The Engineering Principles That Still Matter (Even With AI)
Software engineering is changing fast. New tools, new platforms, and now AI is reshaping how we build. But even with all that change, there are core engineering principles that still matter.
Just because the tools evolve doesn’t mean the fundamentals change. At the center of these fundamentals is something we don’t talk about enough: the human side of software engineering.
Despite the stereotypes, software engineering isn’t just sitting behind a screen writing code. It’s about problem-solving. It’s about creativity. It’s about figuring out how to get from where you are to where you need to be. And most importantly, it’s about collaboration; not only with product teams and stakeholders, but internally with other engineers as you work through complex problems together.
As we move into this new season of AI, here are a few principles we believe are more important than ever to keep top of mind.
Collaboration: Pairing and Mobbing
One of the strongest ways we practice collaboration is through pairing and mobbing, two techniques that bring engineers together to work on the same problem at the same time.
- Pairing typically involves two developers: one acting as the “driver” who writes the code, and the other as the “navigator” who reviews, asks questions, and thinks ahead.
- Mobbing takes this even further by having the entire team work together on one task, rotating the driver's role and sharing context in real time.
This becomes even more critical as engineers start working with agentic AI. Engineers are being handed large volumes of generated code, and that can be exhausting to review alone. Working together makes it easier to catch issues, share understanding, and avoid blind spots. Our CEO and Co-Founder, Jeremy Duvall, recently shared more about this on LinkedIn and it’s a conversation we think every engineering team should be having.
Mentorship Still Matters
Another core principle is mentorship. Having someone to guide you is valuable at every stage of your career, but it’s important for junior engineers. Many junior engineers are jumping headfirst into AI-driven workflows, while some senior engineers may take longer to adapt or remain more skeptical and that’s okay, having a balance of both is healthy. The important part is learning from each other. Strong mentorship creates space for knowledge sharing in both directions. It builds confidence, accelerates growth, and strengthens teams over time.
Testing Is Non-Negotiable
This is something we constantly preach at 7Factor: testing matters.
Testing isn’t just about catching bugs. It’s about maintaining healthy skepticism of assumptions. It’s about understanding where things can fail, recognizing common mistakes, knowing how to verify what you believe to be true, and being honest about what you don’t yet know. This mindset is deeply embedded in how we work, and it’s not going away anytime soon.
Critical Thinking in an AI World
The final principle might sound basic, but it’s anything but: critical thinking.
Even as AI generates more code, engineers still need to understand what they are designing and why. They need to know how systems should behave, how to validate outcomes, and how to spot when something doesn’t feel right.
This also includes curiosity (one of our core 7 Factors) asking “why,” challenging assumptions, and not always agreeing just because something looks good on the surface. Different perspectives make products stronger. It’s one of the reasons companies work with consulting partners like us: to bring fresh thinking and outside viewpoints into the room. Critical thinking also means fully understanding the business goals behind what you’re building. Not just how something works, but why it exists and what outcome it’s meant to create.
Back to the Basics
At the end of the day, none of these ideas are new. They’re fundamentals. But sometimes the best way to move forward is to revisit the basics.
As technology continues to evolve, keeping these human-centered engineering principles, top of mind will help teams build better software, work better together, and adapt more confidently to whatever comes next.