Indian developers say AI helps them learn more as they code less
Across Indian development teams, a quiet anxiety is spreading: the belief that writing every line by hand is the only path to mastery. Recent conversations reveal that many engineers, especially newer hires, feel trapped by the expectation to produce code from scratch, even as AI‑driven assistants become commonplace. Managers report a split in productivity—some interns cling to manual coding, while peers who tap into generative tools move faster and, paradoxically, absorb concepts more readily.
This tension has sparked a broader debate about what “learning” really means when a machine can fill in boilerplate or suggest entire functions. As companies grapple with balancing traditional practice against the efficiencies AI offers, the question becomes less about speed and more about depth of understanding. The following remarks capture why, for many, the real value lies not in the volume of keystrokes but in the insights AI can surface while the code itself writes itself.
So I feel you [developers] can learn more with AI," he explained. "We had a few interns who were trying to write all the code from scratch, which was actually holding others back who were using AI to code," he added, reinforcing how important it is to learn to use AI tools. Similarly, Adarsh Shirawalmath, founder of Tensoic AI and an SGLang developer, told AIM that junior developers often use AI coding tools without understanding what the output code is. "But sometimes the way I've seen some engineers use AI, especially working on large projects like SGlang, blows my mind," he added.
Can AI truly replace the hands‑on practice that builds a developer’s intuition? The Bengaluru front‑end developer says his team ships faster thanks to Cursor and Lovable, yet admits the learning curve has flattened. Learning is at risk.
Interns who still code from scratch were, in his view, slowing down peers who rely on AI assistance. This tension suggests that proficiency with the tools is becoming a new prerequisite, while traditional coding drills recede. Companies appear to be mandating Copilot‑like solutions, but the article offers no data on long‑term skill retention.
Some developers feel they can learn more by mastering AI, but the same source notes that “there is very little learning curve left.” Whether the trade‑off between speed and depth of understanding will balance out remains unclear. The narrative stops short of measuring productivity gains against potential skill decay. In short, AI aids delivery, yet raises questions about how developers will maintain core competencies without regular, manual coding practice.
Further Reading
- Product Hunt - AI Tools - Product Hunt
- There's An AI For That - TAAFT
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Common Questions Answered
How are Indian development teams perceiving the impact of AI‑driven coding assistants on learning speed?
Managers report that developers who leverage generative AI tools tend to move faster and absorb concepts more readily than those who write code from scratch. The article notes that interns relying on manual coding can actually hold back peers who use AI, suggesting AI accelerates learning for many.
Which AI tools are mentioned as helping Bengaluru front‑end developers ship code faster?
The article cites Cursor and Lovable as the AI assistants that enable the Bengaluru front‑end team to increase shipping speed. These tools are highlighted as examples of generative assistants that improve productivity while raising concerns about a flattened learning curve.
What concerns does the article raise about junior developers using AI coding tools without understanding the output?
Adarsh Shirawalmath of Tensoic AI warns that junior developers often employ AI tools without grasping the generated code, which could undermine deep comprehension. This lack of understanding may erode the hands‑on practice that builds a developer’s intuition over time.
According to the article, how is proficiency with AI tools becoming a new prerequisite for developers?
The tension described shows that teams view mastery of AI assistants as essential, while traditional coding drills are receding. Companies are even mandating tools like Copilot, indicating that being skilled with AI is increasingly required for effective development work.