Prompting isn’t just asking the AI a question. It’s a deliberate, engineered input design process, and a critical skill when working with Large Language Models (LLMs).

 

 

Prompting isn’t just asking the AI a question. It’s a deliberate, engineered input design process, and a critical skill when working with Large Language Models (LLMs).

Let's breakdown the prompting techniques.

1. Core Prompting Techniques

Zero-shot - No examples provided. Just the task.

One-shot - One example shown before the task.

Few-shot - A handful of examples used to teach patterns.

2. Reasoning-Enhancing Techniques

Chain-of-Thought (CoT) - Encourage step-by-step reasoning.

Self-Consistency - Sample multiple CoTs; choose the best.

Tree-of-Thought () - Explore multiple reasoning paths (advanced).

ReAct - Combine reasoning steps with action/tool use (e.g., API calls).

3. Instruction and Role-Based Prompting

Instruction prompting - Clear directives (“Summarize this…”).

System / Role prompting - Define persona or behavior (“You are a legal assistant”).

Hybrid (Instruction + Examples) - Combine clarity with few-shot grounding.

4. Prompt Composition Techniques

Prompt chaining - Use one prompt’s output in the next.

Dynamic prompting - Inject real-time variables or context.

Meta prompting - Ask the model to improve or verify its own response.

5. Multimodal Prompting

Image + text - Provide both visual and textual context.

Audio/Video + text - Use transcripts or sensory input (model-dependent, e.g., GPT-4o, Gemini 1.5).

6. Domain-Specific Prompting

Code prompting - Constrained, tool-specific inputs (e.g., Python, SQL).

Medical / Legal prompting - High-precision language with strict format and accuracy needs.

7. Prompt Evaluation & Debugging

(Not prompting techniques, but crucial tools.)

Prompt ablation - Remove elements to test contribution.

Injection testing - Evaluate prompt robustness in apps or agents.

What’s Not a Prompting Technique

RAG: A retrieval + generation architecture. Prompts are used inside it.

Agents / Tool-use systems - Orchestration frameworks (e.g., LangGraph, AutoGPT). Prompting is one component, not the technique itself.

Prompting is no longer “just prompt engineering.” It’s system design.

If you're working with LLMs, know these cold.

Source: Tech with Mak