In Partnership With
Hey {{first_name | CS Pro}},
Everyone keeps telling you to be AI first, but nobody actually explains what that looks like on a Tuesday afternoon. So I sat down with Cassie Vaughn, who just left her role leading customer success across the Americas at Monday.com to become head of growth strategy at Clay, one of the most AI native companies out there.
She has built AI fluency into CS teams from both sides, and what she shared changed how I think about getting a team to actually adopt this stuff. Here is the thing, AI fluency is not about whether your team has opened ChatGPT. It is about whether they use it in a way that drives real results. Here is everything she shared including frameworks to help level up your entire CS team:
But first, today’s sponsor
↓
Most CS teams know they should be using AI. Very few have figured out how.
Your team has access to AI, but building actual post-sales workflows that influence retention, expansion, and engagement is another thing.
These on-demand recordings, from the AI + Post Sales Summit hosted by Matik, walk you through AI workflows you can implement today and close that gap, step-by-step.
Watch over a dozen recordings on how you can use AI to:
Automate the Sales to CS Handoff
Turn Customer Data Into Weekly Briefings & Action Items
Create an Insights Dashboard from Product Data
Build a CS Leadership Command Center
And more!
The trusted advisor trap
We throw the phrase trusted advisor around constantly in CS, and Cassie thinks we have it wrong. As she put it, the problem is that "people think that a trusted advisor is someone who has all of the answers and guides their customer or their advisee on how to get to those answers." Right now, nobody has all the answers, and AI is the most unknown area of everyone's world, so she uses the term thought partner instead. Your customers are excited about AI, a little nervous about it, and most of them feel like they should be further along than they are. What they actually want is someone to figure it out with them.
"I don't know where the end goal is. I don't know what this journey looks like personally, but I'm navigating it with you. And here's what I'm learning."
You do not need to have it all figured out. You just need to be in it with them.
The three layers of AI fluency
At Monday, Cassie built an AI fluency program with three parts.
The first is self-education, knowing the good podcasts, the voices worth following, and the basic language, like the actual difference between an LLM and an agent.
The second is communication, taking what you are learning and forming a real opinion so you can contribute and find your own voice.
The third is building, getting your hands on the tools, and as she points out, that is the part everyone rushes toward.
"The third layer is where everyone thinks that they need to jump to immediately, which is the building."
She is also clear that building well is not just typing a question into ChatGPT and hoping.
One line from a colleague at Clay stuck with her, and now it has stuck with me too: "Artificial intelligence is artificial and we have to remember that. It's not just intelligence. You have to give it native human intelligence for it to work appropriately." The reframe she would make now that she is starting over at Clay is that these three parts are not sequential steps you climb. They happen all at once, more like an open menu where you choose where to start.
Build a family of agents, and stretch your creativity
Here is the mistake Cassie sees everywhere. People think they need to build one all powerful agent that does everything a human does. Her advice is the opposite.
"You should think of an agent as different skill sets or families of agents who do different things, but roll up to one centralized owner or manager of all of those agents."
At Monday, her colleague Kim built a set of agents, a discovery agent, a build agent, and an optimization agent, that together act like a digital CSM. At Clay, Cassie is tinkering with an interview agent that nudges her during calls and drafts the scorecard after, while keeping a human firmly in the loop for the actual decision. AI is your co-pilot, and you are still driving. And the thing holding most of us back is not the tool, it is us.
As Cassie said, "the limiting factor most of the time in AI is our human ability to be creative."
This week's challenge
Steal Cassie's exact starting move. Here is how she describes it:
"I challenged myself for three months to listen to two different AI podcasts a day, once on my commute to work and once on my commute from work. And it changed everything."
Pick three AI podcasts and listen to two episodes a day, one on your way in and one on your way home. You are not trying to become the resident expert overnight, you are just getting close enough to the conversation to feel confident joining it. In her words, it "helped me feel, let's say 40% more confident in my ability to talk about it," and it is honestly the lowest effort place to begin.
Here are 3 AI podcast episodes from me that you can add to your playlist to help level up your AI skills:
That is it for this week. If you want the full conversation, including how she is reimagining the entire customer journey at Clay, go have a listen on Spotify, Apple Podcasts, or YouTube. And as always, let me know what you think.
I hope you enjoyed this week’s newsletter.
If you have any questions or suggestions, please feel free to contact us.
Cheers to your CS success,
Anika
