The Best Seat in the House: A Graduate's View from Both Sides of the Product

Introduction

Hello, I’m Prerna, a software developer at Rimo. This Advent Calendar Day 21, I’ll be diving into how I blend product thinking with development and why I refuse to choose between building and owning the “why.”

As a graduate software engineer, I've landed what I consider the best seat in the house. I'm training to become a Product Manager while simultaneously working as a developer building new features. It's like watching a film while also seeing how it's made you appreciate both the story and the craft behind it.

This dual perspective has given me a unique view of where product development is today and where it's heading. I get to see the "why" behind features while also wrestling with the "how" of implementing them. And honestly? I think this intersection is exactly where the future of our industry lives.

What I'm Learning: The Present

One concept that surprised me was how interconnected everything is in product development. A feature isn't just a ticket to complete it's a node in a web of user needs, technical dependencies, business goals, and future roadmap considerations. When you change one thing, you need to understand its impact across the entire product. This is systems thinking in action, and getting it wrong means building something users don't need or breaking something they rely on.

The PM Fundamentals That Changed How I Think

What surprised me most is how much of PM work is about communication and alignment translating between users, developers, stakeholders, and business goals. It's not about having all the answers; it's about asking the right questions and connecting the dots.

What I'm Building - The Bridge

I experienced the interconnected nature of products first-hand recently. I was working on a feature involving permissions, and after I made changes to some functions, the requirements were updated. My manager then adjusted the entire flow how we'd handle permissions, what edge cases to consider, which other components would be affected. I watched him trace through the implications like it was second nature.

What amazed me wasn't just that he knew everything about that feature it was that he could see how one change ripples outward into dozens of little considerations I hadn't thought of. Things I might have forgotten, or only realized were important after something broke. He was thinking like a product manager and a developer simultaneously understanding both the "why" and the "how."

Working with AI - A Collaborative Loop

As a graduate developer, I work alongside AI tools like Claude daily. It's changed how I approach problems not by doing the work for me, but by accelerating the learning loop. I can explore approaches faster, get unstuck quicker, and focus more energy on understanding why something works rather than just getting it to compile.

When I was working on a new feature, I used Claude to help me understand the existing flow of the codebase how specific functions relate to each other and how data moves between different repositories. It was incredibly useful for getting up to speed quickly.

But the AI's first suggestions didn't account for important considerations: how the architecture should align with existing patterns, how to handle edge cases we'd already solved elsewhere, or how to structure things optimally according to our codebase conventions. It just created something entirely new that didn't fit with what we already had.

Recognizing that gap and knowing how to fix it is where my growing understanding of the product actually matters. I had to step back, study how similar features were built in our codebase, and then guide the conversation toward a solution that actually fit our architecture.

The skill isn't "being good at prompting" - it's knowing enough about the problem to guide the conversation and evaluate the output.

What's Coming - The Future

The trends shaping product development require people who understand both the domain AND the technology. Here's what I'm watching

1. AI as a Collaborative Partner [Not a Replacement]

AI is transforming how product teams work. According to recent industry reports, 76% of product leaders expect their investment in AI to grow significantly. But this isn't about replacing human judgment it's about augmenting it.

For Product Managers:

• AI-powered feedback analysis that synthesizes thousands of user comments into actionable insights

• Predictive analytics forecasting feature adoption before launch

• Automated user research synthesis turning hours of interviews into patterns

For Developers:

• AI pair programming that suggests code, explains existing systems, and catches bugs

• Automated documentation generation

• Intelligent code review and architectural suggestions

The catch? AI doesn't understand your product's context, your users' specific needs, or your company's strategic direction. That requires human judgment and ideally, someone who understands both the product and the technical implementation.

2. The Rise of the Full-Stack Product Person

There's a growing demand for product managers who can move seamlessly between strategy and execution. The traditional boundaries between PM and technical roles are blurring:

• PMs need enough technical fluency to have meaningful conversations with engineers

• Developers benefit from understanding user needs and business context

• The best products come from teams where everyone speaks both languages

This isn't about PMs learning to code or developers becoming business strategists it's about building bridges of understanding.

3. Data-Driven Everything

Product decisions are increasingly backed by data rather than intuition alone. This means:

• Real-time user behaviour monitoring informing feature development

• A/B testing as standard practice, not an exception

• Customer feedback integrated almost instantaneously into product cycles

For someone straddling PM and development, this is exciting I can understand both how to interpret the data (PM hat) and how to instrument systems to collect it properly (developer hat).

Why Both Paths Matter

This is what I learn every day being both a developer and a PM trainee. The user impact and the implementation keep me on edge whenever I make a change, I'm constantly thinking:

• What impact will this have on other functionalities?

• Am I breaking something?

• Does this still solve the user's actual problem, or have I drifted into over-engineering?

• How does this fit into where the product is heading?

The Dual Perspective Advantage

Some might say I should specialise pick PM or pick development. But I see them as complementary. Understanding the domain makes me a better developer. Understanding the code makes me a better product person. And honestly? I enjoy both. I like solving problems in code, but I also like understanding the bigger picture of how products evolve and serve users.

For Other Graduates: Skills to Develop Now

If you're early in your career and wondering whether to go deep or go broad, here's what I'd suggest:

Technical skills that translate:

• Understanding APIs and system design (helps you spec realistic features)

• Data literacy reading metrics, understanding what they mean

• Basic SQL or analytics tools (you'll need to answer your own questions)

PM skills that make you a better developer:

• User empathy - thinking about who uses what you build

• Prioritization frameworks - knowing what matters most

• Communication - explaining technical concepts to non-technical stakeholders

The meta-skill:

• Learning how to learn - because both fields evolve constantly

Conclusion

And somehow, even when I'm tired from the day and life feels strange in a foreign country far from home, I find a quiet amusement in it. There's something satisfying about untangling these puzzles, about slowly building the instinct to see connections that weren't obvious before. It's not always easy, but it's the kind of work that makes me feel like I'm actually growing.

The future of product development belongs to people who can bridge worlds who understand users deeply AND can build solutions elegantly. AI will handle more of the routine work, freeing us to focus on judgment, creativity, and connection.

For other graduates wondering whether to go deep or go broad - my answer is: why not both?