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Struggling with your AI Output? The “Always Ask” Method Can Help

Engagement with ChatGPT has plummeted almost as quickly as it exploded. The bot that once awed us with detailed essays on command now ghostwrites our middle schoolers’ homework…poorly. What happened to the AI we were promised? The one that could spawn a million startups and automate away drudgery?

But what if it’s all still there and we just have to learn how to converse with AI properly? We can try just impatiently barking orders at it but my experience is that the real power comes from a more collaborative approach.

Building effective skills like crafting clear prompts, iterating based on the AI’s output, and guiding the conversation all take practice. But with some practice you can learn to get the most out of the time you’re putting in.

For my own journey into developing better prompting skills, asking targeted questions is one of the most useful skills to develop. And over time, I’ve come up with what I consider to be my bedrock rule: Always ask the AI.

No matter what I’m working on or trying to achieve, my first step is to think about whether there’s a strategic question I can ask the AI that will help expand the scope of the problem on one end, while focusing on the quality of the output on the other.

Let me give you a specific example – In this case, creating an overview document for a concept pitch. Let’s go really meta and say that I’m developing a concept for “An app that lets you use AI to create pitches for AI driven apps.”

I’ll want to add some detail to that so the chatbot has something to chew on.

Here’s my basic pitch:

This app will be on iOS and Android. It allows the user to input short app ideas and will expand those out into a simple pitch. The user can use some menus to detail tone and define an audience demographic.

I’ll also tell the AI that I want it to give me a short concept doc.
And at this point, I’ll ask the AI to ask me questions before it actually generates the content.

That’s usually phrased something like:

Before starting go ahead and ask me any questions that would help make the document more clear or effective.

Now here’s a full prompt that I can input into Claude 2:

I’m developing a concept for “An app that lets you use AI to create pitches for AI driven apps. The app will be on iOS and Android. It allows the user to input short app ideas and will expand those out into a simple pitch. The user can use some menus to detail tone and define an audience demographic. I want to generate a short concept doc (maximum of 3 pages). Before starting go ahead and ask me any questions that would help you to make the document more clear or effective.

And here’s the response I got putting that into Claude 2:

Thank you for sharing the idea for your app. Before generating a concept document, I have a few clarifying questions:
1. What problem is this app trying to solve? Understanding the core user need will help craft a compelling value proposition.
2. Who is the target audience for this app? Defining the demographics and psychographics will inform the tone and messaging.
3. What are some key features or functionality the app should provide? Details on the user experience will help describe the product benefits.
4. How does this app differ from or improve upon alternatives in the market? Highlighting competitive advantages makes the pitch more persuasive.
5. What business model are you envisioning for monetization? Revenue models like subscriptions or advertising should align with the product and user base.
6. What is your vision for scale or growth over time? Pitching the long-term potential makes the opportunity more exciting.
Please feel free to provide any additional context or details about your goals for the app and pitch. The more I understand, the better I can tailor the concept document to your needs. I’m looking forward to working together to bring your idea to life!

Clearly the next step would be to pull out that list, answer those questions, and then feed those answers back into the AI.

Here’s an example of me asking for that:

Please give me some suggestions for #5. We’re thinking that it would be a subscription model but maybe it could be possible to pay a la carte on a per item basis. Does that sound good or do you have any other suggestions?

And here’s the answer it gave:

Here are some suggestions for potential business models for your AI app pitch concept:

– Monthly or yearly subscription to access all app features
– Different tiers based on number of pitches generated per month/year
– Entry level plan for individuals, higher tiers for agencies/teams
Pay Per Item:
– Users pay a fee each time they generate a new pitch
– Could offer bulk discounts for purchasing multiple pitch credits upfront
– Allows very low cost to try out the app before committing
– May be better for one-time use vs frequent users
– Core app is free, advanced features require upgrade
– Limits on number of pitches before needing to upgrade
– Can upsell additional pitch credits as in-app purchases
– Free for users, monetize through ads
– Keep ads relevant to target audience of startups/developers
I think any of these models could work well. The subscription plan provides predictable recurring revenue but may have a higher barrier to entry. Pay per item or freemium keeps initial cost low and could drive adoption, but need volume to make profit. Would be happy to expand on any of these options! Let me know your thoughts.

From there I can pick one of the business models and ask it to dig in even further, exposing even more possibilities.

Whatever model I finally choose, rather than just going with my usual response the AI itself has given me some insights into a model that I’ve either forgotten or simply never considered before and helped me to make solid choices before I’ve written a single word of the actual doc!

And however deep I ultimately go, the key was having it help me answer questions whenever I’m stuck for ideas or need to expand my options in a particular area.

Rather than simply trying to get the AI to craft a specific idea to help me generate a spectrum of ideas that I can then focus back down into a cohesive whole that it will generate.

And how did I get better at doing that? By asking the AI to help me do it.

Once you start asking the right questions, you’ll begin to see how this technique can be useful at every step of the process. Whether it’s Claude, ChatGPT or even Bard, it’s only by using these tools effectively as my first stop that I’ve begun to fully grasp their capabilities and understand what they have to offer me creatively.

The specific example above illustrates the concept, but the power truly comes when applying this approach more broadly. Asking an AI to help expand outlines, suggest structural changes in a draft, or brainstorm fresh titles unlocks creativity and reveals possibilities I may not have originally considered.

Guiding the AI to show me new directions and then integrating the best parts into my own work allows me to leverage its immense knowledge. I’ve stopped trying to get a finished product from the AI, but instead use it to strengthen my creative process.

And it goes beyond just solving problems. Where AI’s capabilities truly become extraordinary is in helping me to define the scope of the problem that I’m trying to solve. It can do this in a few key ways:

  1. Nailing down a more well-defined description of the problem. For example, asking it to rephrase, rewrite, or expand on a particular definition can crystallize my thinking.
  2. Broadening the problem space with ideas or concepts I hadn’t originally considered. I can prompt it for more detailed scenarios or ask for “5 alternatives” to open up possibilities.
  3. Concepting out other potential solutions that subject matter experts commonly use but I may not have thought of. Asking it to suggest approaches as if it were a subject matter expert may expose new options.

At every turn exploring the current state of the art guides me to new insights. The AI excels at illuminating the problem, not just resolving it. With some well placed questions, I can better grasp the true scope and dimensions of what I want to achieve.
But at every turn it is the exploration of the current state of the art that will give you what you’re looking for.

Generative AI may not be “thinking” in a traditional sense but as a Mimetic Chameleon it is processing answers based on essentially the sum total of human knowledge and experience that has been encapsulated on the internet.

The chatbot will never get bored, sleepy, or angry. You can keep asking as many questions as you’d like at every step along the way until you arrive at something you can use directly or reach a point where you can (and should) use the new information and customize it yourself.

Today’s AIs don’t think creatively on their own. Defining problems clearly, expanding possibilities broadly, and iterating rapidly is where AI excels. And with practice, anyone can improve their prompting proficiency. It all starts with an open mind to new approaches and a willingness to constantly inquire and explore.

I’ll say it one more time for those in the back, “Always ask the AI.”” When you learn how to direct the model to surface fresh connections and perspectives that would otherwise remain concealed in the darkest depths of their language models you’ll get the building blocks you need to not only finish your work but excel at it.



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