Less typing, more vibing: How AI is fundamentally changing coding

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What was earlier limited to minor suggestions is now full-scale assistance, where the developer gives instructions, and the AI handles the execution

What was once the domain of seasoned developers writing thousands of lines of code is now being reimagined by AI agents that respond to plain English and even images—transforming software creation into a more intuitive, artistic, and radically faster process. Experts say this shift is more than a tech trend—it’s a wake-up call for enterprises still relying heavily on manual, labour-intensive coding for early-stage development, who may fall behind more agile competitors who can rapidly iterate using AI.

Coined by OpenAI co-founder Andrej Karpathy, vibe coding is said to alter the status quo by democratising access to software development and reshaping the role of engineers in the age of AI collaboration.

Nagasanthosh Joysula, the co-founder of Tabletsprint, explained, “Vibe implies an emotional state. When we create art forms like a painting or a song, we emotionally bond with them. On the other hand, coding till recently was supposed to be dominated by logic and structure. Now, combined with conversational interfaces, AI agents are bringing out the coding artists.”

Working smarter

Tablesprint is a full-stack chat-based AI App builder platform that enables enterprises to build, automate, and scale business applications—without writing code. Companies like Flipkart, Vedantu, Aspire Fintech, and Easebuzz have partnered with Tablesprint to build complex, scalable tools without writing code.

While logic and structure persist, almost anyone can master software applications with the brain power of AI agents, he said. TableSprint’s DevConsult AI is a vibe coding platform built for such creators, with Replit and Lovable being other notable players.

Until a few months ago, AI could only perform basic tasks like auto-completion. But with new advancements such as Claude 3.7 and Google Gemini 2.5 Pro, developers can now provide screenshots or English prompts, with which the AI can generate code modules, noted Paramdeep Singh, the Co-Founders of Shorthills AI, which also leverages vibe coding to quickly build core systems and develop apps.

What was earlier limited to minor suggestions is now full-scale assistance, where the developer gives instructions, and the AI handles the execution. These models can write code, generate documentation, create test cases, and improve overall developer efficiency. Tasks that earlier took days or weeks can now be completed in hours, fundamentally changing how software development is approached and executed.

“This shift dramatically lowers the entry barrier, allowing anyone with ideas to quickly prototype and test them—even without formal training in computer science. While this could impact lower-value or repetitive coding jobs, it opens up new possibilities for innovation and speed in product development,” shared Jaspreet Bindra, Co-founder, of AI&Beyond.

Enterprises are seeing significant efficiency gains by reducing development cycles and enabling smaller teams to accomplish more, said Joysula. This will inevitably require companies relying only on traditional, manual coding methods to embrace the shift.

A wake-up call

On the flip side, companies relying on writing boilerplate or routine maintenance code will need to upskill.

“AI will take over basic, repetitive tasks. Developers who understand business problems and can build solutions around them will continue to be in demand. Those who only write standard code will be replaced unless they evolve,” the Shorthills AI co-founder said.

To stay competitive, developers must shift to solving more complex problems that require layered thinking, something AI cannot yet replicate. This includes understanding business needs and translating them into technical solutions. Custom algorithms and non-standard workflows will still require human input.

The emergence of such AI-assisted development will not diminish the role of engineers and instead, transform it, Mayank Maggon, Founder, CEO & CTO, of TechChefz Digital, said. The focus will move from writing every line of code to reviewing, debugging, and refining AI-generated suggestions.

To stay relevant and excel in this evolving landscape, engineers will need to embrace a new set of core competencies including mastering prompt engineering, adopting systems thinking, and developing AI literacy by understanding the capabilities, limitations, and risks of large language models (LLMs).

As the engineering role shifts closer to product ideation and user experience, skills like product thinking, collaboration, and storytelling will become increasingly vital.

“This trend is a wake-up call for companies still relying heavily on manual, labour-intensive coding for early-stage development. They risk falling behind more agile competitors who can rapidly iterate using AI. However, building scalable, secure, and feature-rich products will still require the rigor of traditional engineering—meaning companies need to find the right balance between vibe coding for speed and traditional coding for robustness,” Bindra said.

Organisations that embrace this dual approach—using vibe coding for rapid prototyping and reserving expert engineering for scale and polish—will be best positioned to thrive, he added.