Gemini Prompting

Introduction

Gemini (Google) offers up to a 2M token context window and strong multimodal abilities. It rewards clear formatting and benefits from system instructions.

Beginner analogy: Gemini is the polyglot — huge memory, fluent across text/image/video.

Understanding the topic

Core concepts to understand:

• Use systemInstruction field for persistent rules.
• Up to 2M tokens — feed whole books, codebases, videos.
• Strong multimodal: image + text + video + audio.
• JSON mode + structured output supported.
• Vertex AI integration for enterprise.

Syntax reference

Visual workflow / architecture:

Gemini Request
  systemInstruction: "You are a code auditor."
  contents:
    - text: "Review for bugs."
    - inlineData: { mimeType: "image/png", data: ... }

Real-world use

Used heavily for document understanding and multimodal apps (image + text reasoning).

Best practices

• Take advantage of the 2M window for whole-document tasks.
• Use multimodal — don't OCR images, just pass them.
• Cache long contexts where supported.

Hands-on exercise

Interview preparation — practice these questions:

• Q1. Gemini's unique strengths?
• Q2. systemInstruction vs system message — same?
• Q3. Use cases for 2M context?
• Q4. Multimodal example?