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AI Systems Prompting Guides - Complete Collection

Overview

This collection provides comprehensive prompting guides for six major AI systems, each tailored to their unique capabilities, interfaces, and use cases. The guides follow a consistent structure while highlighting the distinctive features and optimal prompting strategies for each system.

Guide Collection Summary

Chat-Based AI Systems

1. ChatGPT Prompting Guide

Focus: Conversational AI with strong reasoning and multimodal capabilities Key Strengths:

  • Custom instructions for persistent preferences
  • Multimodal processing (text, images, audio)
  • Code interpreter and data analysis
  • Web browsing capabilities
  • Extensive plugin ecosystem

Best For: General-purpose tasks, content creation, data analysis, coding assistance, research

Unique Prompting Approaches:

  • Role-playing and persona adoption
  • Chain-of-thought reasoning
  • Few-shot prompting with examples
  • Iterative refinement through conversation
  • Custom instructions for consistent behavior

2. Gemini Prompting Guide

Focus: Multimodal AI with massive context window and Google ecosystem integration Key Strengths:

  • 1M+ token context window for large documents/codebases
  • Superior multimodal reasoning
  • Built-in Google Search integration
  • Code execution capabilities
  • Strong analytical and research capabilities

Best For: Large-scale analysis, comprehensive research, multimodal tasks, complex reasoning

Unique Prompting Approaches:

  • Long-context utilization for entire codebases
  • Search-grounded prompting for current information
  • Multimodal chain-of-thought reasoning
  • Structured analytical frameworks
  • Comprehensive context provision

3. Manus AI Prompting Guide

Focus: Autonomous AI agent that executes complete tasks and delivers finished results Key Strengths:

  • End-to-end task execution
  • Multi-deliverable project completion
  • Autonomous workflow management
  • Professional-quality outputs
  • Deployment-ready solutions

Best For: Complete project delivery, business automation, comprehensive solutions, professional deliverables

Unique Prompting Approaches:

  • Outcome-focused prompting (not conversational)
  • Comprehensive context provision upfront
  • Multi-deliverable project requests
  • Production-ready specification
  • Autonomous execution trust

Command-Line Interface (CLI) AI Systems

4. Claude Code CLI Prompting Guide

Focus: Agentic coding assistant integrated with development environment Key Strengths:

  • Automatic codebase context gathering
  • Direct file editing and manipulation
  • Git integration and version control
  • Web search for documentation
  • Enterprise platform integration

Best For: Code development, debugging, refactoring, project analysis

Unique CLI Approaches:

  • Concise, terminal-optimized responses
  • Action-oriented prompting
  • Codebase-aware requests
  • Direct file modification commands
  • Integration with development workflow

5. OpenAI Codex CLI Prompting Guide

Focus: Lightweight coding agent with granular autonomy control and safety features Key Strengths:

  • Three-tier approval system (Suggest/Auto Edit/Full Auto)
  • Sandboxed execution environment
  • Version control integration
  • Multimodal input support
  • Safety-first design

Best For: Safe code experimentation, controlled automation, learning and exploration

Unique CLI Approaches:

  • Approval mode specification
  • Safety-conscious prompting
  • Progressive autonomy requests
  • Constraint-driven development
  • Sandboxed experimentation

6. Gemini CLI Prompting Guide

Focus: Large-scale development with Google ecosystem integration and real-time search Key Strengths:

  • Massive context window for large codebases
  • Built-in Google Search integration
  • MCP server connectivity
  • Media generation capabilities
  • Google ecosystem integration

Best For: Large-scale projects, research-driven development, ecosystem integration

Unique CLI Approaches:

  • Large-scale analysis prompting
  • Search-integrated development
  • Multi-phase project prompting
  • Ecosystem integration requests
  • Research-driven implementation

Key Differences and Selection Criteria

Chat vs CLI Interfaces

Chat Interfaces (ChatGPT, Gemini, Manus AI):

  • Conversational interaction style
  • Iterative refinement through dialogue
  • Comprehensive explanations and context
  • Multi-turn problem solving
  • Rich formatting and presentation

CLI Interfaces (Claude Code CLI, Codex CLI, Gemini CLI):

  • Direct, action-oriented commands
  • Terminal-optimized responses
  • File system integration
  • Development workflow integration
  • Concise, executable outputs

Autonomy Levels

High Autonomy: Manus AI, Gemini CLI (Full Auto), Codex CLI (Full Auto)

  • Complete task execution
  • Minimal user intervention
  • End-to-end delivery
  • Production-ready outputs

Medium Autonomy: Claude Code CLI, Gemini (with search), ChatGPT (with plugins)

  • Guided task execution
  • Some user oversight required
  • Tool integration capabilities
  • Iterative development

Controlled Autonomy: Codex CLI (Suggest/Auto Edit modes), Standard ChatGPT/Gemini

  • User approval for actions
  • Step-by-step execution
  • Safety-first approach
  • Learning-oriented interaction

Specialization Areas

General Purpose: ChatGPT, Gemini Autonomous Execution: Manus AI Code Development: Claude Code CLI, Codex CLI Large-Scale Analysis: Gemini, Gemini CLI Research Integration: Gemini (all versions), Manus AI Safety-Focused: Codex CLI, Claude Code CLI

Best Practices Across All Systems

Universal Principles

  1. Be specific and clear about requirements and desired outcomes
  2. Provide comprehensive context relevant to the task
  3. Specify constraints and limitations upfront
  4. Define success criteria and quality expectations
  5. Use examples to illustrate desired formats and styles

System-Specific Optimization

  1. Match prompting style to interface: Conversational for chat, direct for CLI
  2. Leverage unique capabilities: Multimodal for Gemini, autonomy for Manus, safety for Codex
  3. Consider context limitations: Massive for Gemini, automatic for Claude Code
  4. Utilize integrations: Google ecosystem, development tools, web search
  5. Respect safety boundaries: Approval modes, sandboxing, version control

Task-Specific Selection

  • Research and Analysis: Gemini (large context + search)
  • Complete Project Delivery: Manus AI (autonomous execution)
  • Code Development: Claude Code CLI or Codex CLI (development integration)
  • Content Creation: ChatGPT (conversational refinement)
  • Large Codebase Work: Gemini CLI (massive context)
  • Safe Experimentation: Codex CLI (approval modes)

Implementation Recommendations

For Development Teams

  1. Use CLI tools for daily coding tasks and development workflow integration
  2. Leverage chat interfaces for planning, research, and complex problem-solving
  3. Apply Manus AI for complete feature delivery and project automation
  4. Combine systems strategically based on task requirements

For Content Creators

  1. Start with ChatGPT for iterative content development
  2. Use Gemini for research-heavy content requiring current information
  3. Apply Manus AI for complete content campaigns and deliverable packages
  4. Leverage multimodal capabilities for visual content integration

For Researchers and Analysts

  1. Use Gemini for comprehensive analysis with large datasets
  2. Apply search integration for current information and validation
  3. Leverage Manus AI for complete research reports and presentations
  4. Combine multiple systems for cross-validation and comprehensive coverage

Conclusion

Each AI system in this collection offers unique strengths and optimal use cases. The key to effective AI utilization lies in:

  1. Understanding each system's strengths and limitations
  2. Matching prompting strategies to system capabilities
  3. Selecting appropriate tools for specific tasks
  4. Combining systems strategically for comprehensive solutions
  5. Adapting approaches based on interface type (chat vs CLI)

These guides provide the foundation for maximizing productivity and achieving superior results across the full spectrum of AI-assisted tasks, from quick development fixes to comprehensive project delivery.