In my last piece, I explored the key elements of context, scope, and goals for guiding AI chatbots productively. In this second part we’ll zooming in on scope – why understanding how to define the limitations of your inputs is so critical for generating quality output.
Because there is so much focus on the quality of output that is being generated, scope gets far less attention than crafting the perfect context or stating your goals. That’s because of all three tools – context, scope, and goals – scope is the one that lands primarily in the lap of the user. Let’s review what each of these terms means in this context:
- Context: This is the overall setting or background for the interaction. What is the conversation about? What are the underlying assumptions or premises?
- Scope: This refers to the boundaries or limits of the conversation. What is included, and what is excluded? It can be thought of as the ‘walls’ that guide the conversation in a particular direction.
- Goals: These are the specific objectives or outcomes that you are aiming to achieve in the conversation. What do you want the AI to do or produce?
Because an AI chatbot like ChatGPT has inhaled so much information and has been designed to consider the connections between all those elements, limiting scope may be the most difficult of the three elements to define clearly.
It also tends to overlap a bit with goals, but the difference is one of action vs. output. I limit scope to better satisfy goals. That makes scoping more about the input and goals more about the output. Understanding this distinction is crucial:
- Scope is about input: It defines what information is relevant or irrelevant to the task at hand. It’s like setting the rules for what can and cannot be considered.
- Goals are about output: They guide what you want the final result to be, whether it’s an answer to a question, a piece of writing in a specific style, or something else.
By layering them together properly, I can more quickly and effectively complete my work using AI tools.
Your own relationship to scope may be modified by what you’re looking to get the AI to generate for you. The more you want to use AI for outputting specific materials designed to satisfy particular criteria, the more you’ll want to use definition of scope to make sure the results fall into the particular parameters that mean the results satisfy your specific needs. In this way, you’re using scope to try and more effectively reach your goals.
On the other hand, when you’re creatively brainstorming, you’ll appreciate what the AI can create for you when the scope is wide open. In that way, it can spark your imagination and deliver results that are unique and inspiring.
To see just how defining scope can help your work, let’s look at the differences between ChatGPT (a text tool) and Midjourney (an Image generation tool).
In a visual tool like Midjourney, scope is not only clear, but it’s possible to come at it from multiple directions with far more direct impact in terms of output. What is the visual style you want your image to be in? Should it represent a particular time period? An aspect ratio? A particular time of day? A particular lighting style? With properly defined scope in your initial prompt, you are bringing in the walls around your subject and hopefully getting something that is bringing more clarity to your ideas.
You can also feed it an initial image with the hope that it will use elements of that to define it even further. Say I want an image of my cat in a top hat, for example. I can start by giving it a link to an image of my actual cat. That’s limiting the scope of its output to cats that look like the one in the photo. And yes, I’ve actually done this…
Once the initial input has been made, Midjourney will give you 4 outputs. You can not only choose one of these images but feed it back into the LLM so that it can make modifications to try and satisfy your needs even more clearly. This is a subtle point, but it’s worth noting that the act of choosing a single image is a clear reduction in scope even as the reasons you may be picking a particular image are to satisfy your goals.
Certainly! Below, I’ve extended the “ChatGPT” section of the text to provide further explanation. I’ve included an example that illustrates how one might define the scope in interacting with ChatGPT, and how that plays a role in achieving specific goals.
When facing the blank prompt, your initial instinct will be to focus in on context and goals. What do I want and what is it for? But defining the scope plays a vital role in shaping the response to align with your goals. We’ll cover that more in detail in the coming weeks, but it’s important to understand that scope in this context is primarily about dynamically editing your piece. “Use my voice,” for example, is a scoping request.
Let’s look at a specific example. Imagine you’re writing a blog post about environmental conservation, and you need a concise explanation of the greenhouse effect for a general audience. Your goal is clear: a simple and engaging explanation. Here’s how you might define the scope:
- Context: “I’m writing a blog post for a general audience about environmental conservation.”
- Goal: “I need a concise explanation of the greenhouse effect that’s easy to understand.”
- Scope: “Please avoid using scientific jargon or complex terms, and keep the explanation to around 100 words.”
Interestingly, many of the current scoping tools provided by ChatGPT are built into the interface rather than happening through the prompt. Allowing you to both save and return to individual sessions is primarily a way to define both scope and context in a way that you don’t have to repeat your requests over and over again.
When you’re considering using scope for smithing words, imagine it’s a chisel that lets you carve away some of the material and better define the limitations of the chatbot’s output. In this case, your goals are how much water you want to drink, and scope is the shape of the glass that you want the AI to use.
In practical terms, it may be telling the chatbot the number of characters/words you want it to output or the complexity of language you want it to use. In the example above, the scope was defined both by the simplicity of language and the word count.
You can say, “Make sure to use words that are simple and direct,” or go the other way and ask for “occasional florid swirls of language.”
Like everything in ChatGPT, scoping is iterative. After each output, you can identify areas that need refinement and scope the next request accordingly. By carefully defining and redefining the scope in line with your goals, you can direct the conversation to a result that truly meets your needs.
Each back-and-forth should shape the focus for the next exchange. Scope begets scope. Stay nimble and be prepared to zoom in or out as needed.
Working with Goals
As you define (and redefine) scope, it ultimately connects to your core goals. Knowing what you want to accomplish at any given moment lets you tailor scope accordingly.
When ideating, keep prompts short and output broad. If revising, keep limiting scope through defining style and structure. When finalizing, use focused scope for improvements.
Scope takes practice
Like any skill, effectively scoping conversations improves over time. At first, you can err towards over-scoping – tighten prompts and outputs gradually as you observe results.
Pay attention to when AI loses focus or regurgitates text. Dial it in until you hit the sweet spot of concise, productive results.
With proper scoping, you’ll be amazed at what creative sparks emerge. Creativity thrives with clearly bounded spaces to explore. Use scope purposefully and artfully to unlock your AI’s hidden potential.