♾️ Functional vs. exquisite

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I was scrolling through Instagram last week and came across this reel, which talks about how today's architecture is more functional, and nobody cares about how buildings look.

The premise was that we’re in such a rush to build more cities and housing complexes that we've forgotten they should be worth looking at, too.

If you walk through French-inspired towns like Pondicherry or an ancient European city, your eyes automatically drift toward the architecture.

People travel thousands of miles just to experience these structures in person.

But today's cities don't reflect that. We've got concrete structures that barely have any meaning, with a few exceptions.

The argument is that we don’t have to choose between functional and beautiful. But that’s how marketers are currently using AI. 

We’re pretending like the problem was our inability to create more content. But the issue was always creating better content for our audience.

And you can't do that without having first-party data in hand. If you want to stand out in the sea of sameness, you have to start from a place that no one else can replicate.

That's why, instead of focusing on generating the words, I'm experimenting with different ways to do more with less.

Here are 3 use cases I’ve found for AI:

1. Creating knowledge bases using GPT and Zapier

I’ve built searchable repositories that index all our interviews, strategy documents, and messaging materials.

I'm not a huge fan of ChatGPT, but unfortunately, it's the only tool that gets me closest to creating a searchable archive of all my content.

For example, I wanted to create a voice of customer (Voc) extractor bot for one of my clients. I had specific categories (Dreams, Objections, Fears, Frustrations) and a few other columns for quotes and jobs to be done that I needed in a spreadsheet.

So, I built the bot and any time I have a transcript from a sales demo or 1:1 ICP interview, I upload it here and get a formatted table that I can paste into a Google Sheet.

Over time, I used the spreadsheet to build briefs, tweak copy/content, and for a few other edge cases.

I’m also experimenting with Zapier’s Chatbots right now. It requires a paid plan, but I'm finding the UI much cleaner, and it doesn't hallucinate as much as GPT.

2. Creating “projects” in Claude to query bots and refine angles

If I'm working with a client to execute their content strategy, I prefer creating dedicated projects in Claude OR having a long-running chat over there.

I can feed Claude portions of our first-party data and ask it to identify potential content angles that align with our objectives and differentiation strategy.

Usually, when I’m building briefs, I have to think about:

• Brand angle

• Our strategy

• Audience needs

• Product info

• SEO (SERP analysis)

• Distribution

• Design

And it’s hard to keep everything stored in your head—especially when you’re working with multiple clients or projects.

Using a running chat with all the docs already in place makes it easier to query and refine the briefs.

I was building a BOFU brief on workflow examples for a client so that we could show what the “after” state would like with our product. I used an existing Claude conversation to pull data from sales calls so that the content is rooted in what our prospects are saying.

This way, I don’t have to remember what every customer or prospect mentioned in old sales calls. But my briefs are still tight enough with brand and audience-specific data.

3. Finding trend lines and patterns in research data

I'm HUGE on running interviews and surveys, and it's where I have the most fun, too. But this also means I usually have 30 to 40 hours of call data and other kinds of first-party data to parse through.

I highly recommend going through it yourself once or twice manually to ensure the AI pulls out the right things. 

But after you’re done with that, feed it to Claude or ChatGPT to pull out trend lines or specific patterns.

I've found this method great for several use cases:

• Creating a messaging document rooted in the market, audience, and brand perspective

• Building a strategic narrative that’s specific to the company’s POV

• Pulling out compelling data points for research reports

• Compiling concrete themes from SME interviews

You'll cut through hours or even days of manual work—while creating content that hits the right note with your audience.

The next time you’re using AI, ask yourself:

If not, work on that first. Then, bring AI into your workflow.

Because AI can create functional content that gets lost in a sea of sameness.

But if you have the right data in place first, you can create exquisite content that builds mindshare.

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That’s all for today! As always, if you have any questions or feedback, feel free to respond to this email.