice guardrails, hallucination checks, PII handling
  • Escalate blockers with context, not panic or silence

How we certify AI proficiency

Role-specific practical test

A timed, hands-on task in the operator's actual discipline — build a Klaviyo flow, QA an ad account, fix a Shopify ticket. Not a generic quiz.

AI workflow proof

Required evidence of AI-assisted work: prompt → output → edits → final deliverable. We hire operators who verify, not button-pushers.

Communication simulation

Async-first: a Loom walkthrough, a written status update, and an escalation message — scored for clarity and judgment.

Recertification every 6 months

AI tools change monthly. Operators re-run certification against an updated rubric twice a year, with ongoing drills via Stack Academy.

Want the full breakdown of the certification process? See StackCertified, or how operators stay current at Stack Academy.

The AI tool stack operators train on

15+ tools across general, coding, creative, and in-platform AI — trained role-by-role, not as a generic checklist.

General AI

  • ChatGPT
  • Claude
  • Google Gemini
  • Perplexity

AI coding

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex

Creative AI

  • Midjourney
  • DALL·E
  • Figma AI

In-tool AI

  • Klaviyo AI
  • Meta Advantage+
  • Shopify Magic / Sidekick

The AI workflow proof — our differentiator

Anyone can claim they "use AI." We require the receipts. Every certified operator submits an AI workflow trace for a real task:

  1. Prompt — how they framed the task to the model
  2. Output — the raw first-pass the model produced
  3. Edits — what they changed, fixed, and rejected
  4. Final — the shipped deliverable, QA'd and on-brand

It's the fastest way to tell an operator from a button-pusher — and you see it before you interview.

MS

Maria Santos

Senior Klaviyo Operator

AI Certified

Overall AI Proficiency

Aggregate certification score

94/100

AI Tools Proficiency

Claude Code
Codex
Prompt Engineering
Cursor / Windsurf
ChatGPT

Communication

Async Communication
Verified by Staff Stack Certification Program

Sample scorecard for illustration.

Frequently asked questions

What does 'AI-trained staff' actually mean at Staff Stack?

It means every operator is certified on the AI tools their role uses and has proven they can use AI with judgment — drafting faster while verifying before they ship. Certification is a timed, role-specific practical test plus an AI workflow proof (prompt → output → edits → final), not a self-reported skill on a resume.

Which AI tools are operators trained on?

Across roles, operators are trained and tested on 15+ AI tools, including ChatGPT, Claude, Gemini, Claude Code, Cursor, GitHub Copilot, Midjourney, DALL·E, Figma AI, Klaviyo AI, Meta Advantage+, and Shopify Magic. Training is role-specific — a retention operator goes deep on Klaviyo AI; a Shopify developer on AI-assisted code review.

How do I see proof before hiring?

You get a candidate scorecard before the interview: test results by category, a sample deliverable from the timed practical task, an AI workflow trace, and a tool-fluency checklist for your vertical. Proof before the interview, not promises.

Does 'AI-native' mean the AI does the work?

No. AI is part of the workflow; QA is the guardrail. We score for verification and judgment, not just speed. An AI-native operator uses AI to move faster, then catches what the model gets wrong and owns the final deliverable.

How do operators stay current as AI tools change?

Through Stack Academy: role-specific prompt libraries, weekly prompt drills against real briefs, tool-rollout playbooks when features ship, a mandatory ethics/safe-use module, and recertification every six months.

Hire operators who ship

AI-trained, StackCertified operators for retention, paid-media, and Shopify agencies. Tested on real work. Ready in 7 days.

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