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Use a PMM AI agent like a Docebo PMM

Product Marketing Adventures · 2026-02-03 · 57 min

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Topics in this episode

PositioningMessagingproduct marketing

Episode notes

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.

Related episodes across the Index

Other episodes covering the same guests and topics, from across The B2B Podcast Index.

  • 25 Years of (Product-Led) Growth: Actionable B2B Lessons From Leah TharinEveryone Hates Marketers · on Positioning96 / 100
  • Event ROI for Early-Stage Startups: Lessons Learned the Hard WayA Go-To-Market Perspective · on product marketing88 / 100
  • Clear Expectations and Skill Capacity: A Sales Leader's Balancing Act with Chris OrlobPillar Talk · on product marketing88 / 100
  • B2B SaaS Marketing: No progress after Series A without product marketing (episode #148)How I Made it in Marketing · on product marketing88 / 100
  • Why Some SaaS CMOs Flourish in PE-Backed Orgs, and Others Flame OutThe Get · on product marketing86 / 100
  • EPISODE 11: Michele Nieberding Shares Her Top Use Cases and Future Predictions for AI in Product MarketingThe Last Word on Product Marketing · on product marketing84 / 100

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