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Northwestern University

The Rise of Product Engineers

Adjunct professor John Renaldi goes behind the scenes of his new course and explains what excites him so much about AI and its potential to revolutionize the product manager role.

Sep 4, 2026

By John Renaldi, adjunct professor

I've spent my career in product development, and what AI is doing is fundamentally shifting the traditional roles previously required to create a product.

Role boundaries are collapsing. Designers, product managers, and engineers are moving toward each other, and AI tools are accelerating the convergence.

I see this with my client teams. The lines are not blurring in theory, but blurring in the actual work. And to be honest, it's creating some friction.

UX designers on these teams are shipping working prototypes in production code. They are not handing static mockups to engineers and waiting. They build the thing, make product decisions as they go, and put something runnable in front of users (although to be fair, without the proper agentic infrastructure, many companies that generate these prototypes are far from production ready - more on this later).

Engineers are moving the other way. They deploy a new feature, get it working end to end, and then hand it to the UX team to tune the interface. The handoff did not disappear. It reversed direction and got shorter. The person closest to the problem builds first, and the specialist refines second.

Today, anyone actively shaping the product and tackling the product risks is a product creator. With the rise of generative AI-based tools, strong designers and engineers are starting to play this role. This represents a fundamental shift.

Creating a product has never been easier. Designers no longer need to hand off static mockups to engineers. Instead, they use AI to prototype in production code, make product decisions in real-time, and understand the systems for which they design.

For an engineer, it's not enough now to be able to know how to build something. The way to stand out is to know why you're building something. Engineers who understand customer problems, market dynamics, and business models are worth more than those who only execute specs.

These realities have pushed one role into the mainstream: the product engineer. While the title is not new, what has changed is the accessibility. AI has made the role reachable for far more people.

The software product engineer sits at the intersection of design, product, and engineering. They talk directly with customers, analyze usage data, decide which problems are worth solving, and then build the solution themselves. No handoffs or waiting for specs.

The same person who understands the user problem writes the code to solve it.

This runs on shared context

None of this works without infrastructure. The reason a designer can ship near production code, and an engineer can produce on-brand UI, is that each discipline's rules now live in a place the AI can read.

Put the design system into the agentic engineering workflow and engineers get UI that is on brand by default. The components, tokens, and design rules are in the context the agent works from, so the output follows them without a designer checking every screen.

Point the same setup the other way and designers can ship near production code. Give them an agentic coding environment with the right context files and rules, the conventions and guardrails engineers already rely on, and their output holds up in the codebase.

The convergence is not only about people getting more skilled. The tooling now encodes each side's rules so the other side can work safely inside them. Shared context is what makes the handoff short enough to feel like it disappeared.

The product engineer role

Product engineers combine technical fluency with product judgment, user empathy, and business context—all of the things we teach in Northwestern's MBA + MS Design Innovation (MMM) program. MMM is a dual-degree program between Northwestern Engineering and the Kellogg School of Management.

In my classes, I demonstrate how AI can be a powerful accelerant for front‑end discovery and a crucial tool for automating execution. I explore how AI can elevate product development from various angles.

AI is lowering the barriers to achieving high‑level performance. Previously, exceptional performance was primarily limited to a select group of product managers who were design‑savvy, product‑strong, and code‑capable. Now, many more individuals can perform tasks that once required this elite skillset, bridging gaps in areas like prototyping and synthesis 

I'm excited to touch on these and other topics in my new AI as a Force Multiplier for Product Leaders course in the MMM program.

It is important for students to understand that AI lowers barriers but does not eliminate the need for human judgment. Teaching students to use AI well means teaching them to evaluate, validate, and own the outputs, knowing both the capabilities and the limitations.

In a recent conversation, MMM director Greg Holderfield put the need for this new course best. 

“The MMM program lives at the intersection of design, technology, and business, and AI is quickly becoming the connective tissue across all three. For our students, this course is essential. AI is reshaping what it means to lead as a product innovator,” Holderfield said. “At MMM, we prepare leaders who think systemically, create boldly, and execute with discipline. AI strengthens those capabilities. AI does not replace the MMM leader. It elevates them.” 

John Renaldi is the former head of product and design at Google for Wear OS. Prior to Google, John served as co-founder and CEO of Jiobit, which was acquired by Life360. In addition to the MMM program, John teaches product innovation and entrepreneurship in Northwestern Engineering's Master of Product Design and Development Management (mpd2) program.

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