1

The Basics and Prompts

Learn the fundamentals of AI, understand the mindset shift, and master prompt engineering with the AUTOMAT framework

Welcome to the first chapter of The Complete AI Training: from a to i. In this chapter, you'll learn the fundamental principles of working with AI. The most important lesson? Treat AI as a junior colleague, not as a magical tool. By using the right prompting techniques, you can effectively deploy AI for your daily work. We are currently in the middle of a technological revolution. A recent McKinsey Global Survey shows that 71% of organizations now use generative AI, a significant jump from 33% in 2023. The difference between successful and less successful AI users lies not in the tools they use, but in how they use them.

The Fundamental Mindset Shift: AI as Junior Colleague

Many people new to AI fail to unlock its full potential because they approach it as just another software application. This 'tool' mentality is a significant barrier to success. Generative AI is not a deterministic calculator; it is a probabilistic engine that predicts the most logical continuation of given text. To truly harness the power of AI, a fundamental mindset shift is required. **Treat AI as a junior colleague.** This analogy is powerful because it reframes the interaction from command and control to collaboration and mentorship. When new junior colleagues join your team, you don't expect them to have all the specific knowledge of your company. You give them: • Detailed instructions and context • Relevant sources and examples • Feedback on their work • Space to iterate and improve This is exactly the approach you should take with AI. A groundbreaking 2023 study by Harvard Business School, MIT, and Boston Consulting Group showed that effective AI users: • **Completed 12.2% more tasks** • **Worked 25.1% faster** • **Produced 40% higher quality** work The difference? They treated AI as a collaborative partner, not as a magical solution.

The AUTOMAT Framework for Effective Prompts

The AUTOMAT framework is a structured approach to creating powerful prompts. This method ensures you include all essential elements that AI needs to produce high-quality output. **A - Audience** Define who the output is intended for. A technical explanation for engineers differs from an explanation for management. **U - Use Case** Describe the specific purpose. Will it be used for a presentation, an email, or a report? **T - Task** Give a clear instruction. "Write a blog post" is vague. "Write an 800-word blog post explaining the benefits of AI in marketing" is specific. **O - Output Format** Specify the desired format: bullet points, paragraphs, table, JSON, etc. **M - Materials** Provide relevant sources, data, or context. The more context, the better the output. **A - Additions** Add extra instructions: "Don't use jargon", "Add examples", "Keep it under 500 words". **T - Tone** Determine the desired writing style: formal, casual, enthusiastic, professional, etc. **Example Prompt:** "You are a marketing expert (Audience) who needs to create a social media post (Use Case). Write a LinkedIn post (Task) in bullet point format (Output) about the benefits of AI in customer service, use this case study as a basis [add case study] (Materials). Keep it under 200 words and add a call-to-action (Additions). Use a professional but accessible tone (Tone)."

Chain of Thought and Advanced Techniques

One of the most powerful techniques in prompt engineering is **Chain of Thought (CoT) prompting**. This method asks the AI to reason step by step before giving a final answer. This leads to more accurate and better-supported results, especially for complex tasks. **Example of Chain of Thought:** "Solve this problem by: 1. First identifying all relevant factors 2. Analyzing each factor separately 3. Determining the relationships between factors 4. Drawing a conclusion based on your analysis" **Other Advanced Techniques:** **Few-Shot Learning** Provide examples of desired output. "Here are 3 examples of good product descriptions: [examples]. Now write a similar description for [product]." **Role-Playing** Ask the AI to assume a specific role. "You are an experienced sales coach with 20 years of experience. Give advice on..." **Iterative Refinement** Improve output through multiple rounds. "This is good, but can you make it more specific for the tech industry?" **Constraint Setting** Set clear boundaries. "Only use information from 2023-2024", "Avoid technical jargon", "Keep it under 3 paragraphs". These techniques can be combined for even better results. Experiment and discover what works best for your specific use case.

Prompting for Image Generation

Prompting for image generation requires a different approach than text generation. When creating images, you need to specify visual elements, style, composition, and atmosphere. **Important Elements for Image Prompts:** **Subject** What do you want to see? "A red sports car", "A business woman in a suit", "A futuristic city". **Style** Which artistic style? "Photorealistic", "Watercolor", "3D render", "Anime", "Oil painting". **Lighting** "Golden hour", "Dramatic shadows", "Soft studio lighting", "Neon lights". **Composition** "Close-up portrait", "Wide angle shot", "Bird's eye view", "Symmetrical composition". **Details and Mood** "Vibrant colors", "Misty atmosphere", "High detail", "Minimalist background". **Example Image Prompt:** "A professional business woman in a modern office, wearing a navy blue suit, confident pose, natural window lighting, photorealistic style, shallow depth of field, corporate photography, high detail, 4K quality" **Tip:** Use Google's "Say What You See" tool to learn how AI interprets and describes images. This helps you write better prompts.

Did You Know?
  • 71% of organizations now use generative AI, a huge jump from 33% in 2023 (McKinsey Global Survey)
  • 2 billion people worldwide use AI tools (Stanford 2025 AI Index)
  • 90% of companies actively use or research AI
  • AI has surpassed human performance in more and more benchmarks, from image recognition to medical diagnoses
  • The FDA has seen exponential growth in AI medical devices: from a few dozen in 1995 to hundreds in 2023
  • Smaller AI models are performing better - MMLU scores (Massive Multitask Language Understanding) are rising year over year
Real-World Examples
  • **Harvard/MIT/BCG Study**: Consultants who effectively used AI completed 12.2% more tasks, worked 25.1% faster, and produced 40% higher quality work
  • **Bill Gates Quote**: 'The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other.'
  • **Humanity's Last Exam (HLE)**: AI models score increasingly higher on this challenging test measuring human expertise. The latest models achieve accuracies approaching or exceeding human experts
  • **Industrial Robotics**: Industrial robot installation is growing exponentially, with AI-driven automation transforming manufacturing processes
Practical Exercises

This course includes step-by-step exercises you can follow at home. In the complete course material (downloadable as PDF) you'll find practical assignments to develop your prompting skills, from basic AUTOMAT prompts to advanced Chain of Thought techniques. Each exercise builds on the previous one, so you gradually become an expert in effectively communicating with AI.

Key Takeaways
  • Treat AI as a junior colleague, not as a perfect tool
  • Use the AUTOMAT framework for effective prompts
  • Chain of Thought leads to better results for complex tasks
  • Image prompts require specific visual details and style indications
  • Experiment and iterate to get the best results
Download Course Materials

Download the complete PDFs for detailed information, examples, and exercises.