AI Implementation Practitioner

A focused session that separates AI reality from marketing hype. Learn how LLMs, computer vision, and predictive models actually work, then identify high-impact AI opportunities specific to your operations.

• How LLMs and AI models work (no PhD required)
• AI capabilities vs. limitations — what it can and can't do today
• Identifying AI opportunities in your specific operations

Stop getting random outputs from AI. This hands-on workshop teaches systematic prompt engineering techniques — from basic patterns to advanced chain-of-thought reasoning — so your team gets consistent, high-quality results every time.

• Prompt anatomy: system prompts, context, examples, constraints
• The CRISP framework for structured prompt design
• Chain-of-thought and step-by-step reasoning techniques

Build a working RAG (Retrieval-Augmented Generation) pipeline that connects AI to your organization's documents and data. Covers vector databases, chunking strategies, retrieval evaluation, and production deployment patterns.

• RAG architecture: how retrieval-augmented generation works
• Vector databases: choosing and configuring the right one
• Document chunking strategies for different content types

For technically comfortable teams ready to build more powerful AI automations. Connect AI APIs directly, build webhook-triggered workflows, and write light scripts that process documents, analyze data, and integrate with your systems.

• AI API fundamentals: OpenAI, Anthropic, Azure AI
• Webhook-triggered automation workflows
• Building data pipelines with AI processing steps