How this course works
The chapters and lessons below are the fixed course structure. When you start, LearnLive teaches each lesson interactively and adapts examples, pacing, and questions to you.
Complete syllabus
Every chapter and lesson
- 01
Chapter 1 · 3 lessons
How LLMs Behave at Work
- 1.1
Tokens, context & why phrasing matters
8 min · Quick check
Lesson goal: By the end you can explain the concepts of tokens, context, and the importance of phrasing in prompt engineering.
- Define tokens and their role in language models.
- Explain context and how it influences model responses.
- Discuss why precise phrasing is crucial for effective communication with language models.
- 1.2
Instruction-following vs. completion
9 min · Quick check
Lesson goal: By the end you can differentiate between instruction-following and completion tasks in language models.
- Define instruction-following and completion in the context of language models.
- Identify examples of tasks that require instruction-following versus those that require completion.
- Discuss the implications of each approach for prompt engineering.
- 1.3
Failure modes that cost you
8 min · Quick check
Lesson goal: By the end you can identify common failure modes in prompt engineering that can lead to ineffective outcomes.
- Define failure modes in the context of language model interactions.
- List common pitfalls that can occur during prompt design.
- Discuss strategies to mitigate these failure modes.
- 1.1
- 02
Chapter 2 · 3 lessons
The Anatomy of a Production Prompt
- 2.1
Role, task, context, format
10 min · Quick check
Lesson goal: By the end you can identify and articulate the role, task, context, and format necessary for effective prompt engineering.
- Define the role of the prompt in guiding AI responses.
- Explain the specific task that the prompt is designed to accomplish.
- Describe the context in which the prompt will be used.
- Identify the appropriate format for the prompt to achieve desired outcomes.
- 2.2
Few-shot examples from your domain
9 min · Quick check
Lesson goal: By the end you can create few-shot examples relevant to your domain to enhance prompt effectiveness.
- Define few-shot learning and its importance in prompt engineering.
- Identify examples from your domain that can serve as few-shot inputs.
- Demonstrate how to structure few-shot examples for clarity and impact.
- 2.3
Constraints, tone & guardrails
8 min · Quick check
Lesson goal: By the end you can apply constraints, tone, and guardrails to refine your prompts.
- Define constraints and their role in shaping AI responses.
- Explain the importance of tone in prompt formulation.
- Identify guardrails that ensure ethical and safe AI interactions.
- 2.1
- 03
Chapter 3 · 3 lessons
Patterns for Real Tasks
- 3.1
Step-by-step reasoning
9 min · Quick check
Lesson goal: By the end you can understand the importance of step-by-step reasoning in prompt engineering.
- Define step-by-step reasoning and its relevance in prompt engineering.
- Identify scenarios where step-by-step reasoning enhances clarity and effectiveness.
- Discuss examples of prompts that benefit from a structured reasoning approach.
- 3.2
Decompose & chain
9 min · Quick check
Lesson goal: By the end you can decompose complex tasks into manageable components and chain them effectively.
- Define decomposition and chaining in the context of prompt engineering.
- Explain how to break down a complex prompt into simpler, actionable parts.
- Illustrate the process of chaining prompts to build a comprehensive response.
- 3.3
Structured output for pipelines
8 min · Quick check
Lesson goal: By the end you can create structured outputs suitable for various pipelines in prompt engineering.
- Define structured output and its significance in data processing pipelines.
- Identify different formats of structured output and their applications.
- Discuss best practices for designing prompts that yield structured outputs.
- 3.1
- 04
Chapter 4 · 3 lessons
Review, Evaluation & Quality Control
- 4.1
Self-critique & revision
9 min · Quick check
Lesson goal: By the end you can effectively critique and revise your prompts to enhance their quality.
- Understand the importance of self-critique in prompt engineering.
- Identify common pitfalls in prompt creation.
- Learn techniques for revising prompts based on feedback.
- 4.2
Grounding in your own sources
10 min · Quick check
Lesson goal: By the end you can ground your prompts in reliable sources to improve their relevance and accuracy.
- Define what is meant by grounding in sources.
- Explore different types of sources that can be used for prompt development.
- Learn how to integrate information from sources into your prompts.
- 4.3
Evaluating outputs at scale
9 min · Quick check
Lesson goal: By the end you can evaluate outputs from prompts at scale to ensure consistency and quality.
- Understand the criteria for evaluating outputs from prompts.
- Learn methods for assessing the quality of outputs systematically.
- Explore tools and techniques for scaling evaluation processes.
- 4.1
- 05
Chapter 5 · 2 lessons
Shipping Prompts Into Your Workflow
- 5.1
Templates & variables
9 min · Quick check
Lesson goal: By the end you can understand how to effectively use templates and variables in prompt engineering.
- Define templates and variables in the context of prompt engineering.
- Explain the importance of using templates for consistency in prompts.
- Identify different types of variables that can be used in prompts.
- Demonstrate how to create a basic template with variables.
- 5.2
Versioning & iterating safely
9 min · Quick check
Lesson goal: By the end you can implement versioning and safe iteration practices in your prompt workflows.
- Define versioning and its significance in prompt development.
- Discuss the process of iterating on prompts safely to improve outcomes.
- Identify best practices for maintaining version control in prompt engineering.
- Illustrate how to document changes made during the iteration process.
- 5.1