By Venkata Pavan Kumar Gummadi
It was late on a Friday evening in our Hartford, Connecticut office when the line on my screen finally turned green. A teammate had spent most of the afternoon reconciling code that two different developers working on opposite sides of the country had written almost simultaneously. Their changes overlapped, the system rejected the merge, and an artificial intelligence (AI) assistant had taken its best guess at fixing it. The guess was wrong. The bank’s nightly run would have failed. We caught it because a human looked twice.
That moment, repeated in some form across thousands of engineering teams every week, is the quiet story behind the AI revolution everyone is talking about. The headlines focus on what these tools can write. The reality, in the trenches, is what they leave behind: small mistakes, silently introduced, that engineers have to find and fix before the customer ever sees them.
I have spent the last 18 years building the digital plumbing that lets one big company’s systems talk to another’s. If you have ever paid a credit card bill, filed an insurance claim online, or checked an account balance on your phone, the chances are good that one of the integrations I or my teammates designed sits somewhere in the middle of that transaction. It is unglamorous work—the kind nobody notices until it breaks and I have come to love it precisely for that reason. When integration is done well, ordinary people get on with their lives without ever wondering how their money moved or their claim got processed.
I came to this country 12 years ago from Repalle, a small town in Guntur district of Andhra Pradesh. My parents are not engineers, but they invested everything they had in my education and quietly steered me toward information technology — a field they could see opening doors that had been closed to them. The sacrifices they made are sacrifices I am still trying to repay.
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My first job in the United States was deeply technical and not at all glamorous: extracting and transforming data from 40-year-old mainframe systems for a large American insurance company. I learned, on those projects, that the most interesting problems in software are almost never the ones the public reads about. They are quieter, the connections between systems that nobody owns, the messy edge cases that only show up at scale, the small acts of translation that turn data into something a person on the other end can actually use.
Over time, those edge cases became a calling. I moved into integration architecture, first at Cognizant, then at Deloitte and Appirio, and today I am an Integration Architect at Broadridge Financial Solutions, where my work helps move the financial information that millions of American investors rely on.
In 2025, the Institute of Electrical and Electronics Engineers (IEEE), the world’s largest professional engineering organization, elevated me to Senior Member, a grade given to roughly one in 10 members. It is a recognition I do not take lightly, in part because it came at a moment when our profession is changing faster than at any point in my career.
Which brings me back to that Friday night in Hartford — after watching teams burn weekends cleaning up after well-meaning AI assistants, I started building, in my own time, a small open-source project called ASCEND. It is a four-layer framework that sits between the AI tools developers love and the production systems they cannot afford to break. It catches the kind of mistake my teammate caught that night, not because it is smarter than the AI, but because it is patient enough to verify what the AI claims, before that claim becomes a problem someone else has to solve at three in the morning.
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I released ASCEND on GitHub a few months ago. Engineers from places I have never visited have started using it, opening issues, suggesting improvements. That is the part of America I find easiest to love: the assumption that a useful idea, even from a quiet immigrant engineer in Hartford, deserves a fair hearing if the code holds up. I did not grow up with that assumption. I am still learning to take it for granted.
I tell this story not because my path is unusual; there are thousands of Indian American engineers doing similar work. But because the public conversation about AI sometimes drowns out the slower, less dramatic work of making technology trustworthy. We will not be remembered for the prompts we write. We will be remembered for what we caught before it broke. That, more than anything, is the work I want to keep doing here.
(Venkata Pavan Kumar Gummadi is an Integration Architect at Broadridge Financial Solutions and a Senior Member of the IEEE. Based in Hartford, Connecticut, he has spent 18 years designing the integration platforms that connect America’s largest insurers, banks, and utilities. He is the author of the open-source ASCEND framework for AI-assisted DevSecOps and a peer reviewer for several international engineering journals.)