Product marketers, you know this pain. You need insights yesterday, but the data is scattered across calls, surveys, dashboards, and internal docs. In this episode, Emily Pick shares how she used AI agents to run a multi-layered messaging gap analysis in just two hours, turning what normally takes weeks into a repeatable process. The big lesson is not magic prompts. It is getting clear on inputs first, then using automation to pull the right data, and finally using AI to pressure-test narratives and messaging angles fast.

We also cover why feedback loops matter if you want the insights to stick. Emily shares how she validates findings with product, demand gen, and stakeholders so the work gets sharper and earns trust. Then we finish with a messaging critique of Granola.ai, an AI note-taking tool with a refreshingly clear promise for people in back-to-back meetings, plus a smart “Crunched” campaign. The opportunity is emotional differentiation. In a crowded market, the story is not just better notes. It is being present in the meeting.

Key Takeaways

• Start with inputs, not tools. Define the data that actually matters before you touch AI
• Automate collection so you can spend time on narrative, not admin
• Use AI to explore and test messaging angles quickly, not to replace strategy
• Build feedback loops to validate insights and increase stakeholder buy-in
• Messaging wins when it is consistent, specific, and emotionally resonant

LINKS

Messaging Critique:

Granola.ai

https://www.granola.ai/

Connect with Emily: 

LinkedIn: https://www.linkedin.com/in/emilypick/

Connect with Elle:

LinkedIn: https://www.linkedin.com/in/elle3izabeth/