Module 10: Advanced Prompt Engineering

Introduction

Welcome to the final core module! We'll now touch upon **Advanced Prompt Engineering** concepts like System Prompts, parameter tuning, and handling highly complex tasks.

This gives you a broader perspective on controlling AI, often used in application development.

Learning Objectives:

Understand System Prompts vs. User Prompts.
Recognize adjustable AI parameters (e.g., temperature).
Appreciate strategies for complex, multi-step tasks.
See how these build upon fundamental skills.

How this Connects: This overview of more technical aspects broadens your perspective, concluding the core learning modules.

Core Content: Deeper Control Mechanisms

1. System Prompts vs. User Prompts

**User Prompt:** Your direct instruction during the conversation (what we've practiced).
**System Prompt:** Higher-level instruction set *before* interaction (often by devs) defining AI's overall persona, rules, safety guidelines (e.g., "You are a helpful assistant..."). Influences behavior throughout.

Conceptual Example: A hidden system prompt making an AI sarcastic would affect its tone regardless of your user prompt.

2. Parameter Adjustment (e.g., Temperature)

AI models have settings (often not user-facing) influencing output generation.

**Temperature:** Controls randomness. Low temp = focused/predictable (good for facts). High temp = creative/random (good for brainstorming).
**Others:** `top_p`, `max_tokens` (length), penalties for repetition.

Why it matters: Explains variations in creativity/predictability. Developers tune these for specific tasks.

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3. Handling Complex, Multi-Step Tasks

For very complex goals, basic decomposition might not suffice. Advanced strategies include:

**Planning Prompts:** Ask AI to generate a plan first, then execute steps.
**Tool Use:** Integrating AI with external tools (search, calculators, code execution) via APIs to overcome limitations.
**Agent-Based Systems:** Multiple specialized AIs collaborating.

Thought Experiment:

Why might AI need "tools" to plan a vacation with flight/hotel bookings?

Practical Examples (Conceptual)

System Prompt Example (Language Tutor App)

You are a friendly French tutor. Engage the user..., gently correct mistakes..., explain grammar simply... Avoid complex jargon.

Parameter Tuning Example (Creative vs. Factual)

Use higher temperature for story ideas, lower temperature for summarizing legal text.

Complex Task Example (Planning Prompt)

My goal is to write a comprehensive blog post comparing solar panels and wind turbines... Generate a detailed plan outlining research steps, section structure...

Key Idea:

These advanced concepts offer deeper control, often managed "behind the scenes" but based on core principles.

Check Your Understanding

1. What is the primary role of a System Prompt?

a) To provide examples for Few-Shot learning.

b) To set the AI's overall persona, rules, and constraints for a session.

c) To ask the AI a specific question.

d) To control the output format like lists or tables.

2. Lowering the "Temperature" parameter generally leads to:

a) More creative and random responses.

b) More focused, predictable, and deterministic responses.

c) Longer responses.

d) Responses formatted as JSON.

3. Which technique involves breaking a large goal into smaller, sequential prompts?

a) Zero-Shot Prompting

b) Parameter Adjustment

c) Task Decomposition

d) System Prompting

4. Why might an AI need integration with external "tools" (like search) for complex tasks?

a) To make its responses more creative.

b) Because LLMs have inherent limitations (e.g., accessing real-time info).

c) To lower the Temperature parameter.

d) To make the System Prompt work better.

Hands-On Exercise: Conceptualizing Advanced Techniques

Scenario: Create a personalized 7-day meal plan (vegetarian, ~1800 cal/day, dislikes mushrooms, loves spicy) including a shopping list.

Goal: Analyze why a single prompt might fail and identify relevant advanced techniques.

Instructions:

Explain why a single, simple prompt might fail here.
Identify relevant advanced technique(s) (Decomposition, Planning, System Prompt, Parameters) and explain why they apply.
Enter your thoughts below.

Why single prompt might fail: Relevant Advanced Technique(s) & Why:

Expected Outcome:

Recognize the task's complexity requires breaking it down (Task Decomposition/Planning).

Prompt Grading Section

Evaluate your conceptual analysis from the exercise.

Paste your Analysis (Why single prompt fails) here: Paste your Relevant Techniques & Why here:

Evaluation Criteria (Self-Check):

1. Complexity Recognition: Did you explain why a single prompt is insufficient? Yes

2. Technique ID: Did you identify Task Decomposition or Planning Prompts? Yes

3. Reasoning: Did you explain *why* decomposition/planning helps? Yes

4. (Optional) Advanced Concepts: Did you correctly mention System Prompts/Parameters? Yes/NA

Suggestion for Improvement:

For complex goals with multiple steps or constraints, always consider if Task Decomposition would lead to a more reliable outcome.