You've sat through the webinars. You've read the threads. You're still not sure AI is actually working for you. That's not a knowledge problem. It's a starting point problem.
Jay and Sarah skip the productivity playbook and go personal. They share the real ways they started using AI for themselves first, from decoding MRI reports to building a compound interest app at the dinner table, and why that's the move that actually builds confidence to use it in business. No framework. No course. Just honest reflection from two operators who've been in the AI weeds for three-plus years.
If you're burned out on AI hype but still haven't found your version of it, this episode's for you.
KEY TAKEAWAYS
• Why starting personal beats starting professional? The fastest path to using AI in your business is using it for something you actually care about first. That low-stakes repetition is what makes the business application feel obvious later.
• What "building on sand" actually costs you. Don't design your workflows around a single tool's features. Platforms shift overnight. The goal is AI fluency, not AI dependency.
• How your personality should drive which LLM you use. ChatGPT, Claude, and Perplexity aren't interchangeable. Try them before you commit. Your cognitive style matters more than the feature list.
• Why the privacy risk is smaller than you think. Sarah's filter: if you wouldn't mind anyone seeing this information, you don't need to be nervous about putting it into an LLM. That reframe removes paralysis without removing caution.
• What happens when your team experiments out loud? AI literacy spread at StringCan because leaders shared what they were trying, not just what worked. That culture of experimentation is what drives client conversations now.
EPISODE CHAPTERS
00:00 Welcome and Sarah's Paris trip
02:17 Why we're done talking about AI productivity
04:16 Jay's origin story: from intimidated to obsessed
07:23 Sarah's start: from fantasy football to health reports
10:14 The danger of betting everything on one tool
13:27 How to think about privacy risk
16:25 Match the LLM to your personality
19:33 Using multiple LLMs against each other
25:32 Jay's three personal AI wins
ABOUT THE HOSTS
Jay Feitlinger is the CEO of StringCan Interactive and co-host of Revenue Rewired.
Connect with Jay on LinkedIn: https://www.linkedin.com/in/jayfeitlinger/
Sarah Shepard is the COO of StringCan Interactive and co-host of Revenue Rewired.
Connect with Sarah on LinkedIn: https://www.linkedin.com/in/sarahshepardcoo/
ABOUT REVENUE REWIRED
Revenue Rewired is a podcast for B2B marketers, sales leaders, and business owners navigating the intersection of sales and marketing. Every episode delivers actionable insights for mid-market companies that are serious about growing revenue strategically.
Email: [email protected] Website: www.stringcaninteractive.com
Get the Revenue Rewired book: https://www.amazon.com/Revenue-Rewired-Identify-Leaks-Costing-ebook/dp/B0FST7JCXQ
Newsletter: https://www.linkedin.com/newsletters/revenue-rewired-7423414515779936256/
KEYWORDS:2026 AI in B2B sales, B2B leadership podcast, business growth podcast, CEO leadership podcast, B2B go-to-market 2026, revenue efficiency, B2B business podcast, custom GPT strategy, AI tools for business owners, ChatGPT vs Claude, personal AI use cases, LLM comparison 2026