Hexaware Technologies CEO R Srikrishna made a striking prediction about the future of software development. Speaking exclusively to Forbes India, he stated that rapid advances in artificial intelligence could reduce the human cost of coding dramatically. Furthermore, he suggested that this cost could eventually reach zero entirely. Consequently, his remarks have sparked significant discussion across the global technology industry about the long-term future of human developers.
What Is Vibe Coding and Why Does It Matter
Currently, a new approach to software development called vibe coding is gaining rapid popularity worldwide. Specifically, vibe coding allows users to generate functional software using simple natural language prompts rather than traditional programming languages. Consequently, non-coders can now build working prototypes quickly and access development tools that were previously exclusive to trained engineers. Together, these capabilities are widening participation in software development significantly and challenging long-held assumptions about who can build technology.
The Limitations That Still Hold Vibe Coding Back
However, vibe coding still struggles with genuinely complex software tasks. Specifically, integrating multiple systems, managing large codebases and handling third-party APIs remain significant challenges for current AI development tools. Furthermore, as complexity increases, the need for verification, debugging and repeated iterations rises sharply, reducing overall efficiency. Additionally, this process frequently generates tech debt — a dangerous build-up of untested and difficult-to-maintain code. Therefore, vibe coding currently remains most useful for early-stage prototyping rather than enterprise-scale software production.
The Future: Rebuild From Scratch Instead of Repair
Srikrishna told Forbes India that this limitation may not persist for long. Specifically, he argued that as AI tools continue to advance, companies may no longer need to repair or painstakingly rewrite flawed legacy code at all. Furthermore, organisations could simply discard their outdated systems entirely and generate brand new, fully functional software from scratch using AI. Consequently, this shift would sharply reduce dependence on human developers across the industry. Additionally, it would cut costs fundamentally and reshape the entire economic model on which the software development industry currently operates.
Hexaware is not waiting for this future to arrive on its own. Currently, the company has launched RapidX in direct partnership with coding platform Replit. Specifically, RapidX enables users to convert natural language instructions into production-ready software without traditional coding expertise. Furthermore, Hexaware is actively developing a Zero License model aimed at replacing conventional software with fully AI-driven solutions by 2026. Together, these initiatives represent a comprehensive and ambitious bet on AI becoming the primary driver of software creation across industries globally.
The Plan to Eliminate Tech Debt Entirely
Additionally, Hexaware is pursuing a separate but equally ambitious goal, the complete elimination of tech debt. Currently, tech debt represents one of the most persistent and costly problems facing large technology organisations worldwide. Specifically, it accumulates when code is written quickly without adequate testing or long-term maintenance planning, creating compounding problems for future development teams. Therefore, Hexaware’s efforts to address tech debt alongside its AI development tools signal a broader ambition to fundamentally change how software is built, maintained and replaced over time.
What This Means for Human Developers
Together, these developments raise an uncomfortable but unavoidable question for the global developer community. If AI can generate, test and deploy production-ready software from natural language instructions, the traditional role of the human software engineer faces significant disruption. However, Srikrishna’s prediction of zero coding costs remains a future possibility rather than a present reality. Currently, human expertise remains essential for complex system design, ethical oversight and high-stakes technical decision-making. Consequently, the industry is watching closely to see how quickly AI tools can close the remaining gap between promise and production-level capability.
