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Level 2: Prompt Engineering for Product Features

Build on your AI fundamentals by mastering prompt engineering to create engaging, AI-driven product features. Learn to craft effective prompts for large language models (LLMs) and integrate them into Blazor apps to enhance user experiences.

Macro View: Why Prompt Engineering Matters

Prompt engineering is the art of communicating with AI models to get the desired output. It's a crucial skill for building AI-powered products that are effective, reliable, and user-friendly. By mastering prompt engineering, you can unlock the full potential of large language models and create innovative products that solve real-world problems.

What You'll Achieve in This Level

By the end of this level, you will:

Understand the principles of prompt engineering and how to apply them to build AI-powered features.

Learn how to use few-shot and chain-of-thought prompting to improve the performance of large language models.

Get an overview of tools like LangChain for building complex LLM applications.

Learn how to integrate LLM APIs into your applications to create intelligent features.

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Practice: Try AI in Action

Try the following hands-on task:

Write a few-shot prompt to classify customer reviews as positive or negative.

Use chain-of-thought prompting to solve a simple math word problem.

Experiment with different prompts in a tool like ChatGPT or the Hugging Face Hub to see how the responses change.

Reflect: What did you learn about how to write effective prompts?

Expand: Broaden Your Perspective

Understand how others are using prompt engineering in the real world:

Khan Academy uses prompt engineering to create personalized learning experiences for students.

Duolingo uses prompt engineering to generate language learning exercises.

GitHub Copilot uses prompt engineering to suggest code to developers.

These examples show that prompt engineering is a powerful tool for building a wide variety of AI-powered products.

Explore: Dive Deeper

Explore the tools shaping prompt engineering’s frontier:

LangChain: A framework for developing applications powered by language models.

Hugging Face Hub: A platform with a vast collection of pre-trained models, datasets, and demos.

Grok API: An API for accessing xAI's Grok model.

These resources offer a hands-on path for those ready to experiment or build their own AI-enhanced systems.

Review Summary

Key Takeaways:

Prompt engineering is a critical skill for building effective AI-powered products.

Techniques like few-shot and chain-of-thought prompting can significantly improve the performance of large language models.

Tools like LangChain and LLM APIs make it easier to build complex AI applications.

Connection to Macro View:

This level has equipped you with the skills to communicate effectively with AI models, enabling you to build more intelligent and user-friendly products. This is a key step in harnessing the power of AI to solve real-world problems.

Lead-In to Level 3:

Now that you know how to build AI-powered features, it's time to learn how to evaluate their performance. In Level 3, you'll learn how to measure the effectiveness of your models and make data-driven decisions to improve your products.

Continue Your Journey

Mastered prompt engineering? Move to Level 3 to learn model evaluation for product performance.

Go to Level 3

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