Google’s most powerful executive is spending his free time asking an AI to build websites for him, and he insists that this new way of working will change who gets to call themselves a coder. As artificial intelligence tools move from autocomplete helpers to full-blown collaborators, the center of gravity in software development is shifting from syntax to intent, from typing to describing what you want.
I see that shift most clearly in the rise of “vibe coding,” the term that has gone from an in-joke among AI researchers to a talking point for Google’s leadership. It captures a deeper transformation: when you can build working software by steering an AI with natural language, the boundary between professional engineer and everyone else starts to blur.
How vibe coding went from meme to mainstream
The phrase “vibe coding” started as a kind of shorthand for a feeling: you sketch what you want in loose language, the machine fills in the details, and you keep nudging it until the result matches the mental picture. AI researcher Andrej Karpathy helped crystallize that idea earlier this year, describing a workflow where the human focuses on goals and constraints while the AI handles writing the actual code. Instead of laboring over every line, you spend your time refining prompts, adjusting architecture, and deciding what “good enough” looks like.
That sensibility has since been formalized into a recognizable technique. On Vibe coding pages and technical explainers, it is framed as an artificial intelligence-assisted software development technique popularized by Andrej Karpathy, where the research methods center on iterative interaction with a model rather than manual implementation. One detailed breakdown describes vibe coding as an approach where you describe the behavior and “vibe” of a system in natural language, then let the AI propose implementations, a pattern that aligns with how While Andrej may have coined the term but not the underlying idea of using AI in coding.
What Sundar Pichai actually means by “vibe coding”
When Google CEO Sundar Pichai talks about vibe coding, he is not just endorsing a buzzword, he is describing a reordering of the developer’s job. In his telling, software development is “exciting again” because the hard part is no longer typing out boilerplate but orchestrating powerful models that can generate, refactor, and translate code on command. In a recent interview, Google CEO Sundar Pichai is quoted saying that this style of AI-assisted work has made software development “exciting again,” even as some developers question whether that excitement is universally shared.
Inside Google’s own framing, vibe coding is not a toy but an “AI innovation catalyst.” Company leaders argue that a new wave of AI-driven development is emerging from the deep investments they have made in models and tooling, and that this is changing how quickly teams can move from idea to product. In one account of those internal views, Why Google CEO Sees Vibe Coding as an Innovation Catalyst is tied directly to the company’s belief that AI can compress the distance between a concept and working code, especially when guided by someone who understands both the product and the underlying systems.
From typing code to steering AI: how the workflow changes
At the heart of vibe coding is a simple but profound shift: the primary skill is no longer writing code, it is steering an AI that writes code for you. Google’s own technical guide describes a workflow where the human defines the problem, constraints, and desired behavior, then iteratively refines AI-generated snippets until they fit, while the AI handles writing the actual code. That does not eliminate the need for engineering judgment, but it moves the work up a level of abstraction, closer to product design and system thinking.
Practitioners describe this as a conversational loop rather than a one-shot prompt. In one widely cited definition, a senior engineer explains that “in vibe coding, you leverage powerful AI tools to generate and iterate on code, especially early in the prototype phase,” a description captured in a newsletter where In Beyond Vibe Coding, Addy Osmani lays out how this works in practice. You might start by asking the AI to scaffold a backend for a ride-sharing app, then refine the database schema, API contracts, and error handling through successive prompts, reviewing and editing as you go.
Why Google’s CEO is vibe coding for fun
For Sundar Pichai, this is not just a management talking point, it is a personal hobby. He has described sitting down at his computer and using AI coding tools to build a custom webpage, not as a formal project but as something he does for enjoyment. In one account of that experiment, Google CEO Sundar Pichai disclosed that he has been “vibe coding” his way to a website, using AI coding tools to build a new webpage rather than delegating the task to a team.
He has also spoken about how this makes him feel more like a hands-on builder again. In one interview, Sundar Pichai is quoted saying that “it feels so delightful to be a coder,” describing how he could type a location and have the AI generate a map-based interface without manually wiring every API call. That anecdote is telling: the CEO of a company with tens of thousands of engineers is choosing to tinker with AI-generated code himself, which signals how accessible these tools have become for people who understand products but do not live in an IDE every day.
Who gets to be a “coder” when the AI writes the code
Once you accept that the AI can handle much of the syntax, the obvious question is who now qualifies as a developer. Vibe coding lowers the barrier to entry, because someone who can describe a workflow in clear language can get a working prototype without mastering a specific framework. That is part of why Learn more explainers emphasize that the major appeal of vibe coding lies in how easy it is to interact with an AI in natural language, asking it to build, refactor, or debug code that you might not have been able to write from scratch.
That accessibility is already drawing in people who would not have called themselves programmers a few years ago. In one profile of early adopters, The CEO of the Swedish fintech firm featured there said that he has been vibe coding for 20 years in spirit, long before the term existed, by focusing on describing what he wanted software to do and letting others implement it. Now, with AI in the loop, that product-first mindset can translate directly into working code, which blurs the line between “business” and “engineering” roles and supports Sundar Pichai’s claim that this new style of development is changing who codes.
Why experts still matter in a vibe-coded world
For all the enthusiasm, even Google’s leadership is careful to stress that vibe coding does not eliminate the need for seasoned engineers. Sundar Pichai has publicly warned that while AI can generate and tweak code across languages, organizations still need experts to ensure the security and accuracy of what ships to users. In a detailed account of his comments, a report notes that During a podcast episode with Logan Kilpatrick from Google DeepMind, Google CEO Sundar Pichai emphasized that AI-generated code still requires expert oversight, especially when it touches critical systems.
Independent research backs up that caution. One study of AI-assisted programming argues that AI-generated code does not have to be perfect to be valuable, but that a questionable output and a lack of explanation can create serious risks if teams treat it as a drop-in replacement for human work. The authors conclude that a one-size-fits-all approach may not be feasible, and that organizations need to adapt their processes to the strengths and weaknesses of these tools, a point captured in the line that Nevertheless AI-generated code can be valuable even when imperfect. In practice, that means vibe coding works best when senior engineers design the architecture, review the AI’s output, and set guardrails for how and where these tools are used.
What early results say about code quality and productivity
Beyond anecdotes, there is emerging evidence that vibe coding can produce code that is not just faster to write but sometimes better than hand-crafted alternatives. One software firm that has leaned into this style of work reports that when vibe coding is done under proper conditions, with solid specifications and senior review, the resulting code quality has proven to be equal or even higher than traditional approaches for many use cases. Their analysis notes that When those conditions are met, AI-assisted development can outperform hand-written code on maintainability and consistency, because the model tends to apply patterns uniformly.
That does not mean every team will see the same gains. Some developers complain that they spend more time debugging opaque AI output than they would have spent writing the feature themselves, and that the tools can hallucinate APIs or misinterpret requirements. Even Sundar Pichai’s own framing leaves room for that skepticism, since he calls vibe coding a valuable addition to the toolkit rather than a replacement for existing practices. The nuance in his comments, captured in reports that Speaking in a Google for Developers podcast he tied vibe coding to the deep investments the company has built, suggests that the real productivity boost comes when teams integrate AI into disciplined engineering workflows instead of treating it as magic.
Inside Google’s podcast moment for vibe coding
The turning point for vibe coding as a mainstream concept came when Sundar Pichai sat down for a Google for Developers podcast and talked about it at length. In that conversation, he framed AI-assisted coding as the natural outcome of years of investment in models and developer tools, and he described how internal teams are already using these capabilities to move faster. One account of the episode notes that Nov coverage of the interview highlighted how he sees vibe coding as part of a broader shift in how software is built inside the company.
The host of that conversation, Logan Kilpatrick, plays a quiet but important role in this story. As the person who runs Google’s developer relations podcast, he is one of the conduits between the company’s research labs and the broader ecosystem of engineers who will actually use these tools. Reports on the episode point out that Logan Kilpatrick hosts the podcast where Pichai made his most detailed public case for vibe coding so far, a sign that Google wants this message to land squarely with working developers rather than just investors or policymakers.
The quiet tension: enthusiasm, skepticism, and what comes next
There is a tension running through all of this. On one side, Sundar Pichai and other executives talk about vibe coding as a way to make software development feel fresh again, to give more people the power to build, and to accelerate innovation on top of Google’s AI stack. On the other, some professional developers worry that their craft is being reduced to prompt writing, or that management will overestimate what these tools can safely do. That split is visible in coverage that notes how Nov reports of Pichai’s excitement sit alongside developers who might disagree with his assessment.
From where I sit, the most realistic future is not one where AI replaces coders, but one where the definition of “coder” expands. Product managers who can articulate a clear user journey, designers who can express interaction flows precisely, and domain experts who can describe complex rules in plain language will all be able to build more directly than before. At the same time, the demand for people who can design robust architectures, reason about performance and security, and audit AI-generated code will only grow. Vibe coding, in other words, is less about automating developers out of existence and more about pulling more people into the act of creating software, with experts still anchoring the work.
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