AI-assisted coding has transitioned from experimental novelty to essential infrastructure, expanding usage beyond professional programmers and prompting shifts in industry roles and deployment practices.
Vibe coding has moved from novelty to routine. What was once treated as a temporary fad is now embedded in day-to-day software work, and the conversation has shifted from whether people use AI to write code to who uses it, for what, and with what limits. According to the original report, tools such as Cursor, Lovable and Claude Code have gone from experimental accessories to part of the working stack, even as their inventor, Andrej Karpathy, has argued that the term itself is already becoming outdated. That change reflects a broader pattern: when a technology becomes ordinary, the argument moves from excitement to governance.
The scale of adoption is now hard to ignore. JetBrains’ State of Developer Ecosystem 2025 found that 85% of developers regularly use AI tools at work, while a separate survey by Napoleon IT and ITMO’s AI Talent Hub found that 75% use AI to write and debug code. A 2026 analysis by Coderfile put the figure for developers who use or plan to use AI in development at 84%, although only 33% said they trusted its accuracy. The same report projected the AI coding tools market could reach $127 billion by 2032, underlining how quickly this category has moved from convenience to infrastructure.
The original report’s most striking finding is that the centre of gravity is no longer the professional software engineer. In SpaceWeb’s July 2026 survey, 52% of respondents said they regularly generate code or assemble web projects with neural networks, and another 19% had tried it several times. Yet fewer than one in four were developers. The largest groups were business owners, website administrators, IT managers, freelancers and people building personal projects. In practical terms, code is no longer confined to specialist teams; it is increasingly being used by people whose main job is to launch, test or run a product.
The kinds of projects people are building show the same shift. The report says the most common use is not starting from zero but modifying existing code, followed by creating landing pages, automating repetitive tasks and building web applications. That matches the wider market picture. Presenc.ai’s May and June 2026 landscape reports placed GitHub Copilot at the top of usage, Cursor at the top of revenue and Claude Code at the top of user satisfaction, while noting that GitHub Copilot had more than 20 million users and Cursor more than 5 million active users. The implication is clear: AI coding is now useful enough to support production work, but also broad enough to attract users who are not traditional developers.
The appeal is obvious, but so are the risks. SpaceWeb’s survey found that 30.6% of respondents saw no barrier to using AI for project creation, yet many others pointed to weak technical knowledge, security concerns, an inability to judge code quality and difficulty deploying a finished project. Those worries are not theoretical. CodeRabbit’s December 2025 review of 470 GitHub pull requests found that AI-generated code contained 1.7 times more issues and up to 2.7 times more security vulnerabilities than hand-written code. Security researcher Matt Palmer also reported in spring 2025 that he found exposed endpoints on 170 Lovable-built sites, with data such as names, phone numbers, payment details and API keys at risk.
That helps explain why the current wave of AI-assisted building works best when the person using it already understands the domain. The original report gives examples of an entrepreneur who built a warehouse-tracking tool in a week, a designer who created and deployed a portfolio site, and the author’s own workflow, in which AI-written scripts process back-office data for management reporting on a serverless setup. In each case, the human user still defined the problem, checked the output and corrected mistakes. The developer has not disappeared; rather, the role has become more distributed, with product owner, tester and domain expert often folded into the same person.
The infrastructure layer is adjusting to that reality. SpaceWeb said the share of first-time cloud users among new customers rose from about 15% to 25%, and orders for entry-level VPS plans tripled over the past year. The company argues that providers now need to do more than sell compute, memory and storage. They must simplify deployment, improve support for users with uneven technical skills and prepare for a future in which AI agents, not just people, interact with hosting platforms through APIs. The broader industry trend points in the same direction: the tools are becoming easier to use, but the responsibility for the running service still rests with a human owner.
The likely outcome is not the disappearance of developers or agencies, but a quieter and broader spread of software creation. More users will learn enough Git, logs and databases to manage more complex projects, while infrastructure will continue to abstract away the hardest parts of setup, scaling and monitoring. That will not eliminate poor projects or fragile code. It will, however, lower the cost of trying an idea. In a market where most products fail, that matters. The real shift is not that everyone can now write code. It is that more people can now get as far as a working product before they ever need to hire a specialist.
Disclaimer: This content is intended for informational purposes only. Readers are advised to exercise their own judgement, conduct due diligence, or consult a qualified expert before acting on any information provided.
