While it may not entirely help land a job, GitHub has traditionally served as a developer’s portfolio, offering a public record of coding activity, projects, and contributions. However, with the rise of AI-assisted tools like Cursor, it’s now possible to build an entire GitHub profile without actually knowing how to code.
By prompting natural language into tools like Cursor, users can auto-generate code, structure repositories, and commit changes that mimic the workflow of a seasoned developer. On paper, the profile looks active, thoughtful, and technically impressive. In reality, it could have been created by someone with no technical background. This raises a critical question: does this create a false sense of skill for employers or fellow developers reviewing such profiles?
The Rise of AI Coding Tools
AIM recently tested Cursor, a popular AI-powered coding IDE, and confirmed that it’s entirely possible to build a GitHub portfolio, complete with repositories, commits, and multiple projects, without writing a single line of code.
Tools like Cursor, Windsurf and Lovable are fast turning non-coders into pseudo-developers. However, this shift raises doubts about the significance of GitHub contributions.
Traditional IDEs like VS Code, JetBrains, or PyCharm once served as the battle-hardened tools of programmers. Yet, the appeal of natural-language-based development has grown. Cursor, which is essentially a VS Code fork with generative AI on top, makes the IDE experience seem almost obsolete.
While Microsoft has already added AI capabilities to VS Code, AI coding tools do not seem to be going anywhere soon.
The fundamental shift suggests that writing boilerplate code is no longer the primary bottleneck. Moreover, even if AI coding present challenges, developers still rely on it in one way or the other. As per a report on AI Trends by Bondcap, the number of AI developer repositories on GitHub increased by approximately 175% over 16 months between November 2022 and March 2024.
All things considered, AI-generated GitHub activity might soon be indistinguishable from that of human developers.
What Developers Have to Say
This democratisation of coding power using these AI tools brings an ethical and professional dilemma. Eduard Ruzga, a staff engineer at Prezi, told AIM that he doesn’t rely on GitHub activity as a hiring signal. “I would look at PRs if I wanted to learn about a potential candidate…There are other things that spike activity without real work,” he noted. What matters, according to him, is the reasoning and code quality.
Pratham Patel, a software engineer, broke the issue down into two parts. “Using something like Cursor gives you an edge in the candidate filtering process, but past that, interviewers will ask you not to use any kind of assistance,” he said while speaking to AIM.
However, he pointed out that several companies, like Klarna, are already recommending AI tools internally to speed up development. He explained that the primary objective is to ensure engineers become accustomed to AI’s enduring presence. The practical utility of AI is a separate consideration. Nevertheless, adapting to it offers advantages, regardless of its immediate helpfulness. If it proves valuable, it is advantageous. If not, individuals will develop the ability to recognise and potentially disregard its limitations.
However, the real concern lies in resume filtering. AI-generated contributions might unfairly boost a candidate’s portfolio. Agreeing with the sentiment, Patel said, “It helps the candidate in the resume filtering process, unfairly.”
Coding Credibility Crisis
For those genuinely skilled in coding, this could feel like betrayal. This is especially true in India’s IT sector, where AI threatens to further erode the value of programming expertise. Tanay Pratap, YouTuber and founder of Invact Metaversity, highlighted at MLDS 2025, “Indian IT services don’t code.” The sector, built on service-based models and testing contracts, might find its largest workforce replaced, not upskilled, by AI tools.
Generative IDEs won’t replace the need for actual coding knowledge when it comes to debugging, system design, or handling large-scale deployments. However, if GitHub profiles can be automated, it throws a wrench into how hiring managers assess talent. It’s no longer just about whether someone can code, but whether they actually did.
The future might not care who typed the code, as long as it works. But for now, the blurred line between skill and simulation remains a risk.
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