Can Engineering Leaders Balance 3x Velocity with “Zero-Tolerance” Reliability? — Priyanka Mehta, DevRev

Based in Singapore, Priyanka Mehta leads a critical function at her current company that sits at the nexus of engineering velocity and customer sentiment. Her mandate is clear: ensure that as the company scales at the speed of AI, the infrastructure remains resilient enough to handle increasing demand. Priyanka is a successful engineering architect who has mastered the art of prevention-first engineering. 

However, she is the first to admit that no matter how robust your internal systems are, the most significant professional growth comes from stepping outside the office and engaging in the high-level strategic conversations that help benchmark your strategy against the industry’s best.

How do you define Performance, Reliability, and Experience in practice?

Priyanka explains why her role focuses on preventing failure patterns before they ever reach the end user. She advocates for a design-first approach to scalability that protects the customer experience.

“My role is closely tied to ensuring that systems are designed to scale from the beginning, rather than treating scalability as an afterthought. I’m deeply focused on preventing customer incidents by understanding patterns and identifying potential risks early. Even small production issues can negatively impact customer sentiment, so prevention is critical. At the same time, engineering teams are scaling rapidly with cloud and AI, so we need to move fast. However, speed must be balanced with stability. My team ensures that every change pushed to production meets a high standard through thorough validation.”

Why is Uptime a dangerous metric to rely on alone?

Addressing a major industry misconception, Priyanka highlights the difference between a system being “up” and a system performing well. She suggests that reliability leaders must look more deeply into the architecture to uncover hidden weaknesses.

“One major misconception is equating uptime with reliability. You might have high uptime, but if users experience latency or performance issues, the overall experience still suffers. Reliability must be considered holistically. Another mistake is thinking scaling can be addressed later. Many teams focus on building new features but don’t think about resilience from the start. These considerations should be part of the architecture stage. We need to be the ‘guardrail’, anticipating what could go wrong and simulating those scenarios.”

How does AI’s 3x Velocity impact engineering trust?

With development moving faster than ever, Priyanka discusses the need for intelligent agents to automate the validation process. She views AI as both a powerful enabler and a reason to double down on quality standards.

“AI has significantly increased engineering velocity, sometimes by three times or more. It’s a powerful enabler, but faster development must be balanced with quality and trust. That means automating test scenarios extensively and building intelligent agents for release validation. Quality is not a one-time effort. As we scale with AI, we must continuously monitor systems through predictability dashboards. We actively use AI to improve efficiency, but we also use it to strengthen how we enforce quality standards. AI is accelerating how we build, but also how we maintain reliability.”

What happens when you stop testing the Happy Path?

Priyanka shares a defining moment where a shift in mindset allowed her team to better understand complex user journeys. She believes that learning from others’ shared experiences is key to uncovering these types of strategic shifts.

“During a phase of rapid scaling, we were adding new features, but it became clear we needed to better understand failure modes. We had automation, but we weren’t fully validating critical user paths. This led us to ask: Are we truly understanding the customer journey? Can we reproduce incidents effectively? We moved from treating quality as a standalone activity to embedding it into system design. We began analysing vulnerable components and aligning more closely with customer expectations. I’m always open to connecting with other leaders to understand their strategies. There is a lot to learn from shared experiences.”

Is Zero Downtime a realistic goal for modern enterprises?

In a zero-tolerance market, Priyanka argues that speed of recovery is more important than the pursuit of perfection. She acknowledges that even senior leaders face the same ongoing pressure of customer expectations.

“Zero downtime is not fully realistic. There will always be situations where something goes wrong. What matters is how quickly and effectively you respond. You need to identify issues, reproduce them, and deploy solutions quickly so that systems are restored within a short time frame. Customers will increasingly have a zero-tolerance mindset toward poor experiences. They expect seamless integrations and minimal downtime. Any disruption affects their operations, so we must focus on speed of recovery and smart response rather than expecting perfection.”

What are the Critical Fundamentals for the next generation of engineers?

Despite the rise of AI, Priyanka believes that human judgment and architectural awareness remain the primary responsibilities of a leader. She challenges her peers to look closer at their own observability gaps.

“It is very important to have strong fundamentals. Even with AI, you need to understand what the code is doing. Beyond that, having a customer-centric mindset is essential. You need to think about how end users will experience the product. Passion also plays a key role. You should constantly ask why you are building something. I would ask other engineering leaders: Do you truly understand your architecture limits, and are you aware of your observability gaps? These are things that cannot simply be taught; they must be developed over time through experience and by benchmarking your strategy against others.”

Join the Conversation: The Ortus Club’s Executive Network

As Priyanka Mehta highlights, the role of a reliability leader is to be a “guardrail,” ensuring that innovation doesn’t come at the cost of customer trust. In an era of 3x engineering velocity, this requires constant architectural validation and high-level strategic exchange. At The Ortus Club, we host executive roundtables that provide the environment where leaders test, challenge, and refine their stability frameworks in real time.

Our events allow leaders to move beyond the “happy path” and engage in the deep, authoritative dialogues that define the next generation of resilient systems. Join our network to identify observability gaps with peers who are also reimagining engineering excellence through AI and automation.

Frequently Asked Questions

Q: What is Experience Engineering?

A: It is a technical discipline focused on the system’s performance, specifically through the lens of the end user, ensuring responsiveness and stability meet customer expectations.

Q: Why is observability different from monitoring?

A: Monitoring flags that a system is down; observability provides the deep data necessary to understand the “why” behind the failure, so it can be prevented in the future.

Q: What are Failure Modes?

A: These are the different ways a system can break. Priyanka advocates for simulating these scenarios early to build resilience before reaching production.

Q: How does AI affect engineering velocity?

A: AI can automate code generation and testing, increasing development speed by 3x or more, but it requires new “guardrails” to ensure that quality is not sacrificed for speed.

Q: Why do senior engineers attend executive roundtables?

A: Leaders like Priyanka attend these forums to benchmark their strategies against peers, exchange “war stories,” and discover architectural blind spots that are only visible through diverse perspectives.