[Note #2] Kickstarting AI Fluency Across Your Ops Team

Good morning {{first_name | operator}} —

In this issue we unpack ChatGPT’s new long-term memory and its governance ripples, share a proven playbook for raising AI fluency across every department, and deliver a hard-nosed verdict on fileAI’s zero-shot document extraction. Read on for guidance you can plug into live workflows before the next sprint.

What’s inside this note:

AI Ops Radar – ChatGPT gets long-term memory
Field Guide – Kickstarting AI Fluency Across Your Ops Team: templates, trainings, and workflows to get your team confident, not confused
Tool Test-Drive – fileAI (one-shot doc extraction) verdict

Let’s dive in. ☕️

📡 AI Ops Radar

Here’s what happened in AI this week—and why your ops team should care (plus the one move to act on it).

ChatGPT gets long-term memory – OpenAI rolled out a feature that lets the assistant recall past chats automatically (outside the EU/UK for now) and hinted GPT-5 will ship this summer with bigger context windows [the Verge]

Enterprise teams will expect assistants that “remember” projects, but new data-retention behaviour raises privacy, IP-leak and model-drift questions.

Next action → Update your internal AI usage policy: require opt-out or “temporary chat” modes for sensitive topics, and add memory-scope checks to any upcoming GPT-based workflows.

🗒️ Field Guide — Kickstarting AI Fluency Across Your Ops Team

Templates, trainings, and workflows to get your team confident, not confused

The biggest blocker to meaningful AI adoption usually isn't tooling—it's fluency.

People don't use what they don't understand. In our 1,200-person scale-up, I've seen firsthand that strategy decks rarely drive behavior change. The key is making AI feel useful, personal, and immediately applicable to daily work.

That's why we created an internal AI Hub—a Confluence-based resource center with guides, templates, and workflows tailored by team. Here's how we built it.

1. Start with Department-Specific Guides

We skip the generic "What is AI" content and go straight to context-rich playbooks:

How Support summarizes tickets with AI
How Marketing drafts campaigns with AI
How HR streamlines onboarding docs with AI

Each guide is short (1–2 pages), written in plain English, and includes real internal examples. Teams see themselves in the content and start experimenting faster.

2. Offer Short "Confidence-First" Courses

We run 10–15 minute Loom-based courses to build baseline confidence:

AI 101: What it is (and what it isn't)
Prompting for business teams
When to skip AI

The goal isn't mastery—it's comfort. These courses help teams feel safe enough to try AI and smart enough to avoid rookie mistakes.

3. Add Templates & Starter Workflows

We include:

Prompt libraries tailored to each team
Zapier, Make, and n8n blueprints
"Copy + tweak" automations for real use cases like summarizing feedback, tagging tickets, or drafting follow-ups

It's not just theory—it's plug-and-play.

4. Appoint Department AI Champions

Each team nominates an AI Champion: someone who's excited to experiment and help others apply what's in the hub. This decentralizes adoption and scales fluency without bottlenecks.

Key Takeaway

AI enablement doesn't start with training—it starts with translation. If teams can't see how AI applies to their actual workflows, they won't adopt it.

One Thing to Remember

The fastest path to fluency is the first win. Make it small, real, and local.

🔨 Tool Test-Drive — Tool Test-Drive — fileAI

Check it out at file.ai

Verdict: ⭐️⭐️⭐️ / 5 WAIT

Why it’s great

Zero-shot extraction: One API call converts PDFs, scans, and invoices into clean JSON—no template training required.
Built-in enrichment: Cross-file validation and anomaly-flagging help you trust the data before it feeds your workflow.

Why wait

Dev-first, UI-light: No custom templates or branding yet, so ops teams still need engineering help.
Maturity gaps: SOC 2 certification, EU data-residency options, and predictable high-volume pricing are all on the roadmap but not here today.

Next up

Next week we’ll cover the always fun topic of AI governance… How much (or little) can you get away with, what is absolutely necessary and how to approach it practically

Got questions or a win to share? Hit reply — I read every email.

— Marc