Member Spotlight: Raghava Dittakavi

What separates a good engineer from a great one when AI can generate a solution in seconds? For Raghava Dittakavi, it comes down to judgment, curiosity, and a willingness to learn from what breaks. This week, I sat down with Raghava to discuss the experiences that have shaped his approach to technology, his perspective on AI-assisted development, and the insights he hopes the next generation of engineers will carry forward.

1. What first got you interested in technology?

I have always been curious about how different parts of a system work together and how to use technology to solve real problems or create measurable value. Early in my career, that curiosity was mostly about understanding how systems/software worked. Over time, it expanded into how software, infrastructure, cloud platforms, automation, and engineering teams can work together effectively at scale.

What continues to keep me interested is how quickly technology evolves. Today, I am particularly interested in how AI is changing the way we build, operate, and improve software systems. I see AI as another important engineering capability, not a replacement for strong fundamentals, but something that can significantly amplify what good engineering teams are able to accomplish.

2. What’s a technical challenge or failure that taught you something you still apply to your work today?
One technical lesson that has stayed with me is that an issue found in staging cannot be dismissed simply because production is a different environment.

The question I ask is: “What evidence supports our conclusion about whether this issue could occur in production?” That means understanding the failure conditions and examining the relevant configuration, data patterns, load, and dependencies. If a difference between environments prevents the issue, we should be able to explain and demonstrate why.

The principle I carry forward is simple: uncertainty is not evidence of safety. Until we understand the cause and assess whether those conditions could exist in production, the risk remains unresolved.

3. As AI becomes a bigger part of how engineers work, what does good engineering judgment look like in an AI-assisted development environment?

For me, good engineering judgment means being able to defend a decision without saying, “The AI suggested it.”

As an experienced engineer, I want to understand the impact of every change I introduce: what behavior it alters, what else depends on it, and what new risks it creates. Even a small code change can have consequences beyond the immediate problem it solves.

AI can produce a convincing solution quickly, but I still need to question its assumptions and validate how it behaves when things go wrong. Passing tests is useful evidence, but I also need to know whether those tests cover the risks that matter.

My standard is straightforward: if I cannot explain the change, its potential impact, and the evidence supporting its safety, I am not ready to accept it. AI can help me move faster; accountability for the decision remains mine.

4. If you could only keep three tools in your developer toolkit, what would they be and why?

I would choose Git, CI/CD automation, and AI-assisted engineering tools. Git because understanding what changed, why it changed, and being able to collaborate safely around code is fundamental to software engineering.

CI/CD automation because engineering does not stop when code is committed. Building, testing, validating, deploying, and recovering software should be repeatable and automated. Good automation improves release velocity, reliability, and confidence.

AI-assisted engineering tools because they are becoming an important part of how engineers work. I find the biggest value is not just generating code. It is helping engineers understand large systems faster, troubleshoot issues, connect information across different sources, automate repetitive work, and move from an idea to a working solution more efficiently.

5. What role do you think experienced engineers should play in sharing their knowledge with the broader tech community?

I believe experienced engineers should share how they think, as well as what they know.

A tutorial can explain the steps to build something. Experience adds another layer: why you would choose that approach, what trade-offs you accept, and when you should reconsider it. Sharing that reasoning helps another engineer decide whether the same approach fits their own problem.

That is what I aim to bring to writing, mentoring, and technical discussions. I want someone to leave with a better way to evaluate a problem, rather than just another solution to copy.

We also need to be comfortable explaining where our understanding ends and what has changed our minds. Sharing experience responsibly means giving others enough context to question our conclusions and make their own informed decisions.

6. What advice would you give someone just getting started in your field?

Build strong fundamentals and stay curious. Learn how software actually works end-to-end: code, operating systems, networking, source control, infrastructure, cloud, testing, deployment, and monitoring. Individual tools will change, but understanding the underlying concepts will remain valuable.

More importantly, build things. Deploy them, most importantly, break them, troubleshoot them, and automate them. A lot of practical engineering knowledge comes from understanding why something failed and figuring out how to make it more reliable the next time.

I would also encourage engineers starting today to learn how to work effectively with AI. Use it to accelerate your learning and engineering work, but continue to understand and validate what is happening beneath the surface. AI is much more useful when it is combined with strong engineering judgment.

7. What’s your ideal way to spend a weekend?

My ideal weekend is a balance of family, community, learning, and creativity. I enjoy spending quality time with my family and being involved in community and spiritual activities. I also like setting aside some quiet time to listen, explore new technology, experiment with ideas, or write about lessons and perspectives.

Writing is something I enjoy because it helps me organize my own thinking while also sharing something useful with the broader technology community. For me, a great weekend is one where I can slow down, spend time with the people who matter, and still have some space to learn, think, and create.

Explore Raghava's content here.