Experts from IAS and Rent the Runway explore the impact AI has had on corporate R&D.
By its very nature, research and development (R&D) is an ever-changing field and with that change comes changes in both the workplace and professional expectations.
To Mark Walsh, director of engineering at Rent the RunwayTechnological advances in R&D are among the most influential trends changing the landscape of research professionals.
He told SiliconRepublic.com, “I dare say, the most exciting, dynamic and uncertain trend is undoubtedly the rapid evolution of AI. I use all three of those words deliberately, because I think that anyone who tells you that it is exciting without acknowledging the evolution and uncertainty is not fully honest.
“The pace of change is unlike anything I’ve seen in my entire career and the scope of what’s changing – from the way we write and review code, to the way we think about system design and even team structure – means there’s almost nothing in the R&D space that’s not affected by it right now. That’s really exciting, even when it’s really disruptive.”
Alexander Smirnov, staff software engineer in IASshared Walsh’s opinion that it is impossible to explore the topic of 2026’s critical trends in R&D without talking about the elephant in the room, AI.
“We have seen a huge increase in AI capabilities and the rapid pace of competition is amazing, vendors are releasing frontier models every few months. Developers write less code now, they rely more on coding agents every day. And it’s not just coding – they also help during the design, testing and planning phases,” said Smirnov.
“Navigating legacy bases has never been easier; you can start a new project very quickly. Asking questions in plain English about the codebase and getting almost instant, context-aware results feels like an amazing experience.”
Fast movement
With that in mind, how have R&D teams evolved to meet the needs of the industry on a daily basis?
Walsh said, “First of all, we are not at the end of that flexibility. I would say that we are constantly adapting and at a much faster pace than I have seen at any time before. What seems to be in practice is a culture of continuous discovery rather than waiting for the environment to resolve before making decisions, because it will not resolve.
“Teams need to be comfortable working with some degree of uncertainty, rigorously testing new approaches, making thoughtful decisions and being willing to revisit those decisions as the situation changes.”
Smirnov finds that many teams implement new workflows and embed LLMs or agent workflows more during development and operational support.
He said, “It’s a great tool, but we still need to learn how to use it effectively, break old habits and develop new skills.
He also explained that having time to self-study, testing new tools, exploring novel workflows, and even just thinking about what could be done differently with new tools are all good ways to improve skills,
He noted the IAS ‘practice’ group for Slack, where developers share their ideas, exchange custom agent capabilities and deployment tool updates, adding that, “it helps us better understand the ecosystem and its capabilities”.
Make it count
Walsh also offered a word of advice to new professionals in the space. He explained that it can be tempting to jump into the tech world and embrace any technology as it comes along, but you can’t forget how and why you were chosen for your role in the first place.
He said, “I believe we are still engineers and knowledge workers first and foremost. Our most important asset is our judgment, the ability to think critically and generate new ideas. In a world that is moving as fast as I see it, I believe that the foundation is becoming more important, not less.
“The tools around you can change and have been changing, however, the thinking you bring to how you use them is what endures. The temptation right now is to rush to use the next great tool or method, but the fundamentals that make one successful in this space remain the same: the ability to dissect a complex problem, to live in uncertainty without getting caught up in simple technical details.”
He advised experts to avoid being confused by the things that are used when they think deeply, because the ones who will succeed are the ones who understand why they reach a certain method, not how it is used.
Walsh said, “Curiosity and tenacity together is a combination that I believe will help anyone regardless of what the future looks like.”
This was echoed by Smirnov, who said, “What doesn’t change is human judgment. While agents can execute code in seconds, developers must understand exactly how that code works under the hood.
“LLMs generate output based on the prediction of possible tokens from their training data; they don’t actually think like humans do, but instead use ‘internet averaging’.”
For both experts, while AI has undoubtedly revolutionized R&D, what hasn’t changed is the importance of sticking to the basics. In particular, to think differently, critically and independently of technology.
Smirnov said, “Understanding how to use new tools effectively is no longer optional. The future belongs to those who combine strong fundamentals of computer science with the ability to direct, evaluate and collaborate with intelligent agents.”
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