Prompting AI: A Practical Guide

Getting Started: Prompts vs. Agent Instructions

Before we dive into best practices, let’s clarify two key terms you'll encounter when working with AI tools: prompts and agent instructions. They’re closely related, but they serve different purposes.

What is a Prompt?

A prompt is a message you type into an AI tool to get a response. It can be a question, command, or instruction—written in natural language—that tells the AI what you want it to do right now. Prompts are used in chat interfaces, document editors, ticketing systems, and other AI-enabled environments.

Example prompt: “Summarize the key action items from this meeting in 3 bullet points.”

Prompts are real-time, one-off inputs—you give the AI a task, it gives you an answer.

What are Agent Instructions?

Agent instructions (sometimes called system prompts or configurations) define how an AI-powered agent should behave every time it’s used. These are often written once and saved as part of the agent’s setup—especially in tools that let you build or customize AI assistants, bots, or workflows.

Example agent instruction: “You are a customer support agent. Your job is to respond politely, use plain language, and escalate issues marked as critical.”

Agent instructions set long-term behavior, tone, and task scope. They help ensure the AI consistently acts like a specific role (e.g., an HR assistant, technical writer, or analyst).

Key Differences

Feature	Prompt	Agent Instructions
When it’s used	In the moment	During setup
How often it changes	Every time you use the AI	Typically set once per agent
Who uses it	Anyone interacting with the AI	Usually admins or creators
Purpose	Directs the AI’s current action	Defines the AI’s overall role and rules

Why It Matters

• If you’re chatting with an AI or generating content, mastering prompting helps you get better results, faster.

• If you're building AI tools for others (like agents or bots), writing strong agent instructions ensures they behave consistently and professionally.

This guide will focus primarily on prompts, with a few notes on how to apply these principles when writing agent instructions.

Task, Context, Example, Persona, Format, and Tone

Generative AI thrives on clear, structured prompts. Whether you're using AI to automate tasks, summarize content, generate documentation, or search across platforms, the quality of the results depends on how you communicate with it.

This article provides actionable best practices to help you prompt AI tools more effectively. Whether you're drafting requirements, automating support tasks, or generating strategic insights, strong prompts help ensure reliable and useful outcomes.

We'll cover:

• General prompting principles for AI tools

• Prompting tips for common use cases like content generation, search, and automation

• Prompting based on user role (developers, product managers, support agents, etc.)

• Common mistakes and how to avoid them

• Example prompt templates you can adapt for your teams

By the end, you'll have ready-to-use guidelines to help your teams move from casual AI users to confident collaborators.

General Prompting Principles

These universal best practices apply across most AI systems:

• Be specific, not vague

  • Instead of: “Summarize this page”

  • Use: “Summarize key decisions and action items from this meeting”

• Provide context

  • Tell the AI your goal, audience, or use case.

  • Example: “Draft a customer-friendly release note for this feature update.”

• Use natural language

  • Most modern AI platforms support plain English and other languages—no need for special syntax or code.

• Assign a role or persona

  • Example: “Act as a senior engineer: review this spec for technical clarity.”

• Set output limits

  • Example: “Keep response under 300 words” or “Summarize in 3 bullet points.”

• Clarify tone and format

  • Example: “Write this in a professional but friendly tone” or “Format as a checklist.”

• Iterate interactively

  • Refine prompts like: “Make this more concise” or “Add a call to action.”

Prompting by Common Use Case

Content Summarization

• “Summarize this discussion thread with key outcomes and follow-up actions.”

• “Provide a weekly executive summary from this project page.”

Editing and Rewriting

• “Rewrite this section for non-technical readers.”

• “Suggest three alternative headlines for this blog post.”

Content Generation

• “Draft an FAQ section based on these bullet points.”

• “Create a structured project brief using the following key facts.”

Search and Insight Extraction

• “Find all documents related to the client onboarding process.”

• “What were the most reported issues related to payment failures in Q1?”

Automation

• “Create a rule: when a high-priority support ticket is opened, assign it to the on-call team and notify via Slack.”

• “Generate a checklist when a new employee is onboarded.”

Prompting by Role

Role	Prompting Tips
Developers	Ask for code explanations, bug summaries, and documentation drafts. “Summarize this technical spec for the sprint review.”
Product Managers	Request PRDs, customer updates, or decision documents. “Draft an update for internal stakeholders summarizing launch progress.”
Support Agents	Use summarization and Q&A prompts. “Summarize this ticket thread for handoff.”
IT Admins	Use governance and automation prompts. “List systems without assigned owners” or “Draft access control policy.”
HR/Operations	Ask for help with policy drafts, survey summaries, or internal communications. “Summarize engagement survey findings with next steps.”

Common Mistakes to Avoid

• Being too vague

  • Always include a goal or context.

  • Instead of: “Summarize this”

  • Use: “Summarize this for our leadership team’s weekly update.”

• Ignoring data access limitations

  • AI can only summarize or analyze what it has access to. If something is restricted, the AI won’t "see" it.

• Overloading a single prompt

  • Break large requests into smaller, manageable steps.

• Assuming factual accuracy

  • Always verify AI outputs—use them as drafts, not final answers.

• Skipping refinement

  • Great results often take a few iterations.

Prompt Templates

Here are easy-to-adapt prompt formulas for everyday use:

• For drafting: “Draft a [document type] for [purpose], targeting [audience], using the following key points: [list].”

• For summarizing: “Summarize this [ticket/project/page] in [format: bullet points, paragraph, executive summary], focusing on [decisions, blockers, action items].”

• For insights: “Analyze trends in [project/data set] and highlight [risks, top issues, or opportunities].”

• For automation: “Create a rule that triggers when [event], and then [desired action].”

• For rewriting: “Rewrite this content to be [clearer, more concise, more persuasive] while keeping the key points intact.”

Final Recommendations

• Create a shared space (e.g., internal wiki) with top-performing prompts.

• Provide quick training on iterative prompting techniques.

• Tailor prompt libraries by role or department.

• Stay informed about new features or capabilities in your AI platforms.

• Always review AI-generated content for tone, clarity, and factual accuracy before using externally.

Try It Yourself: Prompt vs. Agent Instructions

1. Write a Prompt

   Choose a recent task you completed (e.g., writing an email, summarizing a meeting, answering a support ticket). Now write a prompt that would help an AI tool complete that task.

   
   

   Example: “Summarize this meeting note with action items for the project team.”

   
   

2. Write Agent Instructions

   Now imagine you're setting up an AI assistant to help with similar tasks in the future. Write a short set of agent instructions that define its behavior.

   
   

   Example: “You are a project assistant. Summarize meeting notes in 3 bullet points, highlighting action items. Keep the tone professional.”

   
   

3. Compare

   What’s different between your prompt and your agent instructions? Which situations are they best suited for?