Building AI Team Capabilities

Training Program Structure

Tier 1: AI Literacy (Everyone) Duration: 2-4 hours Audience: All employees

Topics:

• What are LLMs and how do they work?
• When to use AI vs traditional solutions
• Prompt engineering basics
• AI safety and responsible use

Tier 2: AI Practitioner (Technical Teams) Duration: 1-2 days Audience: Developers, data scientists

Topics:

• API integration patterns
• Fine-tuning fundamentals
• RAG architecture
• Testing and evaluation
• Cost optimization

Tier 3: AI Specialist (AI Team) Duration: Ongoing Audience: ML engineers

Topics:

• Model architecture deep dives
• Training infrastructure
• Deployment and scaling
• Research paper reviews

Internal Playbook Components

1. Decision Framework

<svg viewBox="0 0 569 131" xmlns="http://www.w3.org/2000/svg" style="max-width:100%;height:auto" role="img"><rect x="0" y="0" width="569" height="131" rx="12" fill="#0d1117"/><g font-family="ui-monospace,SFMono-Regular,Menlo,Consolas,&quot;Liberation Mono&quot;,monospace" font-size="14"><text xml:space="preserve" x="20" y="31.7"><tspan fill="#c9d1d9">Should we use AI for this task?</tspan></text><text xml:space="preserve" x="20" y="50.7"><tspan fill="#6e7681">├──</tspan><tspan fill="#c9d1d9"> High stakes, regulated </tspan><tspan fill="#6e7681">→</tspan><tspan fill="#c9d1d9"> Proceed with caution, human review</tspan></text><text xml:space="preserve" x="20" y="69.7"><tspan fill="#6e7681">├──</tspan><tspan fill="#c9d1d9"> Creative, generative </tspan><tspan fill="#6e7681">→</tspan><tspan fill="#c9d1d9"> Good fit</tspan></text><text xml:space="preserve" x="20" y="88.7"><tspan fill="#6e7681">├──</tspan><tspan fill="#c9d1d9"> Simple, deterministic </tspan><tspan fill="#6e7681">→</tspan><tspan fill="#c9d1d9"> Maybe not needed</tspan></text><text xml:space="preserve" x="20" y="107.7"><tspan fill="#6e7681">└──</tspan><tspan fill="#c9d1d9"> Complex reasoning </tspan><tspan fill="#6e7681">→</tspan><tspan fill="#c9d1d9"> Test carefully</tspan></text></g></svg>

2. Model Selection Guide

3. Prompt Templates Standardized templates for common tasks:

• Customer support responses
• Code review suggestions
• Document summarization
• Data extraction

4. Security Guidelines

• Never send PII to external APIs without anonymization
• Use internal models for sensitive data
• Audit logs for compliance
• Regular security reviews

Measuring Training Effectiveness

Resources for Teams

• Internal AI documentation wiki
• Slack channel for AI questions
• Office hours with AI team
• Example code repositories
• Case studies and success stories