Share:
Share:
Reaching out to industry leaders can feel daunting especially when you’re just starting out. That’s why Open Avenues created the Coffee Chat Series to break down those barriers and bring real-world advice directly to students and emerging professionals from those working at the forefront of their industries.
We’re excited to feature Shritesh Bhattarai, a Build Fellow at Open Avenues & Principal Software Engineer at Remix Labs, where he works on programming platforms and tooling. He develops AI-powered tools designed to support and accelerate the work of fellow developers. With a background in both large-scale systems and cutting-edge AI integration.
In this Coffee Chat, Shritesh shares how artificial intelligence is reshaping the role of software engineers. He talks about how tools like pre-large language models (LLMs) are changing the way developers design, code and collaborate and why junior engineers shouldn’t fear these changes but instead learn to harness them. From using AI to rapidly learn new domains to improving code quality, to making the most of small agile teams.
Curious about how AI is shaping the future of software development? In this article, Shritesh shares practical insights for students eager to grow in this industry.
A: Software engineers that have embraced AI tools are more productive at solving problems and can tackle highly ambitious problems.
The unit of work that a software engineer can produce is much higher than in the pre-Large Language Model (LLM) days. LLMs are already good at generating code, but software engineering also involves design, architecture, implementation, testing, review, etc. These tasks usually are collaborative in nature and having an AI on the side that helps you with these tasks lets you move much faster with a smaller team.
Similarly, many problems in the past required having access to a domain expert or becoming one yourself. The time and resources necessary to research and learn a new domain have shrunk with access to the latest AI models. I am currently working on a side project where I process satellite imagery data and generate insights from it, even though I have never taken any formal courses or read books on the topic. I did not know where to start, but I just started asking questions. The beauty of learning with LLMs is that you get answers tailored to your needs.
For example, I was working on map data with different Coordinate Reference Systems (CRS). I scoured the web on the topic and got a generic idea of what they were but when I asked the question to the LLM, I could follow up with the exact CRS’ that I was working with and tradeoffs we have to make when switching between them and recommendations on how to store them in the database. It is like having an expert co-worker patiently helping you all the time.
A: I would not say they are at risk, but the shape and sizes of software engineering teams are changing. I am aware that new grad roles are getting much more competitive. As we come to terms with this new world, expectations for junior developers will probably change as well. I have seen many startups require familiarity with AI coding tools as a job requirement.
A: Embrace AI. It’s here to stay. Consider them to be tools to aid you in software development and make you a faster and better software engineer. Keep a learning mindset. Incorporate tools like GitHub Copilot or Claude Code for your day-to-day coding tasks. Ask it to review your code, generate ideas and implement features.
A: Communication and writing skills have become critical with LLMs. We have seen that when it comes to code generation, LLMs are as good as the context and the prompt you provide. Learn prompt engineering. LLMs are not perfect, and your prompt needs to help the AI succeed at the task.
Also, the field of AI is moving extremely fast. It is too much to keep up, but I’d recommend surveying the field every month at a minimum.
A: Don’t be afraid to put your work out there. Put your side projects publicly on GitHub, talk about it on local meetups and share it on Twitter/X. For example, if you’re doing a Build Project with Open Avenues, you should showcase your deliverables on LinkedIn. Sharing the things I’m working on with people on the internet has been the most important career accelerant for me. Someone will notice you and find the work that you produce to be useful, and possibly even collaborate with you or hand you a job offer.
Similarly, contributing to open-source software gives you the opportunity to work on high-value things and contribute to the commons. Whether it’s a simple clarification in the documentation that you read, or a fix to a bug that you encounter, submitting pull requests and working with the maintainers of the projects gives you the exact experience of working in a professional software team. I wish I had made a habit of doing so sooner.
Final Thoughts:
As the Coffee chat wraps up, there is a lot to take away from Shritesh’s experience. His insights highlight that AI isn’t replacing software engineers, it’s redefining what’s possible for them. By embracing tools like GitHub Copilot and learning how to prompt, developers can increase their productivity and tackle challenges that once required years of domain expertise. Shritesh’s own journey from experimenting with satellite imagery to managing complex code architectures demonstrates the power of staying curious and leveraging AI as a collaborative partner.
For students and early-career professionals, his advice is clear: build publicly, contribute to open-source projects and showcase your creations. The engineers of tomorrow won’t just be coders they’ll be learners, creators, and collaborators working alongside intelligent tools. In a rapidly changing field, adaptability and willingness to explore unfamiliar territory can be your greatest asset.
Let Shritesh’s experience be a roadmap, ask questions, experiment boldly and share what you build. That’s how you grow and get noticed in the AI-powered future of tech.
Danila Blanco Travnicek is the Director of Program Strategy & Evaluation at The Build Fellowship where she leads the education programming and its initiatives. She is a social entrepreneur who has been working tirelessly for over 10 years in the nonprofit sector to ensure more people have access to quality education. Danila holds a B.A in Business Management and a master's degree in Teaching and Nonprofit Management. She is a Professor at the University of Buenos Aires, an international speaker and facilitator and has managed and led programs with social impact in Latin America, U.S., Europe and Asia. She also received scholarships to study abroad in Finland, China and the United States.
Mazvita Maboreke is a Human Resources Analyst at Open Avenues Foundation. In her role, she leads initiatives that foster team development, professional growth, and a positive organizational culture. She focuses on designing and implementing programs around training, onboarding, team-building, and employee recognition—helping to cultivate a workplace that is both supportive and high-performing.
Stay updated on all things Open Avenues!
