In this one-day training, you will dive deep into advanced prompt techniques for power users who want to structurally integrate AI into complex, professional workflows. You will go beyond standard prompting: you will work with chain-of-thought and tree-of-thought reasoning, build multi-step prompt chains, apply system-level instructions, and integrate AI with external tools and APIs. Through intensive hands-on exercises with Large Language Models (LLMs), you will discover how to objectively measure, benchmark, and systematically improve the quality of prompt outputs, and how to make AI collaborate with the tools you already use every day.

What you will learn

• Chain-of-thought and tree-of-thought prompting: making AI reason step-by-step for more complex and reliable output.
• Prompt chaining: building multi-step workflows where the output of one prompt serves as the input for the next.
• System-level prompting and instruction tuning: giving AI structural behavior through system instructions and persistent context.
• RAG (Retrieval Augmented Generation): combining AI with external knowledge sources for accurate, source-based answers.
• Multimodal prompting: effectively combining text, images, and other input forms in complex prompts.
• Integration with APIs and external tools: connecting AI to data, applications, and automated workflows.
• Evaluation and benchmarking: objectively measuring prompt quality, comparing via A/B testing, and systematically optimizing.
• Using personas and dynamic role-switching for targeted and consistent AI output.

Content (overview of the program)

Part 1 – Chain-of-thought & tree-of-thought prompting

• Making AI reason step-by-step for more complex, reliable, and well-substantiated output.

Part 2 – Prompt chaining & automated workflows

• Building multi-step prompt chains where each step builds on the previous one.

Part 3 – System-level prompting & instruction tuning

• Setting up persistent instructions, system control, and consistent AI behavior profiles.

Part 4 – RAG & multimodal prompting

• Integrate external knowledge sources and combine text, images, and data into a single workflow.

Part 5 – Integration with APIs & external tools

• Connect AI to data sources, applications, and automated processes without coding.

Part 6 – Evaluation, benchmarking & A/B testing

• Objectively measure prompt quality, compare results, and optimize systematically.

Part 7 – Custom use cases & Q&A

• Develop complex work examples, identify patterns, and create a personal action plan.

• Advanced users of ChatGPT, Copilot, or other AI tools who want to go beyond standard prompting.
• Professionals who want to structurally embed AI into complex work processes.
• Anyone who wants to deploy AI as a fully-fledged part of their professional toolkit, without needing to code.

Prerequisites

• Solid foundational experience with ChatGPT, Microsoft Copilot, or other generative AI tools is required.
• The beginner Prompt Engineering training or demonstrable practical experience with prompt techniques is highly recommended.