Fred Reichheld, Bain Fellow and creator of NPS, joins host Josh Schachter on the latest [Un]Churned episode, “187. The Creator of NPS Says It Was Never Built for Surveys” to share what two decades of loyalty economics actually taught him, and why the metric most CS orgs are optimizing isn’t capturing true growth potential.

Listen on YouTube, Spotify, Apple Podcasts, and Gainsight.com.

Subscribe now and get the [Un]Churned take straight to your inbox.

🎯 The [Un]Churned Take: The Referral Engine Is the Only Growth Lever That Compounds

Fred spent decades believing retention was the engine of loyalty economics and referrals were the icing on top. Then he went back and looked at the data more carefully.

On average, 20% of new customers come through referrals, but those 20% generate closer to 80% of profitable growth. He calls it the thing that “blows people’s minds.” But for post-sales leaders, the sharper implication isn't about acquisition. It's about where Customer Success (CS) energy goes. Most programs are built around churn reduction and NPS score management. Fred's argument is that those things capture maybe 10% of the loyalty upside. The real gold mine comes from making customers love you enough to send their colleagues your way.

Referrals Compound In Ways Retention Doesn’t

Referred customers are qualitatively different from customers who came in through marketing. They arrive already trusting you, already understanding what they’re buying, and already pre-disposed to be satisfied. They pay closer to full price and retain longer. Most importantly, they’re more likely to refer someone else and that’s where the exponential math kicks in.

Fred shares that referred customers come from true promoters who are “really acting in their friend’s best interest.” That’s a different psychological contract than a prospect who found you through a paid ad or an outbound sequence. The economics follow the psychology.

Retention is finite. Every customer has a ceiling on how much they can buy from you. The referral engine has no ceiling. It’s the only customer growth mechanism that genuinely multiplies.

And Then AI Walks In

Here’s where it gets urgent for CS leaders specifically. Fred’s view on AI is not that it disrupts loyalty economics; it’s that it accelerates them, hard, in one direction.

AI tools are being used by buyers to cut through paid signals like ads, SEO, and sponsored influencers, and get to what he calls “the truth”: legitimate reviews, peer conversations, and referrals from similar customers.

That's a direct threat to growth strategies built on paid acquisition and survey scores, but for companies that built real referral engines, it’s a direct tailwind. The buyers coming through AI-assisted research are going to find themselves leaning towards the companies with the most credible word-of-mouth. Not whoever spent the most on marketing.

What a Modern Referral System Should Look Like

When a new customer closes, find out how they came in. If a referral played a role, track it. Rank-order which referral was most important. Get that back to the people in your org who created that referenceable relationship. Make it part of their performance record, their bonus, their career trajectory.

At Bain, this was formalized: to make junior partner, you needed at least three C-suite executives who would enthusiastically pitch Bain in a competitive situation. Mid-level partner: six or seven. Senior partner: a dozen. Tracked by name. The requirement was real, not abstract.

Most CS orgs have nothing like this. They have NPS dashboards and churn reports. They might have an advocacy program with points. What they don’t have is a system that connects individual CSMs and CS leaders to the referrals their accounts generate. And one that rewards connection in ways that actually change behavior.

Most CS orgs have never built for this. As AI pushes buyers toward earned trust over paid signals, that's going to show up in the numbers.

🎧 Listen for These Moments

Fred Reichheld has been thinking about loyalty economics for longer than most of us have been in the workforce. This conversation covers the full arc, from why he built NPS in the first place, to why he thinks surveys are over, and what he’s arguing in his next HBR piece.

1. Why Fred thinks 90% of NPS implementations are missing the point, and the specific misuse that he argues destroys the signal entirely.

2. The earned growth framework and how to calculate it without a single survey; all of which live in your CRM already.

3. The Bain referral model in detail and what it would take to build something equivalent in a CS org.

🔎 Where to Find Fred Reichheld

• LinkedIn: linkedin.com/in/fred-reichheld

• Bain profile: bain.com/our-team/fred-reichheld

📎 Referenced in This Episode

• Book: Winning on Purpose by Fred Reichheld

Wrapping Up

Fred leaves CS leaders with this question, so now we’ll pass it along to you: if your team disappeared tomorrow, would your customers still refer you?

See you next week 🧠

The response from most CS organizations has been to push their teams toward more strategic, outcome-driven work. But without a clear definition of what strategic work actually looks like, teams default to what they know: reactive problem-solving, relationship maintenance, and last-minute saves. These CS heroics at scale are unsustainable for ambitious retention numbers and for the people doing the work.

So if you asked your team to be more strategic and nothing has changed in their work, can you identify why?

The problem is that “be more strategic” is a destination, not a direction. Your Customer Success Managers (CSMs) want to get there, but without a defined framework for what “strategic” actually looks like, the directive is just pressure.

Paycor is a human capital management (HCM) platform that helps small and mid-sized businesses streamline payroll, HR, recruiting, and workforce management. Adnan Rahman, Head of Customer and Partner Success, and Alan Schaffer, Sr. Manager of Customer Enablement, built a value realization playbook to help their CSMs drive customer outcomes strategically and at scale.

Here’s how they did it and the unexpected impact it had on their team.

🎧 Hear Adnan on the [Un]Churned Podcast

Why Success Plans Weren’t Working

Before the playbook, Paycor’s success plans were, as Alan put it, “not very meaningful, impactful, or consistent.” Their customers were using their tools, but didn’t have a shared idea of success.

One CSM might count a resolved support issue as a win. Another might record a completed training. Someone else might mention an executive check-in that led nowhere. All of these went into the “success plan,” but they weren’t aligned, and the real business outcomes Paycor could deliver weren’t being tracked.

Paycor delivers value in many ways, but without alignment on the core outcomes that matter most to customers, it’s difficult to consistently reinforce that value or scale it across the organization. What they saw in practice was that each function defined “value” through the lens of their own role:

• Sales often framed value around the initial business case: cost savings, consolidation of systems, or improving hiring outcomes.

• CSMs tended to anchor on activity-based wins: resolving issues, completing trainings, or maintaining a strong relationship with the primary contact.

• Support and Services teams focused on responsiveness and issue resolution as indicators of value delivered.

• Finance or procurement stakeholders often viewed value through cost comparisons, such as what was paid versus a competitor or staying within budget.

• Operational teams sometimes defined value in terms of usage or throughput, like the number of payrolls processed or transactions completed.

All of these are valid signals of value, but they weren’t aligned to a shared definition of business outcomes. Without that agreement, their current success plan strategy could never be consistent at scale.

With over 30,000 customer relationships to manage, scale mattered at Paycor. A framework that depends on individual CSM judgment or style doesn’t hold at that volume. Whatever they built needed to be repeatable and easy enough for a CSM to pick up and run with, regardless of tenure, territory, or personal instincts about what strategic work looks like.

Adnan and Alan started here. They needed to define value before they could deliver it. What they didn’t fully anticipate was how much that clarity would change the nature of the CSM role.

Building the Playbook from the Outside In

Their development process started with deep research. Alan and his team talked to sellers, solutions engineers, learning, and development staff and customers. They reviewed call transcripts and asked questions like:

• What matters most to customers?

• What worries them during the sales process?

• What issues keep coming up after they start using the product?

Defining the Outcomes

The goal wasn’t to map every possible value Paycor could deliver. That list would have been too long to be useful. The goal was to identify the few categories that mattered most and that the entire organization could get behind. “You want to keep things somewhat simple,” Adnan says. “There are a lot of things you could pick. How do we keep teams focused on, let’s say, five main things, and get real agreement on what those things are?”

So that’s exactly what they did. They boiled down research and focused their value framework on five core areas where their customers typically seek transformation:

Each area connects to specific business outcomes and KPIs, making it easier to tailor conversations to what matters most to each customer.

Establishing the Metrics

To make the value framework actionable, each outcome area was paired with a defined set of metrics that help customers measure progress and validate results. These metrics give CSMs and customers a shared way to quantify success and anchor conversations in outcomes rather than activity. Here are some examples:

1. Attracting Talent

• Number of applicants per role

• Time to fill (often targeting a 30–40% reduction)

• Offer acceptance rate

2. Retaining Talent

• % of employees with completed development plans

• Frequency of manager check-ins and 1:1s

• Reduction in voluntary turnover

• Employee Net Promoter Score (eNPS)

3. Administering Benefits

• % of employees enrolled by enrollment deadline

• Benefits participation and utilization rates

• Time saved during open enrollment

4. Optimizing Workforce

• Forecast accuracy (scheduled vs. actual labor)

• Manager satisfaction with workforce planning tools

5. Simplifying Back Office

• % of workflows automated

• Admin and manager system usage rates

• Payroll error rate

The value framework is embedded directly into Quarterly Business Reviews (QBRs), serving as the foundation for how CSMs structure the conversation—aligning on goals, tracking progress, and demonstrating measurable outcomes over time. These metrics also act as conversation starters, helping customers think more strategically about what success looks like and how to measure it.

“To help CSMs connect customer goals to tangible results, we partnered closely with our product team to map each outcome to the Paycor capabilities that enable it. For example, a customer focused on retaining top talent would align to talent development solutions, with success measured through improvements in engagement, retention, and employee growth.” - Alan Schaffer

This structure ensures that every QBR clearly connects three things: the customer’s stated goals, the actions taken, and the measurable impact achieved.

Growing Cross-Functional Alignment

Getting cross-functional agreement on the categories was a challenge in itself. When you’re building something that sellers, CSMs, solutions engineers, and learning teams all need to use consistently, you’re building a shared language. This requires the kind of multi-stakeholder interviews that most teams skip because they feel slow. Alan’s view: you can’t shortcut it. The consistency you get on the back end is only possible if you do the alignment work on the front end.

One of the biggest learnings was how much this work influenced teams beyond Customer Success. What started as a CS initiative quickly made its way upstream into the sales process. The value framework and success planning approach are now being introduced on prospect calls, to clearly outline the outcomes buyers can expect and the structured partnership they’ll receive post-sale.

“That wasn’t part of the original plan. We set out to improve how CSMs drive value after the sale, but it ended up reshaping how we position value before the deal is even closed.”
- Alan Schaffer

They were surprised at how powerful the alignment between Sales and CS became. Instead of Sales, CS, and customers having slightly different definitions of success, Paycor now has a shared language from the first conversation. It reinforces a simple idea early: Customer Success isn’t something that happens later. It’s the foundation of the partnership from day one.

How the Playbook Gets Used

With the playbook developed, it was time to set it in motion. It operates in a cyclical structure.

A CSM opens with a strategic conversation rooted in two open-ended questions:

• What are your goals for the next six to twelve months?

• What problems are you trying to solve?

Using the insights from that conversation, the CSM creates a success plan. This shared document connects customer goals to specific outcome categories, with metrics attached.

From there, the CSM becomes a curator. If a customer has flagged hiring velocity as a priority, they’re receiving relevant content, such as articles, webinars, and product guidance, specifically tied to that goal. Instead of generic Paycor communications, customers receive targeted communications that ladder up to their desired outcomes.

At the QBR the loop closes. The CSM comes back to what was agreed, shows what moved, and gets the customer to verify. “You mentioned you wanted to reduce your time-to-hire. Using this product, you cut it by 50%.” Once you’ve documented an outcome, you can reset and go again. New goals. New metrics. Another cycle.

One surprising outcome was the increased level of executive engagement. Paycor’s CSMs work primarily with payroll administrators, HR directors, and VP-level contacts. CHROs and CFOs aren’t usually in the room. But when the conversation shifts from “here’s what the platform can do” to “here’s the measurable improvement your organization achieved,” executives start showing up. The playbook created a reason for them to do so.

The Unexpected Win: Boosting Team Morale

The Human Capital Management (HCM) industry isn’t for the faint of heart. As Adnan describes it, it’s “relentless and thankless, especially at year-end.” Customers are under a lot of stress, issues come fast, and there is a constant pull toward reactive firefighting. The work left his team with no way to feel they were winning, and inevitably, burnout followed.

The value realization framework changed this energy completely. When CSMs have a clear idea of what strategic work looks like and the tools to have those conversations, they get back something they were missing: the feeling that they’re making progress. Alan calls it “a renewed sense of focus and energy.” Confidence went up and the stress of heroics went down.

Before launching, Adnan surveyed the team. The high-performing CSMs wanted this. Not because it made their jobs easier, but because it gave them a framework for the conversations they already thought they should be having. They wanted to be thought leaders for their customers, but never had the structure to do it.

That’s the piece that’s easy to miss when you think about value frameworks as customer-facing tools. The CSMs who’d been operating in a transactional mode were doing it because the work was set up that way. When you give them a defined path to something more strategic, the identity shift follows. How a customer sees their CSM changes. How the CSM sees themselves changes. Paycor went from being simply a vendor to a strategic partner, and the CSM was the champion leading the way.

Alan and Adnan made two investments that were critical to the overall success of their playbook rollout.

Investing in Enablement

Paycor worked with Bob London to teach CSMs how to ask questions that move the conversation from “let’s talk about your issues” to “let’s talk about your business.”

These enablement sessions reinforced a critical behavior shift: great customer conversations start with understanding, not solving. CSMs were trained to ask open-ended, strategic questions and resist the urge to immediately jump into solutions.

“As Nick Mehta once shared with my team, the greatest asset a CSM can have is to be curious. Ask questions to understand. For many on the team, this was a reset. It gave them permission to slow down, listen deeply, and focus on the customer’s broader business context instead of just product usage or immediate issues. As a result, conversations became more strategic, insights were richer, and CSMs felt more confident leading discussions with higher-level stakeholders.” - Adnan Rahman

This training was essential. The playbook showed CSMs what to discuss and the training made it actionable, showing them how to have impactful value conversations. If you want to hear Adnan expand on the curiosity mindset and what it actually takes to coach a team toward strategic conversations, check out his episode of the [Un]Churned podcast.

Investing in Talent Clarity

Once strategic work is defined, it’s easy to see who’s having those conversations and who isn’t. Coaching became more focused. Gong call reviews targeted the right moments. The playbook made it clear who was adapting to the new model and who wasn’t. Not everyone made the transition, but that clarity was valuable too.

Together, these investments ensured the playbook didn’t just exist on paper. The team had the skills to execute it and a clear picture of what execution actually looked like. With the human side of the rollout on solid footing, the question became, “How do you deliver this level of strategic engagement across tens of thousands of customer relationships?”

The Digital Layer

The next step is figuring out how to scale the value playbook through digital channels and AI-assisted outreach. With 30,000 relationships, not every customer can have a dedicated CSM.

As a customer moves through the sales cycle, key information about their goals and context follows them into the post-sale relationship. For customers without a CSM, AI-driven campaigns send targeted content based on their outcome categories using the same logic a CSM would use in a one-on-one conversation, but now at scale.

For customers with a CSM, digital campaigns work alongside the human relationship. As Alan says, it arrives “on a silver platter.” The CSM doesn’t have to search for context; it comes to them. Using Gainsight’s Journey Orchestrator, they’ve built signal-driven journeys based on key customer parameters. These journeys allow them to engage customers directly with targeted, outcome-aligned content, while simultaneously creating coordinated calls to action for CSMs.

Example 1: Maximize Growth Opportunities

These journeys identify customers at critical growth moments and deliver timely, value-added content, tailored support, and relevant expansion pathways. At the same time, Gainsight surfaces these signals to the CSM as a Call to Action (CTA), equipping them with the context they need to engage in a more strategic, informed way.

Example 2: Deliver Client Education

These journeys focus on client education to accelerate onboarding and time-to-value. New users are enrolled in targeted programs that deliver role-specific training and certification content, helping them get up to speed quickly and begin realizing value early in their lifecycle. CTAs are also sent to CSMs, prompting them to follow-up on new administrator certifications to ensure successful adoption.

Alan and Adnan built the playbook first, tested it with real CSMs, and are now using digital tools to scale what works. That’s the right way to do it. If you automate before you know what you’re delivering, you just get more volume, not more value.

Once You Define Value, You’re Accountable to It

The hard truth about building a playbook like this is that once it’s in place, you can’t ignore what it shows. You see which customers are having strategic conversations and which aren’t. You see which CSMs use the model and which are still reactive. You see which parts of the organization are aligned and which aren’t.

Paycor set out to solve a customer value problem. Along the way, they also solved a team clarity problem. The playbook didn’t just change how CSMs talk to customers, it changed how leaders can see, develop, and hold the CS team accountable for more than just managing tickets.

That’s what this kind of initiative really asks: be willing to see what you build. Not every organization is ready for that. But organizations that are ready often find their CSMs were ready all along.

About This Article

This article draws from a detailed conversation with Adnan Rahman, Head of Customer and Partner Success, and Alan Schaffer, Sr. Manager of Customer Enablement, both at Paycor, on how they developed a value realization framework that changed both customer outcomes and team morale on Paycor’s CS organization.

Adnan also joined the [Un]Churned podcast to talk through how CS teams can lead with business outcomes, and what it actually takes to make that shift stick. Check out his episode, here.

All data referenced here has been sanitized to protect confidential business information.

Adnan Rahman, Global Head of Customer and Partner Success at Paycor, joins host Josh Schachter on the latest [Un]Churned episode, “186. Why The Best CS Leaders Start With The Boardroom, Not The Product.” He shares how Paycor structures Customer Success (CS) across a 35,000-account base, why discovery questions were crucial, and how he sees AI helping to scale their success.

Listen on YouTube, Spotify, Apple Podcasts, and Gainsight.com.

Subscribe now and get the [Un]Churned take straight to your inbox.

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🎯 The [Un]Churned Take: Curiosity Is Infrastructure, Not Instinct

Adnan Rahman built a value realization playbook for his team at Paycor, complete with outcome categories, leading and lagging metrics, a cyclical success plan structure, and a Quarterly Business Review (QBR) process. But in building it, he learned something the playbook itself couldn’t fix. You can’t operationalize value delivery if you can’t surface what the customer actually cares about in the first place.

Inspired by a past visit from Nick Mehta, whose parting advice was to “be more curious,” Adnan dug deeper to figure out what that actually looks like in a strategic sense.

His solution was to make curiosity part of the process.

The Simplest Answer Is to Ask More Questions

Health scores reward account stability. Renewal timelines reward contract closings. Escalation queues reward responsiveness. The CSM who keeps things quiet is doing their job by every measure you’ve given them. There’s no metric for the question they never asked.

To help him incorporate curiosity into the value realization framework, Adnan brought in customer discovery expert and coach Bob London. Bob shared a deceptively simple rule for discovery: stop asking questions customers can answer with a yes or no. “Do you have hiring challenges?” gets you nowhere. “Which parts of your hiring process feel inefficient?” gets you a conversation. Same topic, completely different output.

Adnan’s team put that into practice with two questions. The first: if you could sit in on your board meeting right now, what’s the one thing they’re debating? The second, which he calls the churn question: if a competitor called you today, would you answer, and what would you say?

His team was hesitant about the second one, assuming that customers would avoid answering. But the opposite happened. “Customers are very forthcoming when you give them the opportunity to tell you about the relationship and how things stand,” Adnan shared. They had opinions; they just needed someone to ask.

Why Most Frameworks Fail Before They Start

The most critical step leaders can miss when moving towards a value delivery strategy is that they define outcome categories and build frameworks, but assume their team already knows how to help customers clearly articulate priorities in measurable terms. In reality, most CSMs don’t, which isn’t a personality issue, but a training gap that often gets mistaken for a lack of motivation.

When CSMs get stuck in tactical conversations, it’s rarely due to a lack of care. The real issue is that nothing about their environment makes it easier to have strategic conversations instead of reactive ones. With the right questions and structure, that dynamic shifts. Customers see their CSMs differently, and CSMs start to see themselves differently, too.

🎧 Listen for These Moments

This conversation goes places most CS content doesn’t. A few cues worth listening for:

1. The resistance before the results: Adnan’s team didn’t immediately buy in. He talks about what it took to get them there, and why the hesitation was worth pushing through.

2. The long-tail customer problem: How Adnan thinks about AI agents specifically for the accounts that will never have a dedicated CSM, and why he’s sequencing efficiency and insights first before touching automation.

🔎 Where to Find Adnan Rahman

LinkedIn: linkedin.com/in/adnan-rahman

📎 Referenced in This Episode

• Bob London — customer discovery coach and creator of the UBR method

📅 Coming Up

Pulse 2026 — Gainsight’s annual conference is May 27–28 in Las Vegas. CS and AI are converging faster than most organizations are ready for. Come see what leading teams are actually doing. Register at gainsightpulse.com →

New Rules of CS: Expansion — The series continues June 9th with a session on identifying early expansion signals. If your team owns any part of the revenue number, this one’s worth your time. Save your seat →

Wrapping Up

Customer Success is in the middle of an identity shift from vendor contact to strategic advisor. If you feel like your team is still struggling through this metamorphosis, it might be time to do the unglamorous work of discovering what strategic thinking actually looks like. Not just the vision, but also the infrastructure.

See you next week 🧠

When Sergey Kondratiuk, Principal Engineer at Gainsight and co-founder of Update AI (now Gainsight Atlas), set out to build the evaluation system behind what would become the Gainsight Atlas Renewal Agent, he knew the engineering side was solvable. The harder problem was the criteria.

What does the appropriate tone sound like in a conversation where a customer is telling you their business is struggling? How do you define the right way to handle a customer who hints at churn three times before the consent recording even kicks in? Those aren’t questions with clean algorithmic answers. They come from years of being on calls. So, Sergey brought in someone who had that expertise. That’s where Skye Maddox, Senior Enterprise CSM at Envoy and contracted CS annotator for Gainsight, came into the picture.

What followed was a crash course in what it actually takes to teach an AI agent to read a room.

The Edge Cases Only a Human Can Surface

The first phase was stress testing. This consisted of running hundreds of simulated calls with the renewal agent and deliberately surfacing every edge case Skye had encountered in real customer conversations. The customer who opened the call by saying they can’t afford to renew, then gets asked two minutes later whether they plan to renew. The customer who switched languages mid-call. The customer who went quiet in a way that any experienced CSM would read as “I’m about to churn,” but that the agent has no vocabulary for yet.

“If there’s a voice agent handling renewals,” Skye says, “it’s going to be new to a lot of people. The very first interaction they have with it matters. Because there’s so much skepticism about AI already.”

Skye’s recent experience with AI had stuck with her. She’d called into Dominos and encountered an AI voice agent. The experience was so bad, she immediately asked for a human. The stakes of a renewal conversation are objectively higher (a fumbled call doesn’t just mean a wrong topping, it means a lost account) but the instinct she took from that moment stayed with her through every test call she placed. Her benchmark wasn’t “did the agent complete the task.” It was “would I want to keep talking to this thing.”

From Stress Test to System: How Annotation Works

Stress testing alone doesn’t improve an agent. What turns test calls into a learning system is annotation.

Here’s how the process works: after each test call, Skye logged what went wrong. Not in engineering terms, but in CSM terms. The agent ended a call without a proper close. It switched languages mid-conversation without acknowledging the shift. It misread a polite hedge as a soft yes. Those observations were compiled, fed into AI to identify patterns, and grouped into distinct failure modes categorizing what could go wrong in a renewal conversation.

Those failure modes became the foundation for what Sergey’s team built next: judges. A judge is a structured LLM call that runs alongside the agent and evaluates every conversation against a single, specific criterion. One judge evaluates whether the agent acknowledged a customer’s financial distress before moving to the renewal question. Another evaluates whether the call summary correctly flagged churn risk. Another checks whether the agent introduced itself appropriately. The reason judges are scoped that tightly is accuracy. The narrower the task, the more precise the evaluation.

But judges are only as good as the criteria they’re built around; and that criteria came from Skye. A true subject matter expert is critical at this stage. Engineers can do their best to anticipate failure modes, but without the experience of someone in those shoes everyday, they’re likely to miss what an SME can see coming.

The Calls Nobody Scripted For

Skye’s input wasn’t a QA step or a sanity check at the end. Her CS pattern recognition was the raw material the entire eval system was built from. Without it, there would have been nothing to build judges around.

Two failure modes in particular capture what only CS experience could have surfaced:

Identifying Churn Intent

Customers don’t say “I’m going to churn.” They hedge. They deflect. They say things like “we’d need to look at this internally” or “we’re going through some changes.” A CSM hears those phrases and adjusts. Skye tested this extensively and identified different inflections, levels of uncertainty, and ways of expressing the same hesitation, to see whether the agent would read it correctly in its call summary.

“You want to make sure you’re capturing renewal intent correctly,” she says. “Because you could put a renewal manager in a weird spot if the agent says they’re likely to renew and then they call and the customer says, no, actually, I said I was undecided.”

A situation like this is far beyond a minor inconvenience. If the agent is supposed to save CSM time by handling initial renewal outreach in long-tail segments, and it’s misclassifying intent, it’s creating rework and eroding trust in the system at exactly the moment when the relationship is most fragile.

The Consent-Recording Gap

The consent-recording gap surfaced the same kind of problem. While the agent’s behavior was technically correct, it was humanly wrong. In one test call, the agent designed a sequence—introduce, collect consent, then engage—which is by the book from a compliance standpoint. But real conversations don’t wait for the right moment to get emotionally complicated.

A customer who says something important before the formal start of the call is still saying it. A CSM would know to hold that. The agent didn’t. For example, a simulated customer opened with “my business isn’t doing well and I’m not sure I can afford this renewal”, but a few minutes later, would get a bright, undaunted “so, are you thinking about renewing your subscription?”

“I knew that would tick someone off,” Skye says. “Because I know it would’ve ticked me off.”

These are the gaps that close when engineering and CS are working together from the start.

The Feedback Loop Doesn’t Have a Finish Line

The eval system doesn’t just catch problems before launch. It keeps watching after the agent goes live. Manually reviewing every conversation at scale is a gargantuan feat. But judges and metrics make that ongoing monitoring possible. How often is the agent handling financial distress conversations correctly? Is it reading churn intent accurately? Is the pattern holding, or has something drifted?

Sergey frames it as a control problem. “You don’t want your users to know about issues before you do. Proactively detecting problems is the goal. You shouldn’t need your customers to report it.”

The Gainsight renewal agent, part of Gainsight’s agentic offering, Atlas, is designed to scale CS coverage into segments where human-led outreach can’t reach. That only works if the agent is actually good at the job, not just completing the task. An agent that handles most conversations competently but badly misreads the distressed customer call creates as many problems as it solves. The eval system is what makes the difference between an agent that performs in a controlled test environment and one that holds up when real customers, with real problems and real business pressures, pick up the phone.

The harder thing this work forces you to accept is that “good enough” is a moving target. Every iteration surfaces something new. The failure modes don’t have an end state. The feedback loop is the work, not a phase of it.

About This Article

This article draws from detailed conversations with Skye Maddox, CSM at Envoy (contracted to Gainsight’s Atlas team for AI agent evaluation work), and Sergey Kondratiuk, Principal Engineer at Gainsight, on the human-AI collaboration behind Gainsight’s renewal agent eval system.

Scott Barker, former head of partnerships at Outreach and co-founder of GTM Fund, joined Josh and co-host Jenny Calvert on the most recent [Un]Churned episode, “185. The AI Acceleration Decade Is Coming for Everyone. Are You Ready?” He’s not here to tell you to take more walks. He’s here to argue that the practices most Customer Success (CS) leaders treat as nice-to-haves are the ones that will determine who’s still standing at the end of this decade.

Listen on YouTube, Spotify, Apple Podcasts, and Gainsight.com.

Subscribe now and get the [Un]Churned take straight to your inbox.

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🎯 The [Un]Churned Take: Slowing Down Is the Only Skill AI Can't Replicate

The Acceleration You Didn’t Sign Up For

Scott spent a decade building what appeared to be a flawless GTM career. He was the youngest director in Outreach’s history, $20M to $250M ARR, $100M under management—and then had a panic attack. The weight of running the wrong operating system at full speed finally took hold. His benchmarks were money and status, and the better he got at hitting them, the less they delivered.

Scott chose his acceleration decade. Nobody is choosing this one. AI is compressing timelines, raising expectations, and making “more with less” a structural condition rather than a budget ask. The Gainsight 2025 CS Index, drawing on data from more than 400 CS professionals, found CS leaders are under pressure to support more customers, adopt AI for scale, and demonstrate measurable revenue impact without proportional headcount growth. Scott looked at that picture from an ashram in India and recognized it immediately. It’s the decade he just survived.

What AI Actually Can’t Do

“What AI can’t do,” Scott argues, “is find meaning in someone’s life.” Scarcity creates value. If AI generates breadth, speed, and synthesis on demand, the things that don’t get cheaper are depth, judgment under uncertainty, and the capacity for original thought.

While constant AI collaboration makes us more productive, it may be lowering our tolerance for slow, generative thinking. CS leaders can’t afford to atrophy this muscle. The role is built on reading customers, holding relationships under pressure, and making judgment calls without a complete picture. None of that gets easier if you’ve outsourced the thinking.

His practical version: pick one hard question—what does success actually mean to you now? what is your team’s real ceiling in the next 18 months?—and spend two weeks exploring it with no deliverable in mind. Explore this for the sole purpose of going deep.

Acceleration Without Integration Breaks People

The most countercultural thing Scott proposes is also the simplest. Treat your attention like a financial asset and pay yourself first. Every day, before Slack and dashboards and renewal prep, a one-hour block with four components: movement, stillness, breath, and solitude. He’s explicit that timing is secondary to consistency. If checking email first removes the friction that’s stopping you from doing the practice, check the email. The goal is sustainability, not an ideal morning routine.

As the pace of AI accelerates, your capacity to absorb that change has to grow with it. CS leaders who invest only in AI adoption without investing in the human capacity to integrate change will see the returns diminish and the burnout accumulate. Investing in AI without investing in yourself is just a faster way to hit the same wall Scott hit.

🎧 Listen for These Moments

This conversation goes places most CS content doesn’t. A few cues worth listening for:

1. The six-hour silence protocol: Scott’s specific, repeatable practice for clearing inputs and recovering the capacity for original thought. More practical and more uncomfortable than it sounds.

2. The attention economy argument: his case that attention may already be worth more than money in an AI-flooded market, and what that implies for where you invest your own.

3. The “old programming” audit: the idea that most leaders are still running a definition of success written by their 22-year-old self, and why that’s worth examining before the next wave of AI pressure lands.

Where to Find Scott Barker

• LinkedIn: linkedin.com/in/ssbarker

• Substack: The Wake Up Call

Referenced in This Episode

• The Wake Up Call: How to Prepare for the Next Decade — Scott’s article that stopped a lot of people in this industry cold. Read the comments too.

• Gainsight 2025 CS Index — Data from 400+ companies on how CS teams are scaling with AI.

📅 Coming Up

Pulse 2026 — Gainsight’s annual conference is May 27–28 in Las Vegas. CS and AI are converging faster than most organizations are ready for. Come see what leading teams are actually doing. Register at gainsightpulse.com →

New Rules of CS: Expansion — The series continues June 9th with a session on identifying early expansion signals. If your team owns any part of the revenue number, this one’s worth your time. Save your seat →

Wrapping Up

If AI keeps making skills cheaper and breadth easier, the thing left to compete on is the quality of your thinking. That only comes from protecting the conditions that make it possible.

See you next week 🧠