App development in 2026: how teams could evolve

AI-native development platforms use generative AI to create software faster and easier than was previously possible. Software engineers embedded in the business, acting as “forward-deployed engineers,” can use these platforms to work together with domain experts to develop applications, Gartner predicted.

Restructured teams

Organisations can have tiny teams of people paired with AI to create more applications with the same level of developers they have today, Gartner said. Each tiny team would allow non-technical domain experts to produce software themselves, with security and governance guardrails in place. The consultancy predicts that by 2030, AI-native development platforms will result in 80% of organisations evolving large software engineering teams into smaller, more nimble teams augmented by AI. 

Source: Dataiku.
Douetteau.

New roles

Florian Douetteau, Co-founder and CEO at Dataiku, suggested that a new role will appear in 2026, that of AI Domain Architect. AI Domain Architects will emerge as the real builders of enterprise AI, Douetteau said. 

"These employees, armed with deep business knowledge and just enough technical fluency, will design and supervise the agentic systems that finally move companies beyond pilots and into true operational AI," he said. 

Revamped responsibilities

The next generation of developers will act more like conductors guiding fast-moving teams, predicted Steve Yen, Co-Founder, Couchbase. 

"The day-to-day work of a developer is shifting. Developers who want to stay ahead will use AI the way a head chef runs a busy kitchen, directing parallel tasks, comparing multiple options, deciding what’s worth keeping and pushing work forward quickly. The real skill is orchestration, not trying to personally hand-craft every line of code. That shift will help teams ship faster and stay relevant," Yen said. 

"The biggest advantage will come from understanding the higher levels of the system: how data flows, how subsystems behave under load and how to keep the bigger picture in focus across an increasingly distributed world that spans edge and cloud. Developer data platforms that support quick iteration, flexible data models and reliable edge-to-cloud performance will give teams what they need to supervise and collaborate with AI so they can move faster than the competition." 

"AI is reshaping the software development lifecycle across industries, shifting from writing code to expressing intent. After years of automation and DevOps-driven acceleration, AI is increasingly generating and maintaining software parts. From now on, developers will specify outcomes while AI generates and maintains components, shortening delivery cycles, and improving quality," noted Pascal Brier, Chief Innovation Officer at Capgemini and Member of the Group Executive Committee.

"But governance and oversight remain critical to prevent hallucinations, security gaps, and silent errors. This new era of 'Rebuilding software' across the full value chain aligns with becoming an AI-native business, operating on adaptive platforms rather than static ones," Brier added. 

"This approach opens opportunities to build more adaptive, sovereign systems, reduce reliance on software-as-a-service provider, and enable differentiation through tailored products at competitive price points." 

Raymond Kok, CEO, Mendix, painted a future where developers "transition entirely to model orchestration and high-level knowledge work, where humans express their intent and expertise through abstract models rather than explicit code". "Since AI agents will handle the heavy lifting when it comes to building – including potentially generating raw assembly code – the human role becomes centred on the plan to build," he said.

"Specifically, that will be ensuring the problem is correctly scoped and defined. As a result, the low-level code output becomes irrelevant, placing all value on the strategic modeling and planning phase."

Supporting infrastructure 

Yen also agreed with Gartner, saying that AI will push development cycles from months to days, and data platforms will need to keep up. "AI is going to speed up the way software ships. Business teams can already spin up prototypes or new features without waiting on developers, and that pace will only increase," he said.

"Work that used to take months may compress into days or even hours when AI produces the first draft. Developers become reviewers and coordinators rather than being the sole point of execution.

"That speed puts real pressure on the data layer. Schemas will change constantly. New fields and new collections will appear overnight. Applications will grow and shift in ways older systems weren’t built to absorb."

These changes mean that IT teams will need data platforms that can handle rapid iteration, fast rollback and constant updates without putting production at risk," Yen predicted.

"JSON-first databases with high ingest rates, support for quick structural changes and reliable edge sync will match the pace of AI-driven development. Systems tied to rigid structures will fall behind as soon as the cycle accelerates," he said.

Replacing jobs?

In his blog All Things Distributed Dr Werner Vogels, CTO, Amazon, addressed the elephant in the room. He believes that AI that can code will not replace software developers.

"Time and time again we have seen that lowering the barrier for entry doesn’t eliminate the need for human expertise, it amplifies it. Generative AI lets us generate code in seconds, but if you put garbage in, you get really convincing garbage out," he noted.

Humans will be needed when decisions need to be made about cost optimisation versus performance, or that the prioritisation should be for 24 x 7 customer service and not an always-up internal reporting dashboard during peak sales periods, he said.

"The politics, the constraints, the unspoken priorities that shape every technical decision are nuanced and require a developer who understands why it matters to the humans who pay for it and the humans that will use it," he observed.

Dr Vogels likened coding today to bringing together art, science, and engineering, just as was required during the Renaissance age. Renaissance developers, he said, must "understand that systems are living, dynamic environments where changes ripple through services, APIs, databases, infrastructure, and people".

"They communicate with clarity that both humans and machines can build from. They own the quality, safety, and intent of what they create, especially as AI grows more confident in its errors. They bring domain knowledge that AI cannot replicate, such as understanding the business, the customer, and the real-world constraints that matter. They never stop learning," he predicted.

"The fundamentals that have always made great developers remain unchanged. But like the great thinkers of the Renaissance who refused to be confined to a single discipline, developers can no longer live in silos.

"You must think bigger, the moment demands it. This is the dawn of a new age for developers. You have never been more valuable. Your creativity has never been needed more," he said.

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