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There's a common misconception that growth solves all problems. More customers, bigger deals, and higher revenue. What's not to like? Yet, anyone who's scaled a business knows that growth often reveals problems faster than it solves them.
Nowhere is this more painfully true than in technical support.
The subtitle of this piece refers to the hit song by Loretta Lynn, later covered by Sinéad O'Connor. When fame and fortune come knocking at your door, it can cause other important things to fail. That got us thinking about how technical support teams often struggle to handle rapid company growth, and how those failures could be prevented or reversed.
In the early days of a company, technical support feels manageable and even rewarding. Engineers directly answer customer questions in Slack, creating a tight feedback loop that keeps the whole company close to the customer. Documentation is created casually, updated sporadically, and most knowledge is stored informally in someone's memory rather than neatly archived.
Tribal knowledge and quick fixes prevail. It's messy, but it works well enough... until it doesn't.
Initially, informal support through chat tools and ad-hoc troubleshooting works fine. However, as user numbers increase and complexity deepens, these informal methods quickly become unsustainable. Tickets get lost in the fray, engineers are solving the same problem multiple times, and customers are waiting longer to get unblocked.
Many rapidly growing companies manage support effectively at first through informal channels and quick meetings. But as their customer bases grow, informal systems fragment, leaving support engineers overwhelmed and unable to maintain useful, current documentation.
We've observed a common scenario across many companies: support teams shift suddenly from managing well to feeling overwhelmed. It often seems like they're pinned under a waterfall, struggling against the sheer volume and unable to get back up.
Consider a company we recently encountered. Initially, their support team handled inquiries effortlessly through informal Slack chats and quick fixes. However, customer numbers tripled within months, turning a steady stream into a torrential flow, and their informal system broke under pressure, causing severe backlog, frustrated customers, and burned-out support engineers.
This overwhelming situation makes lasting improvements challenging. The gradual buildup of issues often goes unnoticed until it becomes overwhelming. Before you know it, you're spending all your time (and more) just getting through the endless ticket backlog.
You try your best to keep up. You add dedicated customer success roles. You implement a ticketing system, enforce documentation standards, and insist on better knowledge-sharing processes. But it's all reactive, and nothing quite sticks. Documentation falls behind faster than you can keep up. Chat threads become impossible to navigate.
Growth, ironically, makes your support structure brittle precisely when you need it to be resilient.
Slowly, the cracks widen:
We've frequently seen employee burnout in fast-growing SaaS companies directly impacting morale, causing turnover, and further straining support capacity.
Success hasn't just brought scale. It's brought entropy with it.
Entropy isn't about poor execution or lack of effort. It's a systemic problem: the natural outcome of informal systems colliding with increased complexity and volume.
Each new customer adds more questions. Each product update introduces more edge cases. Each new hire faces a steeper learning curve, buried under legacy threads and incomplete documentation.
Teams become trapped in a perpetual state of reaction, never truly addressing the root causes of customer issues. Even when well-intentioned support engineers update documentation on the fly, they tend to document solutions tailored to specific problems. This unintentionally confuses future users if their issues differ, causing docs to misalign with tickets and further compounding confusion.
Entropy makes your growth feel unsustainable, despite your best intentions.
The solution isn't more heroics, overtime, or documentation alone. It's creating systems that scale naturally with complexity:
The key shift is from reactive heroics to proactive design.
Until now, designing your support effort for success required meticulous documentation and strict organizational discipline. Information was only as good as the structure imposed by your team. This was manageable when support meant primarily handling tickets via email (remember those days?). But then chat and other channels emerged, scattering information further. The good news is that the right AI can fix all that. Even messy, highly scattered, or inconsistently updated documentation becomes clear and actionable. From our own experience, if it's written down anywhere, whether Slack, Jira, Zendesk, or internal wikis, RunLLM will find and organize it. It's an AI superpower: we make sense of it, synthesize it, and deliver that knowledge precisely when and where it's needed, tailored to the question and context. In other words, AI done right can dig you out of almost any hole.
Scaling successfully means recognizing that what got you here won't get you there. It requires building systems to manage, not mask, entropy. With the right AI, that's achievable now.
Here's how you can effectively manage support at scale:
Done right, technical support transforms from a cost center into a strategic driver of acquisition, onboarding, and customer success. Companies investing in robust support systems don't just manage growth; they leverage it.
Ready to explore how your company can build a more resilient support system? We're here to help you get started.
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