One thing I love about customers is that they are divinely discontent. Their expectations are never static – they go up. It’s human nature. We didn’t ascend from our hunter-gatherer days by being satisfied. People have a voracious appetite for a better way, and yesterday’s ‘wow’ quickly becomes today’s ‘ordinary’. I see that cycle of improvement happening at a faster rate than ever before.
Excerpt from his 2017 Letter to Shareholders
Every startup begins with energy, ambition, and a product that sparks excitement but scaling a company isn’t about the energy alone. It’s about the strength of the systems behind the scenes and whether they can rise to the pressure of growth.
At AWS, and now at DevRev, I have seen this pattern repeat itself. A product may be loved by customers, but the workflows, ownership, and communication that support it begin to fray as the company expands. Complexity multiplies, teams overlap, and customer expectations, which Jeff Bezos once called “divinely discontent,” continue to rise.
What felt effortless with ten people can feel impossible with a hundred. The lesson is simple: scaling is not just about growing faster; it is about growing stronger.
In this article, I’ve distilled some of the lessons I’ve learned the hard way on what makes a system resilient, where things tend to go wrong, and how it can be fixed to build systems that are sustainable.
Defining resilience beyond uptime
Resilience isn’t about uptime alone. It’s about how a company senses what’s coming, absorbs impact, and recovers while keeping people informed and confident.
It shows up in four ways:
- Monitoring: The quiet awareness that spots early signs before they turn into failures. Good systems do not wait for alarms; they anticipate them.
- Mitigation: Acting fast, not frantically. When something breaks, contain the problem before it spreads and protect the rest of the system.
- Recovery: Getting back up quickly and visibly. Progress should be felt, not just reported.
- Communication: Keeping everyone in the loop. Clarity in tough moments earns more trust than perfection ever could.
Resilience is not reactive; it is designed. It is the sum of preparedness, responsiveness, and transparency. When built well, it strengthens trust both internally and externally, turning incidents into opportunities to prove reliability.
Why scalability starts with architecture
If resilience is about recovering gracefully, scalability is about growing without strain. It begins with the structure of the system itself, its architecture. The right architecture prevents breakdowns not by resisting change, but by absorbing it. It spreads risk, keeps failures contained, and allows each part of the system to evolve without breaking the whole.
At AWS, one of our earliest lessons was to design for failure and to assume that something, somewhere, will eventually go wrong. That mindset shaped how many modern systems evolved. Netflix embraced the same principle through Chaos Monkey, a tool that randomly shuts down production servers to test whether the system can survive unexpected failures. It may sound chaotic, but it is an exercise in control.
Scalable architecture is rooted in four principles: modularity, redundancy, isolation, and decoupling. These keep systems stable as they expand and adaptable under pressure:
Modularity: Build systems in self-contained blocks so each piece can grow, break, or improve without halting the whole stack. Modularity gives teams ownership and keeps change manageable.
Redundancy: When the primary fails, backup systems kick in and take the load so operations continue smoothly.
Isolation: Contain failures. One system’s issue shouldn’t cascade into another. Isolation keeps problems small and recoveries quick.
Decoupling: Design how those blocks connect. When communication flows through clear interfaces instead of hidden dependencies, the system stays flexible even as it scales.
Each of these principles reinforces the others. Together, they create systems that don’t just scale , they stay predictable under challenges.
Similarly, a strong system does not assume everything will work; it assumes some things will fail and builds with that in mind.
That mindset encourages accountability at every level. When something breaks, the system points directly to where it happened and allows teams to respond quickly without blame or confusion.
The process that keeps teams strong
Every company operates in a web of shared projects and shifting priorities. Over time, chaos appears not because people are not working hard, but because they are not working clearly. Clarity does not come from effort alone; it comes from design. These are the building blocks that make scale sustainable:
- Clarity of scope – Everyone should know the problem they are solving and how success will be measured.
- Modularity of work – Projects must be split into smaller, manageable units. Each team should own a specific part that can progress without waiting on others.
- Single-threaded ownership – One person must be accountable for every major outcome. This eliminates grey areas and avoids diffusion of responsibility.
- Visible communication – Work and dependencies should be transparent. Visibility keeps alignment alive.
When these principles break down, organizations fall into known traps: duplicated work, unclear ownership, or meetings that replace decisions.
Structure creates clarity, but rhythm creates momentum. Without cadence, even great systems drift.
Make sprints your rhythm
- Weekly syncs: Maintain alignment across teams, surface blockers early, and keep progress visible.
- Monthly 2×2 reports: Offer a quick snapshot of business health, customer sentiment, and key field insights.
- Quarterly reviews: Step back to evaluate outcomes, refine strategy, and ensure long-term focus.
These rituals may not sound revolutionary, but they create a pulse, a consistent rhythm that prevents drift. These habits matter most when pressure hits because scale always introduces pressure.
In fast-moving companies, rhythm is often the difference between speed and chaos.
These beliefs were not shaped in theory. They were forged in high-stakes moments where systems bent, and sometimes broke.
The role of objectivity
At AWS, I learned that even the strongest systems can stumble during high-traffic events. The causes were rarely dramatic. A missed autoscaling setting, skipped pre-warming, or incomplete load testing. Those moments shaped how I think about resilience: it is not about preventing every failure, but improving how you respond and adapt with each cycle.
Scale changes the rules. The larger a system grows, the less room there is for subjectivity. Clarity, structure, and objective decisions become the real leverage.
We saw this when we launched the AWS startup credits program. In the early days, everything was manual. We reviewed each application one by one, trying to consider every founder's context. It felt thoughtful, but it did not scale. Decisions varied, and fairness depended on who was reviewing.
So we moved to objective, rule based evaluation. Criteria were clear: funding stage (bootstrap, seed, series A), VC tier, and automated checks. No interpretation. No debate.
The impact was immediate. Decisions became faster, consistent, and easier to explain. Founders and partners everywhere could trust the same model, and the program scaled globally without more reviewers.
Objectivity removes friction. It makes fairness transparent and shifts energy from debating decisions to executing them. And at scale, execution usually fails not because the tools are weak, but because the tools do not talk to each other.
Tools do not build clarity, integration does
Tools make work easier, but too many of them make work invisible. The problem is not lack of technology; it is lack of integration.
The best systems are those that:
- Connect across data sources and functions
- Respect access controls and permissions
- Allow teams to complete work without manual copy-paste loops
Adding more software cannot fix fragmentation. What matters is how deeply tools talk to each other and how seamlessly they fit into daily workflows.
For example, a support escalation should automatically update the right product backlog and notify the account owner, without copy-paste. This foundation becomes even more critical now, as work moves from manual workflows to autonomous execution.
The rise of agentic systems
We are now entering a new era of agentic work, where AI agents perform operational tasks autonomously. Interfaces will become conversational. A single layer of engagement will abstract the underlying complexity of tools and silos.
This will make systems more intuitive but also more revealing.
AI will not fix chaos. It will amplify what already exists.
If your systems are weak, AI will magnify the cracks.If they are strong, AI will multiply your strength. Technology is a mirror, it reflects your discipline, not replaces it.
Building living systems at DevRev
With Computer, by DevRev, we don’t view systems as workflows to be managed. We see them as ecosystems that learn.
Our platform connects every customer conversation, product update, and business initiative into one continuous flow of context.
Instead of separate tools for projects, tickets, and customer feedback, everything converges into a shared graph, a living map of how the company operates and evolves. When something changes in one part of the system, the impact is visible everywhere else almost instantly.
This interconnectedness turns day-to-day operations into collective intelligence:
- A customer issue is not just resolved; it informs the next release.
- A product insight is not stored in a report; it becomes a decision trigger.
- A leadership review is not another meeting; it becomes a real-time pulse of what is working and what is not.
We have moved from documentation to discovery, from static reporting to self-learning systems that keep improving through use.
And that, to me, is the ultimate goal of scaling: not to grow bigger, but to build systems that stay alive. Systems that think, remember, and improve with every interaction.
The feedback loop that keeps systems young
Even the best systems decay without feedback.Customers and teams evolve constantly, and systems must evolve with them. As Bezos said, they are “divinely insatiable.”
At DevRev, feedback is not a formality; it is part of the system design. We use it to measure whether our processes are serving their purpose or adding friction.
Detect → Discuss → Decide → Document
- Detect: Monitor signals from customers and internal teams to identify pain points early.
- Discuss: Review patterns across departments to build shared understanding.
- Decide: Assign clear actions and owners to maintain accountability.
- Document: Share results transparently to create organizational learning.
The loop is not about volume of feedback but velocity of response.The faster you close the loop, the healthier your system becomes.
A system that listens stays young. A system that ignores feedback grows stale.
Closing reflection: building for the long run
Scalability is not headcount. It is how strong your systems remain when growth tests their limits.
AI will accelerate everything, including chaos. It cannot replace structure, but it can reward it.
Startups do not fail because they lack ambition. They fail because their systems cannot keep up. Build systems that can, and you build a company that lasts.
If you’re building not just a product but a living system, one that learns, listens, and lasts, talk to us.
