GENCOW founder Kevin Choi
For all the excitement around AI-assisted coding, a stubborn gap remains: building a demo has become easier, but turning that demo into a reliable product is still hard.
That is the problem GENCOW, a South Korea-based AI service development platform, is trying to solve. Founded by Kevin Choi, a former Samsung Electronics executive with more than 15 years of experience building global software products, the company sits in a fast-growing category of tools that promise to help founders and developers move from idea to working application with less backend engineering.
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Choi’s view is blunt: AI will not make developers obsolete. Instead, he believes it will create many more of them.
“Many people believe AI will eliminate software developers. I see the exact opposite,” he said. “AI isn’t taking developers’ jobs away. It’s enabling millions more people to turn their ideas into real products.”
It is an argument increasingly heard across startup ecosystems, including Southeast Asia, where engineering talent remains expensive, technical co-founders are hard to find, and many early-stage ideas never progress beyond slides or mock-ups. AI coding tools have changed what is possible at the prototype stage. The next challenge is whether they can also lower the cost and complexity of launching real services.
The hidden work behind every app
GENCOW’s starting point is not the visible side of software: slick interfaces, chatbots, dashboards or mobile screens. It is the infrastructure beneath them.
Before founding the company, Choi spent more than a decade and a half at Samsung Electronics, where he led the development of international software products and worked on large-scale launches. Over time, he noticed a pattern. As deadlines approached, backend engineers were often the ones working the latest nights.
That is because every new digital service requires far more than the feature a user sees. Teams must set up servers, databases, authentication, payments, APIs, cloud infrastructure, deployment systems and security controls. For AI products, there is another layer: connecting to models, managing data flows and ensuring the service can operate reliably outside a test environment.
“The polished applications users see are supported by countless hours of invisible engineering,” Choi said. “I watched talented colleagues spend nights and weekends handling repetitive infrastructure work.”
GENCOW was built around that pain point. Its platform provides common building blocks such as user authentication, database management, payment integration, AI connectivity and operational infrastructure. The idea is to let developers and founders focus on what makes their product distinct, instead of repeatedly rebuilding the same backend systems.
The company describes its approach as “Prompt to Production”, a phrase that captures a broader shift in software creation. Natural-language prompts can now produce code and functional prototypes. GENCOW wants to extend that process to services that can actually run in the market.
Why this matters in Southeast Asia
The timing is relevant for Southeast Asia’s startup market. Across Indonesia, Vietnam, the Philippines, Thailand, Malaysia and Singapore, founders are experimenting with AI products in education, logistics, finance, healthcare, agriculture and customer service. But many face the same constraint: it is easier to identify a problem than to assemble the technical team needed to solve it.
This is especially true outside major hubs such as Singapore, Jakarta, Ho Chi Minh City and Bangkok. A founder in agritech, for example, may understand crop supply chains deeply but lack access to engineers who can build a scalable platform. A teacher may know exactly where learning gaps exist but be unable to turn that insight into a usable AI tutoring product. Local operators often have strong domain knowledge, but software development costs can block them before they test demand.
That is where platforms like GENCOW could become relevant. If AI lowers the technical barrier to product creation, Southeast Asia may see more startups emerge from industry practitioners rather than only from traditional software teams.
Choi sees this as a redefinition of who gets to be a developer.
“In the future, being a developer won’t be limited to people with computer science degrees,” he said. “Entrepreneurs, designers, marketers, researchers, educators, anyone with expertise in solving real-world problems will be able to build software with AI.”
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The claim should not be overstated. Production software still requires judgement, security awareness, product thinking and operational discipline. A badly designed fintech or healthtech tool can do real harm. But the direction of travel is clear: the early stages of software creation are becoming more accessible.
From coding assistance to company creation
GENCOW is not alone in chasing this opportunity. Globally, the market includes infrastructure and app development tools such as Google’s Firebase, AWS Amplify, Supabase, Vercel, Replit, Bolt and Lovable, each attacking different parts of the software-building workflow. Some focus on backend infrastructure, others on AI-assisted coding or front-end app generation. GENCOW’s challenge will be to show that its combination of AI service development and production infrastructure offers enough value in a crowded field.
For founders, the difference between these tools matters. A prototype builder helps create a working demo. A backend-as-a-service platform removes some infrastructure work. A deployment platform helps teams ship and scale. The next generation of AI development platforms is trying to combine these steps into a more continuous workflow, reducing the handoff between idea, code, backend setup and live product.
GENCOW has already found one route into the market through South Korea’s government-backed “Startup for Everyone” initiative, where it was selected as an official AI solution provider. Through the programme, the company works with aspiring entrepreneurs and early-stage startups building AI-powered services.
Choi said the ideas he sees range from agriculture and education to local community problems. In the past, many such concepts would have struggled to move forward because hiring developers was too expensive or difficult. Now, he argues, founders can test ideas faster and with fewer resources.
“In the past, building a new service often required months of development,” he said. “Today, with AI, teams can build prototypes in days, validate ideas quickly, and iterate much faster.”
The future developer may not look like one
The biggest question hanging over AI development tools is whether they reduce the need for engineers or simply change what engineers do.
Choi is firmly in the second camp. His argument is that developers will spend less time assembling routine infrastructure and more time solving harder problems: architecture, security, product quality, data governance and user experience. In other words, AI may not remove technical work, but it could push human effort higher up the value chain.
That matters in markets where engineering teams are stretched thin. A small startup in Southeast Asia rarely has the luxury of dedicated backend, DevOps, security and AI infrastructure specialists. If common technical work can be automated or packaged, lean teams can attempt products that previously required larger budgets.
There is also a human dimension to Choi’s thesis. He frames GENCOW not only as a productivity tool, but as a way to reduce the late-night burden on developers.
“I want software developers to spend less time on repetitive infrastructure work and more time solving meaningful problems,” he said. “I want them to leave the office earlier, have dinner with their families, and focus on innovation instead of rebuilding the same backend systems over and over again.”
That may sound idealistic in an industry known for tight deadlines and compressed launch cycles. But it points to a real shift. If AI can absorb more of the repetitive work, software creation could become less about who can grind through infrastructure fastest and more about who understands the problem best.
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For Southeast Asia, where the next wave of digital products will need to solve local, fragmented and often offline problems, that shift could be significant. The region does not just need more apps. It needs more people with direct knowledge of real-world problems to have a practical path to building them.
GENCOW’s bet is that AI will make that possible — not by replacing developers, but by multiplying the number of people who can create software at all.
The post From Samsung to startups: Kevin Choi’s bet on AI-powered software creation appeared first on e27.