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Introduction to AI Instructions

Introduction to structured instructions, scopes and AI Tools comparisons.

· Beginner
Requires
  • ai

What Are AI Instructions?

Structured instructions guide how the AI processes, reasons, and formats its response. Think of them as dials and levers on the AI’s behavior.

The Global Scope: What Can Be Controlled?

There are roughly 6 dimensions you can influence:

  1. Output Format & Length — How the response is structured (prose, lists, tables, code, JSON, markdown) and how long or short it should be.
  2. Reasoning Depth — Whether the AI thinks step-by-step, skims the surface, or performs multi-angle analysis before answering.
  3. Tone & Persona — Formal, casual, expert, Socratic, devil’s advocate, or a specific character or role.
  4. Scope & Focus — Broad survey vs. narrow deep-dive; what to include, exclude, or prioritize.
  5. Output Behavior — Whether to ask clarifying questions, make assumptions explicit, iterate, self-critique, or stop at a threshold.
  6. Knowledge & Search Strategy — How to weight sources, whether to reason from first principles, acknowledge uncertainty, or cite reasoning chains.

Scopes Unique or Stronger in Specific AI Tools

🔧 Tool Use / Function Calling

Claude, GPT-4, Gemini — all support this to varying degrees. You can instruct the AI to call defined functions, return structured JSON, or interact with external APIs. Critical for web dev workflows.

🖥️ Code Execution (Sandboxed)

ChatGPT (Code Interpreter / Advanced Data Analysis) is strongest here — it actually runs Python in a sandbox. Claude has artifacts with live React/JS preview. Gemini has limited execution.

🌐 Web Search / Live Data

Gemini is deeply integrated with Google Search. ChatGPT has browsing. Claude has web search too. Useful when you need current docs, library versions, or CVE data.

🎨 Artifacts & Live Preview

Claude-specific — you can generate React, HTML/CSS/JS and see it render inside the conversation. Very powerful for iterative web UI building.

📁 File & Project Context

ChatGPT Projects and Claude Projects let you upload files, maintain memory across sessions, and give the AI persistent context about your codebase.

🔌 MCP (Model Context Protocol)

Claude-specific (for now) — connects Claude directly to external tools like GitHub, databases, Figma, etc. via standardized servers. Game-changer for web dev pipelines.

🧠 Extended Thinking / Deep Reasoning

Claude (extended thinking mode) and ChatGPT o-series models can do slower, deeper reasoning — great for architecture decisions or debugging complex logic.

📐 System Prompts / Custom Instructions

All three support this, but behavior differs. Sets persistent rules, personas, or constraints before your conversation starts.

Comparisons between AI tools

ScopeClaudeChatGPTGemini
Live code preview✅ Strong (Artifacts)⚠️ Limited❌ Weak
Code execution⚠️ Limited✅ Strong⚠️ Limited
Web search✅ Yes✅ Yes✅ Very strong
Function calling✅ Yes✅ Yes✅ Yes
File/project context✅ Projects✅ Projects✅ NotebookLM
MCP integration✅ Native❌ No❌ No
Deep reasoning✅ Extended thinking✅ o3/o4 models⚠️ Limited
Memory across chats⚠️ Projects only✅ Memory feature⚠️ Limited