DeveloperXperience Summit 2025: Empowering Innovators in the AI Era

The role of developers is being reshaped in this new age of AI. Technologists need to master core skills and shape secure, innovative solutions beyond coding. Learn why Singapore is a rising hub for AI innovation at DeveloperXperience Summit 2025.

Chairperson Andrey Adamovich aptly summed up his message for the second annual DeveloperXperience Summit that was hosted in Singapore on 27 May. The true role of the modern developer is not defined by the fastest typing. In this new age of AI, automation, and complex distributed systems, developers are now central to innovation strategy, enterprise transformation, and technological ethics.

Organised by the Infocomm Media Development Authority (IMDA) and Informa, this year’s Summit brought together more than 200 leading technologists, platform architects, and enterprise decision-makers to uncover how the developer experience is transforming and why it matters.

A consensus was reached across panels: AI is now a priority, open-source demands discretion, and the role of the developer is becoming more strategic, cross-disciplinary, and irreplaceable.

Here are seven takeaways that are reshaping the developer experience, and the digital landscape.

1. Developers aren’t being replaced: They’re advancing with AI

As AI takes over basic coding tasks, developers are not being replaced, they're being empowered. “You become a supercharged human being with AI,” said Robin Fong, Managing Director, Asia at Redis. “You have to learn it, or you'll be left behind. Or alternatively, you can adapt, and you can dominate.”

Rather than eliminating roles, AI can help push developers toward higher-impact work such as system architecture, ethical oversight, and strategic integration.

The rise of AI does not merely improve workflows but also redefines the value developers bring to the table. “We are moving towards an AI-centric future,” said Kannan Muthukkaruppan, Co-Founder and CEO of Yugabyte. “As a founder, I’m focused on how to leverage AI so every part of the organisation, whether engineering or marketing, becomes more efficient.”

To stay ahead of the curve, developers must be able to blend technical expertise with broader organisational strategy.

2. Core skills remain crucial in an AI-powered tech landscape

While AI continues to be the talk of the town, it is not the solution to every problem. Core infrastructure and fundamentals remain essential. Philip Rathle, CTO of Neo4jcautioned, “It doesn’t make sense to use a really expensive and slow, approximate answer generation engine when we already have technologies that give fast, exact answers.”

Andrew Sellers, Head of Technology Strategy at Confluent, underscored that reliable AI starts with disciplined data practices, not just smart algorithms. “If data isn’t trustworthy and contextualised, every team downstream has to rebuild understanding from scratch,” he explained. “It’s not just about moving data, it’s about making it reusable, discoverable, and meaningful.”

3. Open source is an investment, not a free resource

Heavy investment is needed to use and maintain open source at scale. “Make a mistake or break an implied promise, and the consequences can be severe,” warned Saju Pillai, Senior VP of Engineering at Kong.

Shubham Agnihotri, Chief Manager - Generative AI from IDFC First Bank, contextualised this from a banking perspective: “Security, compliance, and model validation add substantial effort on the consuming side.” Harpreet Singh, CTO of Watermelon Software, highlighted the hidden risks: “If you’re not on top of your open-source game, it can get very, very expensive.”

Meanwhile, Sunny Bains, Chief Architect at PingCap explained why firms turn to open source in the first place: “They don’t want to be beholden to a vendor’s release cycle, they want to fix it themselves.”

The panel concluded: using open source wisely requires governance, process, and foresight, not just code.

4. Developers must adopt the mindset of architects and risks managers

Writing code is no longer enough, developers must now tackle licensing pitfalls, ensure compliance, and design for the long-term. Harpreet Singh recounted how “licensing changed overnight” on a key library, forcing his team to rebuild quickly to avoid downstream risk.

For Saju Pillai, open source is more than code, but accountability: “When you build on open source, you inherit its responsibilities. You need processes to vet, pin, and approve every component.”

Shubham Agnihotri brought to attention the stakes in regulated industries: “Even open libraries must pass rigorous internal review. Vulnerabilities or licensing gaps can stop production.”

Sunny Bains pointed to foundation-backed governance as a safeguard: “We donated our project to CNCF [Cloud Native Computing Foundation] … it’s managed by them, which means we cannot change the licensing anymore and it reassures our customers.”

Whether vetting dependencies or preparing for audits, today’s developers now take on new tasks traditionally led by legal and systems teams.

5. AI’s is only effective with security and accountability

Building with AI means rethinking the entire pipeline, from data ingestion to endpoint exposure. “Now’s the time to get your APIs in order,” urged Rachna Kawasra, VP of Operations at TYK Technologies. “Managing them securely is critical to scaling AI responsibly. Data can leak from connectors before the AI model even sees it.”

Anuj Jaiswal, Chief Product Officer at Fortanix emphasised the stakes in regulated sectors: “We’ve seen a great deal of experimentation with generative AI, and it’s clear that it can be transformative. But challenges remain, particularly around data security, privacy, and compliance. Enterprises must ensure data is protected at rest, in motion, and in use.”

Developers are crucial in securing the AI pipeline as well. Paul Gray, Vice President Sales, Asia & Pacific region, Delphix by Perforce Software cautioned, “If you're using tools like Copilot to build software faster, you also need to ask: what are you using to test that code before it hits production? Speed without validation just introduces risk. The responsibility for secure, reliable code doesn’t go away, it just shifts left.”

On their end, clients also have their reservations. “The first question we get is: what happens to our data?” said Honey Mittal, Co-founder & CEO of Locofy.ai. “Clients excited about AI’s potential, but deeply cautious about how models are trained and whether their data might be exposed or reused. In sectors like finance or insurance, concerns over data reuse and IP protection are shaping how AI tools are adopted.”

6. AI enhances productivity, but only if developers continue to adapt

While some worry about AI taking over the role of developers, panellists argued that its real power lies in acceleration. “It’s not about AI doing your job,” said Honey Mittal of Locofy.ai. “It’s about using it to do more, faster.”

Abhishek Pathak, Global Head of Field Engineering at FlutterFlow added that while AI lowers the barrier to creation, it raises the stakes for getting things right: “Because creating is easier, you need stronger software engineering fundamentals to ensure what you ship is actually production-ready.”

For Perforce’s Paul Gray, staying relevant means aligning your work with the business’s core value drivers. “Follow the money,” he advised. “Find the part of the application or service that generates the most revenue and get as close to it as you can. That’s the part that won’t go away, and that’s where AI tools will make the biggest impact.”

Still, AI fluency should not be the only priority for engineers. Rachna Kawasra underscored the importance of human-centric skills: “Collaboration and communication are still key.”

And Fortanix’s Jaiswal mentioned the shift in mindset required: “The most important thing is to see yourself as an AI practitioner. Someone who looks at a problem and goes ‘how can AI help me solve it?’, not solve it completely, but help me to.”

7. AI in Singapore: Becoming an emerging hub for innovation

From infrastructure to talent, Singapore’s developer ecosystem is positioned to spearhead the next wave of AI transformation, backed by meaningful government partnerships.

On the sidelines of the Summit, IMDA’s accreditation programme came up repeatedly among panellists and speakers as a powerful catalyst. “It lends a lot of credibility,” said Watermelon Software’s Harpreet Singh. “It’s a great showcase with customers and prospects.”

That credibility goes far beyond branding, Kannan Muthukkaruppan of Yugabyte called it “a rigorous programme that helps build trust with developers and enterprises alike.”

For Saju Pillai of Kong, the benefits were direct and immediate: “IMDA opens doors. It builds trust in new markets and has been one of the best things for us in Singapore”. Rachna Kawasra of TYK noted that the programme “helped us organise developer workshops and gain traction locally.”

Closing remarks: Embracing the era of the forward-thinking developer

Across the day’s discussions, a unified theme emerged: the role of developers has expanded. They are no longer simply builders. Developers now shape organisational direction, uphold ethical standards, and help guide technological change at scale.

As panel moderator and Gartner VP Manjunath Bhat concluded, developers today must understand not only how systems are built, but why. “Time to market, simplicity, and continuous adaptation, that’s the new baseline”, he said.

Andrey Adamovich’s parting advice was simple yet profound. “Focus on what can’t be easily replaced”, he urged. In a time where LLMs can draft code and models can optimize themselves, what remains irreplaceable is judgment, ethics, and the human capacity to design for others.

The future of innovation isn’t just about better technology. It’s about better technologists.