You’ve seen sales and marketing clash. You’ve lived the messy handoffs. And you’ve probably wondered who should actually own what inside your revenue engine.

In this episode, Sarah and Jay unpack the real friction point between marketing and sales, where one ends, the other begins, and why the line between them is a lot gooier than anyone wants to admit. From cold email debates to personalization rabbit holes to the “who writes what” showdown that sparked this episode, they pull apart the blurry middle where most companies lose speed, clarity, and opportunities.

In this episode, you’ll learn:

• Why the marketing–sales boundary is murky (and why that’s normal)
• How tactics like cold email create ownership confusion
• The role of skill sets, context, and timing in deciding who leads
• Why communication, not org charts, fixes most misalignment
• How unified teams move faster and create a better prospect experience

If you’ve ever felt like your teams are stepping on each other’s toes, this episode will show you how to tighten the handoff, reduce the noise, and build a revenue flow that actually works.

Contact Us:

Email: podcast@stringcaninteractive.com

Website: www.stringcaninteractive.com

Reach out to the hosts on LinkedIn:

Jay Feitlinger: https://www.linkedin.com/in/jayfeitlinger/

Sarah Shepard: https://www.linkedin.com/in/sarahshepardcoo/

Buy the Revenue Rewired book: https://www.amazon.com/Revenue-Rewired-Identify-Leaks-Costing-ebook/dp/B0FST7JCXQ

Let’s reset the narrative for a second. Large language models don’t actually know things. They aren’t pulling from a live database. They don’t check facts in real time. What they do exceptionally well is predict language.

So when you hear someone say, “ChatGPT sounded confident, so it must be right,” that should raise a red flag.

These tools generate answers based on patterns, not certainty. There’s no internal meter saying, “I’m pretty sure this is accurate.” They’re optimized to sound authoritative whether the information is solid or completely off base.

That’s where hallucinations come in. Fabricated quotes. Data assigned to the wrong sources. Details that feel believable but were never true to begin with.

If you’re using AI as a source of truth, you’re setting yourself up for trouble.

The better move is to treat it like a thinking partner. Use it to spark ideas, outline a draft, or pressure test your thinking. Then do the real work: verify, validate, and apply judgment. AI should help you get started, not sign off on the final answer.

Bottom line: confidence is not accuracy. Use AI with intention, and always verify what matters.

Contact Us:

Email: podcast@stringcaninteractive.com

Website: www.stringcaninteractive.com

Reach out to the hosts on LinkedIn:

Jay Feitlinger: https://www.linkedin.com/in/jayfeitlinger/

Sarah Shepard: https://www.linkedin.com/in/sarahshepardcoo/

Buy the Revenue Rewired book: https://www.amazon.com/Revenue-Rewired-Identify-Leaks-Costing-ebook/dp/B0FST7JCXQ

Use AI not just to align with your thinking, but to challenge it. Prompting AI to write from a critical perspective, like a competitor or a tough stakeholder, can reveal unexpected insights and blind spots.

This practice forces you to anticipate objections and shows where your messaging, assumptions, or pitch might be weak.

Key takeaway: Make AI your sparring partner. Purposefully prompting it to disagree is the fastest way to strengthen your ideas and find your next breakthrough.

Contact Us:

Email: podcast@stringcaninteractive.com

Website: www.stringcaninteractive.com

Reach out to the hosts on LinkedIn:

Jay Feitlinger: https://www.linkedin.com/in/jayfeitlinger/

Sarah Shepard: https://www.linkedin.com/in/sarahshepardcoo/

Buy the Revenue Rewired book: https://www.amazon.com/Revenue-Rewired-Identify-Leaks-Costing-ebook/dp/B0FST7JCXQ