As an AI consultant, I’m often asked how to get the most out of advanced language models like ChatGPT. While these AI assistants are incredibly capable, the quality of your results relies heavily on the clarity of your prompts. Poorly framed prompts lead to suboptimal responses, while well-structured prompts allow the AI to truly understand your intent and deliver its best work.
That’s where prompting frameworks come in. These structured approaches provide a template for crafting clear, purposeful prompts that set the AI up for success. Today, I’ll highlight one particularly simple yet powerful framework to start optimizing your AI interactions.
The TAG Framework: Task, Action, Goal
The TAG framework breaks down your prompt into three core components:
Task: Define the specific task you need the AI to work on. Be as clear and unambiguous as possible.
Action: Describe the precise action or type of response you want from the AI to address that task.
Goal: Explain the intended outcome, purpose, or use case for the AI’s response.
For example, let’s say you need the AI to draft an email announcement. Your TAG prompt might look like this:
Task: Draft an email to customers
Action: The email should describe our latest software update and key new features
Goal: To inform customers of the update and encourage them to start using the new features
Using the TAG framework is easy, but it can have a profound impact on your AI results. Across my client work, I’ve seen it boost the relevance, quality, and usefulness of AI-generated content by ensuring prompts are clear, structured, and purposeful from the start.
Of course, TAG is just one of many potential prompting frameworks. Others like TRACE (Task, Request, Action, Context, Example) and CARE (Context, Action, Result, Example) offer more comprehensive templates for complex AI interactions. But TAG’s simplicity makes it a great entry point.
Whichever framework you choose, the key is bringing intention and structure to your prompting process. With tools like these, you can unlock the full potential of AI assistants and drive better results for your business use cases.
So give the TAG framework a try next time you need an AI-powered assist. Your future self will thank you for taking a few extra moments upfront to clarify your task, action and goal. The payoff will be AI outputs that are consistently more relevant, tailored and valuable.
