Who is a software engineer in 2026?

01.06.2026

For five years, //kood has been training people to become software engineers. Every couple of years, we update our core-curriculum to adapt to the shifts of the role, this is our third major update.

Before designing anything, we spent months on a single question: who is a software engineer today, and where is the role heading? This post is what we found, and what we changed because of it.

Feedback and insights from recruiters, engineering managers and alumni

We talked to senior engineers and engineering managers about where the field is going and what separates junior hires who grow vs ones who don’t. We spoke with technical recruiters about what the market expectations are, who gets selected and why. We sat with our alumni and asked them, honestly, what the programme prepared them for and where it left them exposed.

Alongside all of that, we pressure-tested what we were hearing against broader market data across the regions, to make sure the patterns we saw inside our network actually held up outside it.

AI raised the bar beyond technical skill toward judgement, communication and ownership

Starting with AI – building simple things is easier and more accessible to people without much technical background. What’s gotten harder is shipping anything non-trivial without understanding what’s in front of you. Companies have become more careful about who they trust with complex systems, and the question they ask about a junior hire shifted from “can this person build” to “can this person contribute.”

AI implementation policies vary by company. Some are leaning heavily and are AI-native by default. Others are more conservative by the nature of their organisation and are piloting cautiously. Regardless of variation, one message was consistent: engineers who don’t use AI will become obsolete, and engineers who over-rely on it will get outcompeted by the ones who use it with judgment.

Underneath that, the role itself is moving from working through tickets to evaluating decisions against the needs of the product and the people using it. Technical skills still get candidates through the door. What gets evaluated once they’re in is the professional layer – how they think, whether they can frame a question that’s worth asking, whether they take ownership of what they ship.

Updated curriculum in three layers: technical skills and product thinking, professional posture and AI literacy

The technical part was the simplest call. Our alumni are strong builders and generally outperform in entry-level roles by being able to ship bigger systems faster than their peers. We kept the strength of that, and broadened the range slightly to match what’s expected of a software engineer today.

Product thinking went through a similar shift, students are already building real products for real users with real stakes. What we added is the layer of why, for whom, and how do we know it actually works.

The professional layer was harder. Self-paced peer-learning naturally requires professional posture through peer reviews, project ownership, working through confusion without a teacher to lean on. That generally works for students who arrived with transferable habits from previous careers but isn’t as reliable for first-career students, who often hadn’t been exposed to those habits in a structured way. In this version we’ve made it more explicit. It’s still practiced in context, but we name what’s happening and why it matters, rather than leaving it for students to absorb on their own.

AI has been a focus point for us for a long time, and we’ve put a lot of effort into figuring out what was passing hype and what was real. In //kood’s curriculum, in addition to building AI-native products, AI is introduced as a professional tool in a day-to-day technical workflow, and as a skill in itself – knowing how to use it responsibly and with precision, and when to leave it alone.

Preparing students for real-world engineering teams

By the end of the core-curriculum, students are what we’ve been calling impact-ready product engineers. They can walk into a professional environment and start contributing because they’ve already been working in one – shipping real systems in teams, making decisions about how to build them, defending those decisions in reviews, giving and receiving feedback, using AI as part of how they work rather than a shortcut around it.

The landscape will keep moving and our programme will continue evolving with it.

Viktor, Curriculum lead @ //kood