As we look ahead to 2026, it’s clear that software delivery is changing in some interesting ways. We asked a few members of our software team what they’re most excited about, what they think is being underestimated, and to make one bold prediction for the year ahead. The answers span everything from AI and real-world systems to AR, IoT, and how technology fits into everyday life.
Here’s what’s on their radar 👇
Chloe: I’m excited about AI increasingly interfacing with the physical world through IoT, edge computing, and real-time systems. In 2026, the most interesting problems won’t be about generating content, but about optimising fleets, infrastructure, energy use, and industrial processes in real time. When AI decisions meet real-world constraints, the engineering challenge and the value goes up significantly.
Philip: RTK (Real Time Kinematic) replacing GPS for mainstream sports tracking equipment is something I’m excited to see develop as it gives cm precision rather than +/- 5m inaccuracies of GPS.
Hephzi: Agentic AI is shaping up to be a very interesting development that will change a lot of workflows in our day-to-day activity. In 2025, we saw how large language models have been integrated into daily life to help with planning, decision making and brainstorming. With the technology out there to expand upon this and to automate complex workflows, I’m very excited to see how it will be adopted and what’s going to stick.
Luke: In 2026, robotics is finally hitting its stride. For years the hardware lagged – robots were too heavy, too expensive, and too unsafe for real‑world jobs. That’s changed. We now have affordable, capable, and safe platforms ready to deploy, paired with astonishing progress in AI. This combination opens the door for small‑batch manufacturing, smart hospitality, and even creative new forms of automation. Some of it will look gimmicky at first, like any new wave of technology, but beneath that are massive new business and societal opportunities. The hardware has caught up, and now the imagination can take over.
Chloe: Indexing internal knowledge for AI. Most companies are trying to “add AI” without making their codebase and documentation machine-consumable. Clean structures, metadata, ownership, and searchable context are what turn LLMs from a demo into a reliable engineering tool.
Philip: Power harvesting technology for IoT devices to replace battery/plug-in power. Some of the types are Solar/PV harvesting can be used to generate power from light in environment, RF harvesting can be used to generate energy from typical radio signals within a building like Wi-Fi access points or mobile phones, and piezoelectric harvesting is getting energy produced from mechanical stress. Some sensors and chips use power harvesting to improve efficiency but not many are fully reliant e.g. would have a battery backup.
Hephzi: I think the potential for Augmented Reality integration with everyday life is being overlooked in favour of its flashier brother Virtual Reality. While VR is undoubtedly very cool, it has limited uses in daily life, especially due to its cost, and I think that people have picked up on that. Given it’s coming up on the 10th anniversary of Pokémon Go, I think it’s a great time to jump back on the AR train and see where it can take us.
Luke: The real sleeper story in tech is how much faster high‑quality software can be built with AI tools. We’re still underestimating this. Coding assistants aren’t just for speed, they’re reshaping what “senior‑level” productivity looks like. Yet many companies either chase the hype blindly or avoid it out of fear that it dilutes craftsmanship. The truth lies in between: engineers who learn to balance fundamentals with intelligent tooling will move dramatically faster and produce cleaner, more reliable code. The big unlock isn’t future tech, it’s learning to wield today’s AI tools well.
Chloe: In 2026, we’ll see systems that can monitor themselves, optimise performance, and suggest or implement changes – but the differentiator will be companies that pair these capabilities with solid architecture, security, and human oversight.
Philip: AI predictive packet loss features for gaming/streaming coming into play. Move to Cloud Gaming rather than using more expensive Gaming PCs.
Hephzi: 2025 saw many people trying to cut back on mobile phone screen time and the rise of “analogue-core”. My bold prediction for software in 2026 is that we’re going to see more development in screen-free ambient computing and single purpose electronics that integrate more seamlessly into people’s lives. With how so many households already use smart electronics that can interact with voice assistants like Alexa, I think that there is a lot of room for this to grow.
Luke: The next big challenge won’t just be about technology; it’ll be about talent. The best students and young engineers will master both the fundamentals of computer science and the latest AI productivity tools. But others will use AI as a crutch, appearing highly capable without truly understanding what’s happening under the hood. That will make recruitment harder. Companies will need new ways to tell genuine competence from clever imitation. As a result, the real talent pool for top software firms could shrink dramatically. For 2026, that’s the skill gap to watch.
Taken together, these views point to a year where progress feels more practical than flashy. Software in 2026 will be less about novelty and more about how well things actually work in the real world. The teams that do best will be the ones focused on solid foundations, thoughtful use of new tools, and building technology that fits naturally into everyday life. It’s an exciting space to be working in, and we’re looking forward to what the year brings!
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