Aravind On Software

Most of the conversation about AI in engineering is about generation. Can it write the function? Can it write the test? Can it write the migration?

Monitoring tells you something broke. Observability tells you why. In engineering, we instrument systems to understand internal state.

Melvin Conway observed: Organizations design systems that mirror their communication structure.

A system can be reliable. It can be accountable. It can be well-architected. And still be slow.

In engineering, accountability is not a meeting. It is not a reminder. It is not escalation. It is not supervision. It is architecture.

Why control does not scale in leadership—and how outcome-driven system design enables autonomy, reliability, and ownership in teams.

A systems-thinking approach to leadership, where people are designed for outcomes, not controlled by processes.

After more than 17+ years leading software, platform, and engineering teams, one leadership principle has consistently separated high-performing organizations from the rest: Leadership is ultimately measured by what gets done....

Early in my career, I worked on a system that offered users multiple ways to view the same data—grid views, list views, filters everywhere. On paper, it looked powerful.

After spending more than a decade working across different flavours of agile teams, one pattern has remained consistent.

Measurement is the first step toward improvement—but only if you’re measuring the right things.

Conflict is inevitable in any organization. The absence of conflict usually signals disengagement—not harmony.

When you are part of an engineering transformation or platform modernization effort, certain debates surface again and again.

In mature engineering organizations, test coverage eventually stops being a meaningful signal.

If you search for Functional Programming vs Object-Oriented Programming, you’ll find no shortage of opinions, frameworks, and dogma. Most comparisons focus on syntax, tooling, or academic purity. Very few address...

Scalability is one of the most misunderstood concepts in software engineering.

In my previous discussion on Building applications with high availability, I outlined the technical pillars required to sustain resilient systems. However, resilience cannot be improved if it is not accurately...

High availability is often reduced to a number.

In organizations that genuinely improve, feedback isn’t episodic—it’s institutionalized.

In high-velocity engineering ecosystems, we often identify recurring patterns within the complex problems we solve daily. As a leader, it is critical to formulate and document these solutions so they...

When we model complex domains in an Agile ecosystem, the initial brainstorming of entities, communication patterns, and behaviors is a critical juncture. However, without a structured approach, collaborating with diverse...

In the era of Web 2.0 and beyond, the architecture of an application is often defined by its reach. However, a critical question frequently arises during the design phase: Why...

There is a well-known joke in our industry: