I have been thinking a lot about how deals are won, especially when you are a perceived challenger in the category versus a leader.

When you are not the default option or the perceived category leader, pressure shows up early. Buyers want comparisons. Features enter the conversation faster than planned. Pricing gets examined sooner. This is not because challenger teams do not care about outcomes. Everyone wants outcomes. However, the focus often shifts to outshining the category leader in the competitive process.

That focus can create risk for the future. Deals may close on features or price, but without explicit clarity on goals, the foundation is weak. Later, when priorities shift or adoption slows, these deals struggle. The reality is that market leaders often get more patience, while challengers do not.

This is why outcome-led deal design becomes critical when you are not leading the category.

The strongest teams slow the conversation down early. They make customer goals explicit. They define what success looks like before leaning into features. Features then reinforce the outcome instead of carrying the deal on their own.

Features help you win attention. Outcomes help you earn durability.

Earlier this week, I spent time in San Francisco with customer success and post sales leaders from across the ecosystem. Conversations at events like these are useful because patterns surface quickly. Different companies. Different stages. Same problems.

At the same time, over the last few months, I have been thinking deeply about why customer success feels harder than it should for so many teams. So, when I presented some of my thoughts at the event, they resonated deeply with the attendees.

Headcount stays flat while expectations rise. Leaders assumed AI will absorb the load. The best CSMs are stretched thin, carrying accounts and context in their heads. Escalations become the default operating model. Dashboards increase, but decisions slow down.

They are system problems.

Customer success breaks when it is treated as a team that reacts, rather than a system that operates. Hero CSMs become single points of failure. Knowledge stays trapped with individuals. Every edge case requires a manager. Alignment meetings replace ownership. The organization stays busy but outcomes do not improve.

What actually scales customer success is much simpler, and much harder.

Clear signals that demand action instead of noise. Defined decision rights so trade-offs happen fast and at the right level. Repeatable motions tied to lifecycle moments, not individual style. Incentives that reward the behaviors you want, not the activity you can measure.

These are operating choices. Tools come later.

AI deployment is a good example of this. It does not fix customer success. It amplifies whatever structure already exists. A broken system with AI just creates faster chaos. A designed system creates leverage.

If you are leading customer success or post sales today, the real work is not hiring harder or buying better software. It is stepping back and designing the system your team operates in. When the system works, people can do their best work. When it does not, no amount of heroics will save you.

For those interested, I am sharing the presentation that I made for the event.
Customer Success is a System, Not a Team (Expand, San Francisco)

Your First Six Months as a CS Leader: From Foundation to Scale

Once you decide to invest in Customer Success (check out Part 1), the first six months matter a lot. This is when you set the rhythm. How your team works. How you measure progress. And how you build habits that will eventually help you scale confidently.

Your goal is simple. Build velocity, but never lose sight of value.

Here is a practical roadmap to shape those first six months.

Month 1 to 2: Diagnose and Define

Start by understanding where you stand today.

• Audit the entire customer journey. Look at onboarding, adoption patterns, renewals, and churn data.

• Define what “value realization” means for each type of customer. For some, value shows up in usage depth. For others, it shows up in how quickly they go live or how much business impact they see.

• Segment customers in a meaningful way and look for patterns in why they stay or why they leave.

This is not the time to jump into solutions. Focus on clarity. You need to understand the terrain before you start building the road.

Month 3 to 4: Design and Pilot

With clarity in place, design the first version of your Customer Success operating model.

• Connect the dots between onboarding, adoption, expansion, and renewal.

• Create two or three simple playbooks to start with. An onboarding checklist. A renewal prep guide. An executive business review format.

• Test these with a few customer segments and observe what creates movement.

• Hire your early Customer Success Managers and align them by customer segment or vertical.

Think of this phase as your MVP. Move fast. Test often. Collect feedback. Refine.

Month 5 to 6: Operationalize and Scale

By this stage, you will have a sense of what truly drives impact. Now it is time to put structure behind it.

• Set up your systems: CRM, CS platform, and basic health scoring.

• Continue to build your Customer Success Managers’ team as you build a clear picture of whats working

• Build a reporting rhythm. Bring in regular success reviews with Product and Sales.

This is when your team starts developing muscle memory. Every dashboard. Every customer conversation. Every internal alignment meeting. All of it helps you scale with confidence.

What Actually Makes This Work

From my experience, the strongest CS teams stay grounded in a few simple principles.

• Build for speed first; scale next. Start with lightweight processes. Improve with data as you go.

• Hire builders, not managers. Early CS hires should be comfortable being player-coaches who can jump into onboarding, renewals, insights and operations.

• Stay very close to the customer. Talk to them often. Listen carefully. Most of your future playbooks will come from these conversations.

Building Customer Success in a fast-growing company is not only about protecting revenue. It is about creating a culture where customer value compounds over time.

When you get this right, CS becomes far more than a retention function. It becomes the engine that fuels your next phase of growth.

While growth is hard, sustaining it is just as hard.

If your company has crossed its first few million dollars in revenue and is scaling fast, the renewals cycle will arrive sooner than you think. That’s usually when things start to strain. Cracks begin to show in retention and post-sales, not because customers stop liking your product, but because your systems haven’t kept pace with your growth.

This is where Customer Success steps in. It’s the function that keeps growth and value aligned. It ensures that as you move fast, your customers continue to see impact.

Here’s how you can start building a strong, scalable Customer Success motion. Think of this as the practical playbook that every post-sales leader needs to build early.

Start with the journey, not the org chart

Before you create roles or hire people, take time to map the full customer journey. Look at what the experience really feels like from onboarding to renewal. Identify where customers drop off or where value breaks down.

In most startups, the biggest gaps lie between handoffs: from sales to onboarding, onboarding to adoption, adoption to renewal. Fixing these early can save you time, customers, and reputation later.

Segment by value, not just revenue

Many CS teams begin by segmenting customers by ARR. That works in the early stages, but as you scale, segmenting by value and growth potential matters more.

For instance:

• Strategic customers: build joint success plans and engage with their leadership teams.

• Growth customers: design scalable programs with clear adoption milestones.

• Long-tail customers: rely on tech-touch models, health scores, and automation.

This allows you to allocate your energy where it drives the most meaningful results.

Build motions, not moments

A good CS team doesn’t react; it moves with rhythm and structure. Create repeatable motions that drive predictable outcomes.

• Onboarding: set clear success metrics and define what time to value looks like.

• Adoption: drive product usage through nudges and insights.

• Expansion: highlight new use cases tied directly to ROI.

• Renewal: focus on reinforcing the value delivered, not just discounts or pricing.

Make these motions repeatable and supported by systems and data, rather than relying on individual heroics.

Partner across the company from the start

Customer Success cannot thrive in isolation. The best CS teams work hand-in-hand with:

• Sales: align on retention goals, expansion triggers, and clean handoffs. Check out what I wrote earlier about deals getting to “Closed Done” stage and how you need to partner with Sales on that.

• Product: feed structured customer insights into the roadmap.

• Marketing: turn customer wins into advocacy and case studies.

Cross-functional collaboration keeps customer value consistent across every touchpoint.

Track the right metrics early

Net Dollar Retention is important, but it’s a lagging metric. By the time it drops, it’s often too late. Focus instead on leading indicators of customer health:

• Activation rates and time to first value

• Weekly active usage across roles

• Executive engagement and sentiment

• Support patterns and ticket trends

Build visibility into these early. It helps you act before churn risk surfaces. Because growth is great, but sustainable growth comes from helping your customers win first.

Check out Part 2, where I share how to set up your first six months when building CS from scratch- from early wins to scalable systems.

There’s a great saying that “good fences make good neighbors.” It applies perfectly to sales and post-sales. Both functions need clearly defined KPIs so that everyone knows exactly what they are accountable for. At the same time they should feel comfortable stepping into each other’s world to provide support when needed. The key is that everyone stays clear on their own metric. That balance of clarity and collaboration only works when you have the right people in the right seats. And it only sticks when the incentives encourage partnership instead of silos.

As a GTM executive I’ve lived both situations. I’ve worked with sales colleagues where we’ve been the best of colleagues and everything clicked and worked where the partnership just didn’t land . The difference was culture. There is truth to the line “culture eats strategy for breakfast.” You can create the best-designed sales to post-sales strategy. But without trust and collaboration it simply will not work.

Here’s what I’ve learned works:

• Clear KPIs. Shared Incentives. An example of this would be “Sales owning new business and expansions while Post-sales owning time to value and renewals.” However, shared incentives align behavior. For example part of sales commission linked to successful onboarding could ensure accountability beyond closed won.

• Redefine Closed Won. A deal is not really done until the customer is live and on the path to value. Linking compensation to deployment shifts the focus from signing contracts to delivering outcomes.

• Overlap Not Drop Off. Think of it as a transition period where both teams are actively involved before one fully steps back. That overlap builds confidence for the customer.

I once had the chance to design this structure from scratch and it worked beautifully. Why. Because the sales and post-sales leaders were genuinely invested in each other’s success.

In the end playbooks, handoff meetings and CRMs all matter. But what really powers a smooth transition is the culture of collaboration at the leadership level. When sales and post-sales see themselves as partners. Not neighbors behind fences. Customers win. And growth compounds.

AI-native startups are breaking all the old rules of building companies—and doing it with shockingly small teams.

At a recent Operator Guild Summit, Henri Shi, co-founder of Super.com, shared how a new wave of startups is scaling to millions in revenue with fewer than 30 employees. That’s not a typo. Startups like Midjourney, Replit, and Eleven Labs are proving that lean doesn’t mean less—it means sharper, faster, and focused.

Want proof? Take a look at Henri’s Lean AI Leaderboard—a snapshot of top-performing AI startups with revenue-per-employee numbers that would make any SaaS founder do a double take.

So what are they doing differently?

They start with the assumption that people are NOT the first solution. Automation is. They build products that are so well-crafted, distribution is built-in—users sell to other users. They avoid bloat by hiring generalist senior talent who can do more with less. And they measure success not by team size, but by output and revenue per person.

Here’s what you can borrow from their playbook:

• Automate ruthlessly. From customer support to hiring workflows, every repeatable task is automated. If you’re still relying on human hours for basic admin, you’re behind.

• Hire generalists who ship. A small team of 10 high-performing doers will outperform 50 average specialists.

• Experiment fast, iterate faster. Speed wins. Small teams with tight feedback loops build better products.

• Own your revenue early. These companies monetize fast, often bootstrapping growth instead of chasing VC money.

Founders and leaders often think they need to scale headcount to scale impact. This new generation proves otherwise.

The game is quickly away from how many people you employ—it's becoming about how few you need to make something people love.

So ask yourself: Are you scaling your team or your impact?

Once upon a time, CS was all about relationships and QBRs. Nice to have? Sure. But now, CS is being asked to do something far more strategic—drive revenue, reduce churn, and power expansion. And here’s the kicker: it has to do that at scale, without throwing more people at the problem.

Here’s a stat that really stayed with me: according to Bain & Company, post-sales headcount has more than doubled over the past seven years. But despite that, over 75% of companies have seen their Net Revenue Retention go down. More than half saw drops of over 10%. That’s not just a red flag—it’s a flashing neon sign telling us that the old model isn’t working.

The model of the future? It’s digital-first, automation-led, and outcome-obsessed. Tools like Agentic AI are redefining what scale actually looks like. No longer about how many CSMs you have—it’s about how intelligently your workflows run, how seamlessly your touchpoints trigger, and how you embed guidance right where the customer needs it.

Another insight that stood out: customers don’t want more “alignment meetings”—they want deployment help, outcomes, and fast wins. And guess what? Most CS teams are stuck playing project manager when customers are actually looking for a trusted guide.

Let’s also not ignore the global angle. If you’re running a global CS team, it’s critical to align on metrics and dashboards—but give teams room to maintain regional nuance. Automation here doesn’t replace the human touch—it amplifies it.

One provocative question someone asked was, “If you were designing post-sales from scratch today—what would it look like?” And honestly, we may not have the luxury of starting over, but we do have the power—and the urgency—to re-architect.

This is where we are now. But it will keep evolving. As AI gets smarter and CFOs get tighter with budgets, our playbooks must keep shifting too.

But one thing is clear—we’re not just scaling Customer Success anymore. We’re designing it for impact.

As leaders, especially in GTM and customer-facing roles, we constantly encounter challenges that seem insurmountable. Customers voice concerns, complaints pile up, and teams scramble for solutions. While it’s easy to treat these as roadblocks, the seasoned leaders recognize them as opportunities to drive engagement, retention, and loyalty.

However, solving complex customer challenges effectively requires more than quick fixes—it demands first principles thinking. The toughest problems often persist because conventional solutions have already been exhausted. When traditional approaches stop yielding results, it’s time to deconstruct the problem and rebuild a fresh solution from the ground up.

Update - AI generated podcast style video at the bottom of the blog, if you would prefer to listen to this blog instead!

Applying First Principles Thinking

1. Ask Clarifying Questions Start by breaking down the problem to its fundamental elements. What is the core issue? Is it a symptom of a larger challenge? Keep asking “Why?” until you reach the root cause. Many times, what appears to be the problem is just a surface-level manifestation of something deeper.

2. Break It Down Once you identify the root cause, dissect the challenge into smaller, manageable components. This helps in understanding which elements are controllable and where new approaches can be introduced.

3. Challenge Assumptions Many solutions fail because they are built on flawed assumptions. Ask yourself: What do we believe to be true about this problem? What if those beliefs were wrong? Could there be another way to approach the situation?

4. Rebuild a Solution from the Ground Up Now that the challenge has been deconstructed, think creatively. What new strategies can be applied? Are there insights from other industries or disciplines that could be leveraged? This step requires thinking beyond conventional frameworks.

5. Execute, Measure, and Iterate No solution is complete without execution and iteration. Deploy your approach, track its effectiveness, and refine it based on real-world feedback. The key is to remain adaptable and continue questioning the process.

Why This Matters

First principles thinking transforms customer challenges into strategic advantages. By focusing on the core issue rather than patchwork fixes, leaders can craft innovative, lasting solutions that drive real impact. This mindset doesn’t just solve problems—it reshapes how organizations approach growth, customer satisfaction, and long-term success.

The next time you encounter a persistent challenge, take a step back and strip it down to its essentials. You may just uncover a breakthrough opportunity hidden in plain sight.

Additional content - I've been experimenting with Heygen to create AI-powered videos and podcasts for Scale It Up. If you enjoyed the article and prefer a podcast-style format, take a look at the video below.

The evolution of SaaS pricing models has been fascinating. Back in the day, companies started with enterprise licenses, moved to per-seat pricing, and now we're seeing a growing wave of consumption-based models. Some even predict a shift toward outcome-based models in the future. But in all these models, one thing remains critical—deeply understanding customer goals.

Why Goal Clarity is Essential

In a consumption or outcome-driven contract, goal clarity isn't a "nice to have"—it's fundamental. The conversation around goals should start in the sales process, ensuring that by the time a contract is signed, both the customer and the provider are aligned. Even in more traditional models, knowing what success looks like for the customer is key to long-term retention and growth.

Measuring the Right Kind of Usage

When it comes to consumption-based models, usage metrics can be misleading. A constantly rising usage graph might seem exciting, but a more telling sign of success is an upward trend with fluctuations. Why? Because it signals that the customer is experimenting, learning, and adapting—figuring out which features drive real value. This kind of engagement is healthier than blind, unchecked usage.

Consumption Models Shine in Downturns

One of the biggest advantages of consumption-based models is their flexibility. In economic downturns, customers can scale down spending rather than churn completely. When the market picks up, they can scale back up. This adaptability makes the model attractive for both customers and providers.

The Challenge of Forecasting

That said, one major challenge with consumption models is predictability. Customers want to budget, and businesses want reliable revenue projections. To bridge this gap, leveraging past data and cohort analysis is crucial. Providing customers with estimates based on similar profiles can help them plan better, making the model more approachable.

Doing Right by the Customer

At the core of all go-to-market strategies, one principle holds: doing right by the customer. Consumption-based models align well with this philosophy, ensuring customers pay for what they use and see direct value. As SaaS companies refine these models, keeping customer success at the forefront will be the key to long-term growth.