Introduction
Artificial Intelligence is quietly revolutionizing how Indian startups approach software development. No longer just a buzzword, AI is becoming a practical co-pilot for developers writing code, spotting bugs, and even suggesting architectural improvements. In a fast-paced startup environment, where speed and efficiency can make or break a product, AI tools like GitHub Copilot, ChatGPT, and automated testing frameworks are streamlining workflows and reducing development cycles. For many early-stage companies, AI isn’t just an add-on; it’s a competitive edge. As these tools become more accessible and powerful, they’re reshaping the coding culture in India’s startup ecosystem, ushering in a new era of tech innovation. GetMyIndia.com
Code Meets Intelligence – AI’s Growing Influence on Indian Startups
Artificial Intelligence is rapidly reshaping how Indian startups build, test, and deploy software. From automating repetitive coding tasks to optimizing entire development workflows, AI tools like GitHub Copilot, ChatGPT, and custom ML models are becoming integral to tech teams. Early-stage startups are especially benefiting, using AI to accelerate product development and reduce time-to-market without needing large engineering teams.
Beyond just code generation, AI is influencing debugging, code review, and even decision-making around tech architecture. As a result, founders and developers can focus more on innovation and user experience rather than boilerplate code. With India’s vibrant startup ecosystem and growing AI talent pool, this synergy between artificial intelligence and software development is setting a new standard where agility, efficiency, and intelligence go hand in hand.
More for granular tasks
Tech leaders such as OpenAI’s Sam Altman, Salesforce chief Marc Benioff, and Anthropic chief executive Dario Amodei have predicted a future where AI generates most of the world’s code. In March, the chief executive of Y Combinator noted that around 25% of the startup accelerator’s current startups were already using AI to write 95% or more of their code.
Nadh explained that rather than using AI tools for generating large swaths of code, Zerodha is leveraging platforms like Aider, GitHub Copilot, DeepSeek, Claude, and Gemini more granularly, for tasks like auto-completing boilerplate code, sanity-checking, and making code more concise.
Saurabh Karn, founding member of Sarvam AI, acknowledged the trend and said some of the projects at the AI startup have 80-90% of the code generated through various agents. “AI may be coming into the picture, and changing the role of a coder, but the responsibility remains the same: build highly-compliant, controlled code and models,” he said.
This shift is evident across sectors. Sudip Ghose, founder of luggage firm Uppercase, said AI now contributes 50-55% to its codebase, up from just 5-10% a year ago.
Inmobi founder and chief executive officer Naveen Tewari took to the social media platform X to caution tech professionals to upskill, as the company expects to write about 80% of its code through AI tools by the end of this year.
Data management company Reltio, which recently opened an R&D centre in Bengaluru, is generating about 15% of its code through GenAI, CEO Manish Sood told ET. A third of data security unicorn Druva’s code is written by AI, ET reported on Tuesday.
This is significantly helping productivity. Ghose said that after this shift, initial coding tasks now take almost 70% less time than before. Sood concurred, saying productivity across different areas due to AI usage was up about 10%.
Dangers lie ahead
Despite the clear advantages, AI coding has presented its challenges. At e-visa startup Atlys, where 25-30% of the codebase is either directly generated or heavily assisted by AI agents, an AI agent once attempted to simplify a script used for cleaning up old log files. This resulted in a serious error: Due to a missing configuration, the script deleted an entire working directory instead of just the intended log files, wiping out essential system files and causing a service to crash repeatedly, said founder Mohak Nahta.
Erring on the side of caution, online self-publishing and audiobook portal Pratilipi also does not use AI to write code, but only in basic structuring tasks. “We avoid taking any kind of risk that could be existential in nature. The bar is high; the code that goes into production has to be error-free. So, we use AI for structuring and reviewing the code, but not for writing,” chief executive Ranjeet Pratap Singh told ET.
Adapting to AI
AI’s proficiency in generating boilerplate code and automating repetitive tasks elevates the entry-level expectations for junior developers. “Entry-level and early-career software engineers will have to accept and acknowledge AI as a significant and able competitor on the floor,” said Prasadh MS, head of workforce research at staffing firm Xpheno.
“AI’s ability to operate at a scale and speed that are humanly impossible to match is a definite advantage that enterprises will pay for. It’s natural for enterprises to expect young engineers to come pre-equipped and prepared to work along with AI agents as digital colleagues,” he added. Neeti Sharma, chief executive of TeamLease Digital, said startups will eventually not look for software developers in high volumes. “Companies will not hire coders, but they will look for someone who knows how to read the code and evaluate its efficacy,” she said.
There are about 1.5 million STEM (science, technology, engineering, and mathematics) graduates who enter the ecosystem every year. “As seen over the last few quarters, the net number of jobs around data security, AI, and machine learning has gone up dramatically. While coding jobs may slow down, new jobs are coming in. Founders will now judge a candidate not on the code they have written, but assess their prompt library,” Sharma said.
Conclusion
AI is no longer a futuristic concept; it’s a present-day reality that’s reshaping how Indian startups approach software development. From automating boilerplate code to accelerating debugging and deployment, AI tools are boosting productivity and enabling leaner tech teams to deliver faster. However, this transformation also brings challenges, including risks of code errors and a shift in developer roles. As AI takes over routine tasks, startups increasingly seek engineers who can guide, audit, and collaborate effectively with AI agents. In this evolving landscape, coding is still king, but knowing how to prompt, evaluate, and work alongside AI quickly becomes the new crown jewel.
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