When people start using AI tools like ChatGPT, they usually jump right into asking questions.

That's a solid starting point, but if you want consistently useful results, it helps to understand both how you're prompting and what kind of AI you're prompting.

There are two core types of prompts that shape how your AI performs: user prompts and system prompts.

Both are important, but they serve very different purposes. Once you understand the distinction, it changes how you work with AI, especially if you're building agents to support real workflows.

Let's start with user prompts.

 User prompts: Instructing a brilliant alien intern

The best way I've found to explain prompting is this: imagine you're working with a brilliant alien intern. They have a plethora of knowledge, are highly skilled, and can do just about anything. They can summarize articles, write emails, generate code, build lesson plans, and brainstorm ideas. But they don't know your business, your goals, or how humans read between the lines. They take everything literally, misunderstand idioms, and sometimes make strange leaps based on patterns that don't quite apply. Say "make it punchy," and you might get boxing metaphors. Ask for a "killer pitch," and you could get something unintentionally aggressive.

That's how AI behaves without enough guidance.

To help our teams at WWT get better at working with AI, we use the Prompt Blueprint. It encourages people to include the task, relevant context, any constraints, a persona, the desired output format, tone and style, and examples. Even including just a few of these elements gives the AI enough information to be genuinely helpful. It's not about writing fancy prompts; it's about being clear, specific, and thoughtful in how you ask for what you need. 

System prompts: Building the AI agent you want to work with

As you get better at user prompting, you start to notice a gap. It would be even easier if the AI already understood your tone, your audience, your workflows, and your expectations before you ever typed a request. That's where system prompts come in.

Unlike user prompts, which are task-specific, system prompts are foundational. They define the identity of an AI agent before any interaction happens. A system prompt tells the AI what kind of agent it is, what knowledge it draws from, what tools it can use, and how it should behave, as well as setting boundaries, guardrails, and security measures.

You are not just giving instructions; you are designing an AI agent.

You might create:

  • an internal research agent,
  • a customer-facing advisor,
  • or a compliance reviewer.

Once you have defined that agent using a system prompt, you give it tasks using user prompts, just like you would with any team member you've onboarded. 

This structure becomes essential when you start embedding agents into tools, services, or day-to-day processes.

Why this matters

Prompting is not just about getting better answers from ChatGPT. It is the foundation for designing intelligent systems that scale. Clear user prompts help you get better results today. Well-crafted system prompts let you create AI agents that are useful, consistent, and aligned with your goals.

That is how you stop just using AI and start designing it to work the way you do.

If you're building AI agents, helping your team adopt prompting, or exploring how to make AI more useful and reliable at work, I'd love to hear what you're trying. This space is moving fast, and we are all figuring it out together.