Beyond Q&A: Using AI as Your Thinking Partner

Hello go-to-market leaders, strategists, and innovators! 👋 Thank you for dropping by to learn practical AI applications and gain strategic insights to help you grow your business and elevate your team's strategic value.

Quick Take

Most teams limit AI to Q&A and content creation. Working with GTM (go-to-market) teams as an AI and executive advisor, I've found something more powerful: AI makes your thinking better when you lead with your ideas.

Let me show you how I recently worked with Claude and ChatGPT to uncover fresh insights about trust, attribution, and brand perception in the AI era.

I find it ironic that we say AI should augment human intelligence. Yet we ask AI to think for us. The best AI-enhanced work starts with your perspective, your insights, your frameworks. In a world where everyone has access to the same AI tools, original thinking sets you apart.

Here are some prompts that turn AI into a true thinking partner. Let me show you how it works.

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Why Use Multiple AIs as Thinking Partners?

Think of it like the Justice League. Each member brings different superpowers to solve problems together.

Claude approaches challenges step by step, while ChatGPT jumps to creative solutions. As a human, I guide with business experience and keep us focused on practical value.

Together, we catch blind spots and build stronger ideas.

I recently asked Jonathan M Kvarfordt, MBA, Head of GTM Growth at Momentum, how he approaches AI collaboration. His perspective reinforces why AI thought partnership matters:

"Most people use AI like a faster search engine or content creator. That misses its real value. I use AI to push my thinking, challenge assumptions, and refine ideas before execution.

When structuring an AI-powered sales coaching framework, I didn't just ask for "best practices." I had AI break down great coaching approaches, critique my structure, and pressure-test my thinking. It flagged gaps in feedback loops, helped define better scoring criteria, and refined how we track skill improvement.

The framework became sharper and immediately actionable. AI didn't give me a single answer. It strengthened my thinking until I got to the right one.

The moat of the future isn't just using AI. It's when YOUR human mind is amplified with AI's capabilities."

A Real Example: Rethinking Marketing in the AI Era

It started with a LinkedIn post I read that about 70% of pipeline coming from four channels: SEO, paid search, social, and events. Given that, it seemed completely logical to focus our efforts on these four. Less is more!

However, this got me thinking bigger about how AI will change everything. I challenged this "less is more" view.

In the AI era, we'll need to be in relevant and reputable places where our audiences talk about us: in communities, social media, publications, review sites, and more. Trust signals will come from all these places. AI will gather these signals before humans even start searching.

This raised bigger questions about measurement. How will we track success when AI forms opinions about brands before humans do? We'll need to measure how easily people find us, where trust signals come from, and how strong those signals are.

My Collaboration With Two AIs

Round 1: Claude Builds on My Perspectives

I shared my thoughts about AI changing how buyers find and trust brands. Claude understood the vision:

"Your observation about AI forming opinions before humans do is particularly insightful... We may need strategies that work for both AI agents and human decision-makers."

Together, we evolved from "less is more" to "authentic is more" in marketing. In the AI era:

• AI will find what people say about you everywhere online

• Happy customers matter more than clever marketing

• Real employee stories beat planned content

• You can't fake real community connections

• Face-to-face meetings become more important

Here's our exchange.

Then Claude proposed something new: a trust signal portfolio to measure brand health. This sparked a deeper discussion about attribution.

I shared that traditional channel tracking won't work anymore. We need to measure:

• How well buyers can find us

• Where trust signals come from

• How strong these signals are

• Overall brand perception

• Impact on pipeline

I asked Claude to assess my point of view using the Rose/Thorn/Bud framework. This helped us identify strong points, potential challenges, and opportunities to make it better.

See this part of our conversation:

Claude agreed that good business practices will matter more than ever. AI will reward companies that create real value rather than those trying to game the system.

This shift in thinking isn't just theoretical. Wendy Werve, CMO of financial services compliance platform COMPLY, shares how they're adapting:

"In financial services, reputation makes or breaks companies and ensuring regulatory compliance is key to building and maintaining that reputation.  With the constantly evolving regulatory landscape, we're exploring how AI can accelerate and optimize compliance processes for financial services firms, freeing compliance officers and teams to focus on other priorities, and ultimately strengthening market confidence. 

We're also looking at how we can use AI internally to help us better understand and serve our customers and the market - from identifying key regulatory trends and building resonant content and positioning, to surfacing customer success stories and data, compiling marketing intelligence, evaluating our marketing campaigns and strategies, and monitoring social sentiment. The goal is to spot trends early and focus our efforts where they matter most.

Success in the AI era comes from consistent performance across every interaction."

Round 2: ChatGPT Adds New Angles

I shared my Claude conversation with ChatGPT. Its response showed the power of getting multiple AI perspectives.

First, ChatGPT noted what worked well, pointing out our focus on trust signals from many sources and the need to rethink attribution. Then it challenged our "just be a good business" approach:

"You and Claude nailed the big shift—AI changes the way brands are perceived, trust signals matter more than ever, and marketing attribution as we know it is due for a major overhaul. However, I'd challenge and expand a few ideas..."

ChatGPT took our attribution discussion further. While agreeing with the concept, it pointed out practical challenges in implementation. It suggested starting with an AI Trust Score that measures:

• What customers say on review sites

• What employees share on job sites like Glassdoor

• When experts mention or cite you

• Real community discussions vs promotional posts

The conversation sparked more ideas. ChatGPT proposed AI-specific PR strategies and brand perception dashboards. As ideas kept flowing, I started calling us "the three chickens." Sometimes keeping things light helps unlock better thinking.

Using the Rose/Thorn/Bud framework helped us spot strong points, tackle hard problems, and find new opportunities. This structured approach, mixed with casual collaboration, led to insights none of us would have found alone.

Here's ChatGPT's take:

Round 3: Finding the Truth Together

After ChatGPT's analysis, I came back to a simple truth: Focus on being a good business. Give great service to customers who fit best. Be helpful where your audience is. Build a business people love to work for.

Claude helped reinforce why being authentic matters more in the AI era:

"AI might actually push us back toward business basics. Because AI can better detect patterns, it may be better at distinguishing genuine value from artificial attempts to game the system."

This collaboration showed how human insight and AI perspectives build stronger thinking together. By the end of our long discussion, I joked about being a "fried chicken" from all the thinking. Claude jumped right in, dubbing us "the chicken trio."

What We Learned

Here are a few big takeaways from this insightful conversation about the impact of AI on marketing:

► Trust looks different now - We need to build it everywhere our audiences gather, not just in traditional channels. And AI will form opinions about our brands before humans do.

► Attribution needs a complete rethink - Simple channel tracking won't work when AI and humans take signals from many places. We need new ways to measure findability, trust signals, and real business impact.

► AI will reward good business fundamentals - No shortcuts. No gaming the system. Focus on serving customers well and building a company people love to work for.

What's Next

For those new to AI collaboration, Jonathan M Kvarfordt, MBA has created an excellent framework that takes the guesswork out of AI thought partnership.

His step-by-step prompts is particularly helpful if you're just starting out, as it prompts you with the right questions and helps structure your thinking process.

Try using multiple AIs as thinking partners on your next big challenge. Start with your perspective. Share it with one AI, then another. Let them build on each other's ideas. Keep it real, keep it practical. Here are links to step-by-step guides with examples for your reference:

1. 10 Steps in 10 Minutes: Practical Tips for Strategic AI Collaboration with ChatGPT

2. 5 Steps in 5 Minutes: Practical Tips for Strategic AI Collaboration

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