Jay Nathan and Jeff Breunsbach break down what 50+ CS leaders are actually doing with AI — and what most teams are still getting wrong.

Jeff shares fresh takeaways from a Planhat-organized event in Boston, and Jay goes deep on the Claude skills his team has built to scale coaching, standardize deliverables, and rethink how prep calls even work. No hype, just real strategies in the field.

KEY TAKEAWAYS

• We're still in early adopter territory: Jeff attended an event with 60 CS leaders and walked away realizing that even among leaders who talk about AI daily, widespread team adoption is far behind what the tech echo chamber suggests. The majority of companies are still evaluating — not executing.
• You don't know your processes as well as you think: Before you can automate or augment a workflow with AI, you have to actually know what that workflow is. Jay and Jeff agree: most teams haven't documented or visualized their core processes, which is the real bottleneck to AI leverage.
• Top-down mandates don't drive AI adoption: "Just use AI" from the CEO doesn't work. Real adoption requires demonstrating behaviors at every layer of the org, giving teams specific problems to focus on, and creating regular show-and-tell moments where people can see and iterate on each other's work.
• Call transcripts are your most underutilized asset: Jay calls Fathom call recordings "the most valuable thing we have in our company."
• Claude skills as a team force multiplier: Jay built an executive readout coaching skill in Claude that replicates his own feedback patterns, so every team member starts their deck review at a higher baseline.
• The future CSM is a technical account manager: Multiple CS leaders at Jeff's event flagged this shift — the CSM role is evolving toward one that requires real technical curiosity.
• Forward deployed engineering is closer than you think: Jay makes the case that giving CSMs a local build of your product — and the ability to generate a feature-based pull request from a customer conversation — is entirely possible today.
• Build a center of excellence, not just a mandate: Sustainable AI adoption at the team level needs a few dedicated people vetting standard tools, scheduling engagement touchpoints, and measuring outcomes — not just an org-wide Slack message to "go use AI."

CHAPTERS

• 00:00 - Intro & Jay's flight back from Seattle
• 01:29 - Jeff's takeaways from a Planhat AI event in Boston
• 03:15 - Crossing the chasm: where is AI adoption actually at?
• 06:59 - We don't know our processes as well as we think
• 09:21 - Driving team-wide AI adoption: what actually works
• 11:43 - Measuring AI impact: KPIs and the multi-attribution problem
• 17:47 - Individual vs. team AI adoption — why standardization matters
• 18:39 - Jay's executive readout coaching skill in Claude
• 22:52 - Jeff's product marketing skill: Notion to branded one-pager
• 26:28 - Call transcripts as the ultimate knowledge source
• 27:15 - Automating product feedback with Fathom + Linear PRDs
• 29:42 - Forward deployed engineering and voice of customer at scale
• 33:28 - The future CSM is technically fluent
• 35:07 - What to look for when hiring CSMs right now
• 39:17 - Building a center of excellence for AI adoption
• 42:00 - Jay's website glossary and partner portal (show & tell)
• 46:08 - Wrap up