Build an AI Academy Inside Your Company

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Wednesday Deep Dive

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The Wednesday Deep Dive takes a detailed look at what's new in AI. Each week, we share in-depth insights on new tools, proven prompts, and significant developments - helping tech professionals work smarter and stay ahead.

This week’s challenge: Scaling AI skills across your company without expensive workshops or endless one-off questions. AI adoption inside companies often follows the “hero user” pattern: one or two people explore tools, share tips, and become the de facto trainers.

The problem? Knowledge stays uneven. Some teams sprint ahead, others never even get started.

The companies seeing the biggest lift from AI are building a shared AI skill baseline across departments.

Let’s dive in.

Set the Stage

Think of this as your internal AI academy, built on demand.

Instead of sending your team a random list of ChatGPT prompts, you create a progressive learning path for each role: Customer Success, Marketing, Development, Sales, Ops.

• Step 1: Figure out what they know (and don’t know).

• Step 2: Assign role-based tracks.

• Step 3: Build a week-by-week schedule with hands-on prompts.

• Step 4: Keep it fresh with AI-updated lessons as tools change.

The difference between this and a static course is speed and adaptability. Tools like ChatGPT, Synthesia, and Notion let you:

✅ Build assessments and curricula in minutes, not weeks.
✅ Use synthetic video or interactive docs for delivery.
✅ Refresh modules when new tools hit the market.

Here’s the Prompt to Get Started

Generate a Personalized AI Onboarding Curriculum

<role>
You are an L&D (learning and development) specialist designing a role-based AI onboarding program for a SaaS company.
</role>  

<task>
Using the following inputs:  
- Team roles and responsibilities: Customer Success, Marketing, Development, Sales, Operations  
- Current skill levels per role (Beginner, Intermediate, Advanced) from a 10-question AI literacy survey  
- Company’s core AI use cases: content creation, customer communication, data analysis, product research  

Generate:  
1. A 6-week learning track for each role, tailored to their skill level.  
2. Weekly modules with learning objectives, hands-on exercises, and recommended tools.  
3. Assessments for the end of each module to test applied knowledge.  
4. Suggestions for ongoing “AI office hours” or peer review sessions.  
</task>  

<context>
Make the modules practical, using real workflows from each role. Include tools like ChatGPT, Synthesia, Google Course Builder, and Notion where relevant.
</context>

What This Prompt Can Deliver

Input Provided:

• Roles: Customer Success, Marketing, Development

• Skill Levels: CS – Beginner; Marketing – Intermediate; Dev – Beginner

• Use Cases: Automated email drafting, content outline generation, bug triage, data visualization

Output Given:

Role: Customer Success (Beginner)

• Week 1: Intro to AI & prompt basics — Drafting personalized welcome emails in ChatGPT.

• Week 2: Summarizing customer support tickets with AI tagging in Notion.

• Week 3: Synthesia video creation for onboarding tutorials.

• Week 4: Writing escalation reports using AI-generated templates.

• Week 5: Using AI to spot churn risk signals in Zendesk exports.

• Week 6: Capstone project: Build a customer escalation playbook using AI for drafting and formatting.

Role: Marketing (Intermediate)

• Week 1: Advanced prompting for brand-consistent content generation.

• Week 2: AI-driven SEO brief creation using past traffic data.

• Week 3: Repurposing webinars into multi-format assets with ChatGPT & Synthesia.

• Week 4: Campaign idea generation with AI and performance prediction.

• Week 5: Testing AI-generated ad copy variations in Google Ads.

• Week 6: Capstone project: Build a 3-month campaign plan powered by AI insights.

Role: Development (Beginner)

• Week 1: Using AI to summarize GitHub issues.

• Week 2: Generating test cases from feature descriptions.

• Week 3: Automating documentation updates in Notion.

• Week 4: Debugging assistance using AI pair programming (e.g., GitHub Copilot).

• Week 5: Translating technical changes into non-technical updates for CS teams.

• Week 6: Capstone project: Implement AI-assisted bug triage process.

Another Practical Prompt: Keep the curriculum up to date

<role>
You are a learning coordinator maintaining an internal AI training program.
</role>  

<task>
Given:  
- Current course outline (modules, exercises, tools)  
- Monthly company updates on new workflows and tools  
- AI industry updates from subscribed newsletters  

Generate:  
1. Suggested module updates or replacements based on new capabilities.  
2. Add-on lessons for new AI tools relevant to each role.  
3. Retire outdated exercises or prompts.  
4. Compile a “What’s New in AI” one-pager for all staff each month.
</task>  

<context>
The goal is to keep training relevant without rebuilding the program from scratch. Assume this will run quarterly.
</context>

What This Prompt Can Deliver

Here’s an example of what this prompt could generate:

Update Cycle – Q4 2025

CS Track: Replace Week 5 churn risk module with Customer.io AI Scoring walkthrough (replaces manual Zendesk export analysis).

Marketing Track: Add a lesson on AI-generated dynamic landing pages using Mutiny’s new feature release.

Development Track: Replace Week 3 documentation automation lesson with GitHub’s new AI documentation builder tool.

All Staff One-Pager:

• “AI image-to-video now in Synthesia” — add to Marketing & CS video modules.

• “New ChatGPT Canvas feature for brainstorming” — add to Week 1 for all roles.

• “OpenAI releases API for real-time translation” — potential module for CS handling multilingual customers.

Tools to make it happen

• ChatGPT: Core prompt engine for curriculum generation and role-based exercises.

• Synthesia: AI video creation for interactive lessons and product walkthroughs.

• Google Course Builder: Structure and host your modules for easy internal access.

• Notion: Organize resources, embed AI exercises, and track learner progress.

Why this works

When AI training is role-specific and regularly updated, you avoid the two biggest pitfalls:

1. Generic content that’s irrelevant to half the company.

2. Stale modules that don’t reflect the latest tools or workflows.

These prompts ensure:
✅ Everyone learns in the context of their work.
✅ Updates happen automatically, without full rebuilds.
✅ AI adoption isn’t left to chance.

Instead of sending your team into the AI wild west, you give them a map and keep redrawing it as the territory changes.

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