A recent Stack Overflow thread asked a simple question: Is it possible to learn coding without AI?
The user, who was building a React Native front end and a Go backend, admitted that they often asked ChatGPT to choose the stack and draft a starter project. They said they wanted to learn, not vibe code. The thread drew many replies, and a familiar worry surfaced.
Has AI made learning easier, or has it removed the very effort that produces real skill?
AIM dug deeper to gather the perspectives of five experts, along with a growing sentiment across the wider industry. What are our takeaways? Let’s find out.
AI as an Accelerant, Not a Teacher
Some developers in the thread said AI helped them find intermediate explanations that documentation did not always provide. One described AI as a fast way to access examples. Others pointed out that official tutorials still answer questions that beginners do not know how to ask.
Ashutosh Prakash Singh, co-founder and CEO of RevRag.AI, an in-app AI agent platform for BFSI, Fintech and Insurtech, sees this across teams. “AI is fundamentally changing how people learn to code. Instead of spending weeks stuck on syntax, debugging, or boilerplate, learners can now focus on problem-solving and systems thinking.”
“People who use AI to learn coding still need to grasp logic, architecture, and constraints.”
He added that AI should be seen as a form of support. “The best way to think of it is that AI is the mentor sitting beside you, not the one writing the exam for you.”
Chaitanya Choudhary, founder of Workers IO, a startup that claims to “put software correctness on autopilot,” also sees strong upside. “AI can basically eliminate the hard, or not so fun parts of figuring out a strategy for learning a complex topic, or gathering the right material for it,” he said.
But he warned of a risk that feels increasingly common. “Some of the models can be very convincingly wrong about things; it is only when you understand things deeply that you can point out the mistakes.”
Choudhary added that Anthropic’s acquisition of Bun suggested there is “still a lot of value in learning how things work deeply instead of solely relying on vibe-coding.”
Sanjay Gupta, CTO at University Living, a global student housing marketplace, highlighted a practical gap. “AI teaches you syntax, struggle teaches you edge cases.”
When the system breaks, he said, it is the person who understands flow and failure modes that ends up repairing the parts that AI glossed over. “A developer who learned the hard way, wrestling with logic, concurrency, and database locking spots this risk immediately,” Gupta added.
Highlighting the importance of coding skills to hire, he said, “When I hire a junior developer, I am not looking for someone who can produce code fast. I am looking for someone who understands [the] consequences.”
The Missing Struggle
Others worry that AI removes the core difficulty that shapes an engineer’s judgment.
Namanyay Goel, founder of Giga AI, which describes itself as “self-learning second brain that works across your engineering stack,” argued that quick answers distort the learning process. “When you ask AI for help, you get answers. Not understanding.”
Citing an example, he said, “You think you’re learning because the code works. But, ‘working code’ doesn’t equal ‘learned skill’. It’s like using a calculator to ‘learn’ math.”
Goel added that while execution is getting code to work, learning is understanding why it works, what alternatives exist, what tradeoffs were made. “AI is phenomenal at execution. It is catastrophic for learning,” he said.
He warned of a dopamine loop that creates surface-level confidence without the depth needed for future change. Without deliberate struggle, he said, learners become “a generation of copy-pasters” who move fast until something breaks.
Arjun Nagulapally, CTO at AIONOS, an AI-first digital transformation company, echoed this loss of depth. “When developers depend too much on AI-generated suggestions, they gradually lose the ability to mentally simulate code.” This simulation is what helps engineers design new features and debug failures.
He explained, “At AIONOS, we view reliance on AI during the learning phase as a form of cognitive technical debt.”
“Just like bad code creates debt in our repo, using AI to bypass the struggle of learning creates debt in your neural pathways.”
He said that new engineers often tell him they don’t need to memorise syntax, as they can just prompt it.
“I disagree. Fluency matters. If you have to look up (or prompt) how to write a for loop or how to initialise a class, your cognitive load is consumed by mechanics rather than architecture.”
The Broader Industry View, Feat. Godfather of AI
This debate is not limited to learners on forums. Geoffrey Hinton, often called the godfather of AI, recently told Business Insider why foundational learning still matters even as AI becomes better at coding.
“Many people think a CS degree is just programming or something,” he said. “Obviously, just being a competent mid-level programmer is not going to be a career for much longer, because AI can do that.”
He added that the degree’s value lies in the deeper layers beneath syntax, and that it “will be valuable for quite a long time.”
A Balanced Path for Learners
Across these viewpoints, one idea repeats. That learners should use AI, but with discipline. Choudhary put this plainly: “As long as one can be disciplined enough, and be intellectually honest with themselves when relying on these models for learning, they can be very useful.”
Goel recommended solving problems alone before turning to AI and explaining AI’s answers back in one’s own words. “Actually read the error message. Google it the old way. Feel the frustration of not finding the answer immediately.”
“That frustration is part of the learning process. Your brain is forming new connections, building mental models, developing problem-solving skills,” he added.
If that cannot be done, the concept has not been learned. Others encouraged one “no-AI project” each month and frequent reading of documentation and source code.
Learning without AI is not foolish. Learning only through AI might be. AI can remove friction, but friction is where understanding forms.
The challenge for new engineers is not choosing to use AI, or not. It is protecting the struggle that builds lasting skill, while still using the tools that make learning easier.
The post Is It Stupid to Learn Coding Without AI? appeared first on Analytics India Magazine.
