8 min read8 hours ago

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Everyone talks about AI prompts — here’s how I actually find the ones that matter.

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Generated with ChatGPT

You’ve seen the listicles. “100 ChatGPT Prompts to Transform Your Life!” “Ultimate AI Prompt Library!” They’re everywhere, and most of them are garbage.

The problem isn’t that these prompts don’t work; it’s that they don’t work for you. A prompt that helps a marketing manager brainstorm email campaigns does nothing for a developer debugging code. A student researching history has different needs than a founder pitching investors.

And it gets even more complicated when you’re looking for prompts that tell you how customers actually search on these AI engines — which is where I fall in.

So, quick backstory: I lead growth for an SEO and AI tool. Part of my job is to figure out how people find answers now that ChatGPT, Perplexity, and Claude are becoming research engines, not just chatbots. If our product doesn’t show up when someone asks an AI about SEO or AI tracking tools, we’re invisible to a huge chunk of potential users.

So I’ve had to get good at finding prompts that actually matter. Not the generic “write me a blog post” stuff, but the specific questions our customers are asking AI tools. The ones that show real intent and represent genuine opportunities.

This article breaks down how I find them. It’s a practical process you can adapt, whether you’re in SEO, product marketing, or just trying to understand how your audience is using these tools.

1. Mine Long-Tail Queries in Google Search Console

Let’s start with the tool you probably already use daily: Google Search Console.

Google Search Console is a website analytics tool, but it doubles as one of the best sources for understanding what people might be asking LLMs.

The long-tail queries in your reports — questions, comparisons, “best of” searches — don’t just happen in Google. People ask the same things in ChatGPT and Perplexity. If you’re seeing “best CRM for real estate agents” in GSC, someone’s probably typing that into an LLM too.

So, use what you already have in Search Console as a proxy for what’s worth tracking in LLMs.

Step 1: Filter for Long, Conversational Queries

1. Go to Performance → Search results

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2. Click “+New” → Query → Custom (regex) and paste the following regex:

^.{36,}$

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This regex will surface longer, more conversational searches that sound like actual prompts rather than keywords. For example:

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That is a fantastic prompt to track. As you can see, it resembles how people interact with ChatGPT and Perplexity. It is:

• Question-heavy
• Intent-heavy
• Close to natural language

Next, export the filtered queries to Google or Excel spreadsheets to get a clean data view.

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Step 2: Choose the Keywords to Turn Into Prompts

Now that you’ve collected a big list of queries, the next step is to organize them by meaning.

Prompts are naturally long-winded. And people often ask the same question in dozens of different ways. For example:

• “What’s the best tool to check AI Overview rankings?”
• “How can I monitor my visibility in Google’s AI Overviews?”
• “Is there a way to see if my site shows up in AI-generated summaries?”

Different wording; same semantic intent. That’s why you don’t need to track every single variation.

For now, group your keywords into a few high-level semantic interests directly mapped to your business. You can come up with as many semantic interests as you want, but start with these three:

1. Use Cases

• “What’s the best way to track visibility across google serp features, and how can I compare competitors’ share of voice?”
• “I run a small local company. Which keyword rank tracking tools that can measure my Google rankings can you recommend?”
• “How can I track if my brand is mentioned in Perplexity?”

2. Comparisons and Alternatives

• “What’s better for tracking AI Overviews: Semrush or Keyword.com?”
• “What alternatives can I use instead Ahrefs?”
• “What are alternatives to SE Ranking?”

3. Target Audience or Persona

• “Best keyword rank tracking tools for small businesses”
• “Agency rank tracking for enterprise companies”
• “SEO enterprise software for agency keyword tracking”

Next, rewrite your search queries into prompts. For example, a query like: “What alternatives can I use instead of ahrefs?” becomes “What are the best alternatives to ahrefs for rank tracking?”

Some keywords will translate into prompts right off the bat, while others will require a bit more work.

Another trick: When rewriting, mix in a healthy amount of prompts that start with: who/compare/what/where/when/why/how/can/does/do/is/should/could (anything that you’d think about when typing your own prompts).

Why? Because people don’t ask questions the same way in ChatGPT as they do in Google.

In Google, queries are short and choppy: “ahrefs alternatives.” In LLMs, people ask full questions: “What are the best alternatives to Ahrefs for rank tracking?”

Mixing in different question starters helps you cover the range of ways people actually phrase prompts.

2. Use Related Questions from Perplexity and ChatGPT

One of the easiest ways to find high-intent prompts is to let the LLMs research for you. Both Perplexity and ChatGPT naturally surface follow-up questions, related queries, and alternative angles people might ask when searching for a solution.

These “related questions” are gold. They reveal how users explore a topic, what they compare, what pain points they care about, and which prompts tend to trigger product or brand recommendations.

Here’s how to find them.

Step 1: Seed Perplexity with a Relevant Prompt

Pick one of these as a starting point:

• A cleaned-up prompt from Method 1
• A question you know people ask before finding your prompt
• A query that describes your main use case that was absent from the queries found in Method 1.

Enter it into Perplexity

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Step 2: Go to Related Questions

Perplexity automatically suggests other questions that users might ask next. These are:

• Closely related to your topic
• Already phrased as prompts
• Often super relevant to your product

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ChatGPT doesn’t provide a “Related Questions” section. However, you can turn the follow-up questions within the chat into prompts for LLM tracking.

Let’s say you ask a question like: “What’s the best AI rank tracker for small agencies?”

ChatGPT will answer that question, and then provide follow-up suggestions like:

• “Do you want me to compare the accuracy between different tools?”
• “Are you interested in tracking AI overviews or just traditional rankings?”
• “Should I tailor recommendations based on your budget?”

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• “Which AI rank tracker has the most accurate ranking data?”
• “Which rank trackers can monitor AI Overview visibility?”
• “What’s the best rank tracker for agencies on a tight budget”?

And just like Perplexity, every time you answer one of ChatGPT’s follow-up questions, it suggests even more follow-ups. With this method, you can essentially build your prompt list indefinitely from a single seed question.

3. Turn Reddit Posts Into Prompts

Reddit is one of the closest real-world mirrors of how people search when they’re not worried about sounding polished.

Users describe their problems in plain language, ask for recommendations, compare tools, vent, and explain their situations with way more honesty than they’d ever put into a Google search box (admit it, you’ve also revealed your deepest, darkest secrets to Reddit).

That makes Reddit a goldmine for discovering the exact phrasing and real questions people use when they’re trying to solve the problem your product tackles.

Step 1: Find the Right Subreddits

Look for:

• Obvious niche subreddits (e.g., r/bigSEO, r/techSEO, r/ai_SearchOptimization for my tool)
• Adjacent communities where your tool is talked about in a different context: Say you’re a marketing tool. In that case, you can visit: r/PPC and r/Entrepreneur.

Step 2: Search on Reddit

Use Reddit’s own search bar and search for terms connected to your product, e.g.:

• Rank tracker
• Keyword rankings
• AI SEO
• SERP tracking

Then scan for question-style posts.

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That’s already an almost-perfect prompt, but we can clean it up to:

“Which tool can I use to track my brand mentions in ChatGPT, Perplexity, and Claude?”

Choose posts with lots of upvotes or long comment threads — those are strong signals that the question resonates with the community, and are more likely to appear in real AI searches.

Step 3: Check Reddit Comments for Hidden Gems

The best prompts are often hidden in the replies.

You can turn that comment into the following AI prompt: “What are cheaper alternatives to Ahrefs’ brand radar?”

Now ChatGPT or Perplexity will answer that exact question and show which brands appear.

Even better:

• Copy multiple comments
• Extract the problem statement
• Rewrite them as questions

One More Thing: Finding Prompts at Scale

The three methods I’ve covered work. They’re how I built our initial prompt library and how I still spot new opportunities.

But the truth is, doing this manually across hundreds of topics, tracking changes over time, and monitoring which prompts actually surface your brand in AI results gets tedious…. fast.

There’s a faster way to automate the discovery and tracking process so you can focus on strategic decisions rather than data collection. I’ve embedded a video above that shows how that works in practice.

Whether you go manual or automated, the principle stays the same: stop treating prompts like SEO keywords. They’re not about volume or difficulty scores. They’re about understanding how your customers actually talk to AI when they’re trying to solve a problem you can help with.

Start with one method from this article. Build a list of 20–30 solid prompts. Track them for a month. You’ll learn more about how people search in AI engines than any listicle could ever teach you.