🚀 Google Cloud Lab: Generative AI with Vertex AI: Prompt Design
Prompt engineering is the art of crafting effective inputs to get optimal outputs from large language models. It’s a skill that bridges human intent with AI capabilities.
**Gemini**: Google’s advanced language model family that powers generative AI applications through its API, delivering high-quality text and multimodal responses.
**Vertex AI** is Google Cloud’s unified machine learning platform that simplifies AI development by providing tools for building, deploying, and managing ML models at scale. In this lab, we focused on using its prompt design capabilities to interact with Gemini models effectively.
## Prompt Engineering Best Practices:
1. **Be concise** – Eliminate unnecessary words and get straight to the point
2. **Be specific and well-defined** – Clearly state what you want, providing context and parameters
3. **Ask one task at a time** – Break complex requests into smaller, focused prompts
4. **Include examples** – Demonstrate the desired output format and quality
5. **Convert generative tasks to classification** – Improve safety by constraining outputs
## Example-Based Learning:
The lab demonstrated how examples dramatically improve response quality. By adding examples directly in your prompt, you teach the model how to respond in context:
– **Zero-shot**: No examples provided – “Classify this sentiment…”
– **One-shot**: Single example provided – “Positive: ‘I loved the movie!’ → Classify: ‘The service was terrible'”
– **Few-shot**: 2-5 examples provided – showing various inputs and expected outputs
This hands-on lab provides essential foundations for anyone looking to harness the power of Vertex AI and Gemini models through effective prompt design. The techniques demonstrated not only improve response quality but also help maintain safety and relevance in AI-generated content.
Skill Badge Link – https://www.cloudskillsboost.google/course_templates/976
Lab Link : – https://www.cloudskillsboost.google/course_templates/976/labs/515636#
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