Latest news with #AndrejKarpathy
Forbes
a day ago
- Entertainment
- Forbes
Vibe Coding: It's Four Months Old. What's Up?
Female freelance developer coding and programming. Coding on two with screens with code language and ... More application. What is vibe coding, anyway? The term, coined by Andrej Karpathy a few months ago, is now shorthand for an entire shift in the way that we view software engineering. It's the idea that AI is 'hands-off' in terms of code generation: the machine just takes the human's inputs, and comes up with source code on its own. Although LLMs are not 100% autonomous with this yet, and there's often a need for some debugging, vibe coding essentially asks the programmer to back off and let the AI do its thing. In contemporary coverage of the phenomenon, Forbes Council member Shubham Nigam quotes Rhiannon Williams of the MIT Technology Review: 'Not all AI-assisted coding is vibe coding. To truly vibe-code, you have to be prepared to let the AI fully take control and refrain from checking and directly tweaking the code it generates as you go along—surrendering to the vibes.' So while it's a colloquial term (good vibes, man!) it's also a request for the human in the loop to take distance – not to stand over the LLM's shoulder as it creates. Here's more from a recent panel at Imagination in Action in April. Nikolay Vyahhi of Hyperskill interviews Artem Lukoianov, Heena Purohit, and Aldo Pareja about this trend. 'I guess the whole beauty of this term is because it so accurately presents what's actually happening,' Lukoianov said. 'You don't even have to read the code that it produces. You … just basically teleprompt to the system, it generates a part of the code for you, and then, quite often, because developers are notorious for being lazy, you don't even read the codes.' 'You don't even try to understand what the code is doing,' added Pareja, theorizing about what will happen when IDEs and other tools start to incorporate unit testing. 'You don't even read the code. You're just feeling it.' Panelist Zach Lloyd talked about the realities of source code management. '(Developers will) get into trouble, and get and they'll try to vibe their way out of it, or they'll get into trouble with their production system and try to vibe their way out of it,' he said. 'So in the terminal, we see it goes beyond producing code, to this whole feeling of: 'let me see if the AI can just fix this thing for me, and maybe I won't have to understand exactly what it's doing.' Lloyd described this power as a kind of double-edged sword: on the one hand, it's, as he said, a 'magical' thing for a developer who feels stuck. On the other hand, he suggested, it can be dangerous for the human coder not to know what the system is doing at all. Panelist Heena Purohit pointed to some challenges with letting the AI have its own project. She argued the systems are not typically good at 'distance thinking,' or how various components of a system interact. 'Sure, you can have millions of lines of code be generated in minutes or seconds, but you still need to understand what the code is actually doing, so that you can troubleshoot it and debug it when you need to,' she said, suggesting that in many cases, scaling might be a problem. By contrast, Lukoianov gave a sort of qualified opinion that we are mostly there, and will get there soon. '(Vibe coding capability) is already good enough for us to stop coding anything,' he said. 'To me, it's more the question of how we engineer the system around this… how do we … provide the correct information to the LLM, how do we summarize our code base, and how do we provide the right tools to the LLM to actually perform … better? in my personal opinion, I feel that like the LLM is already there. It's all about, how do we properly provide this information about your code base, about what you want, about any regulations, security issues that are around there. So it's all just about the correct information, correct inputs, correct tools, to the LLMs, and eventually we'll get there.' In the 1980s, he pointed out, we had to be very close to the hardware – now, it's different. 'You don't think that much about operating systems,' he said. 'You don't think that much about hardware, unless you're working in something very specialized.' Regardless of the change, Pareja argued that full stack developers are still valuable. 'If you're using (tools) to synchronize different processes, and you have a million processes, your system is going to break,' he said. 'You need to understand these constraints.' If I was going to boil down some of the biggest ideas in this panel, I think most of them would be around the need for coding knowledge to manage the detail and periphery of systems development. In other words, the AI can do everything, but it might not do it 100% the way that you need it to be done. And there's that old adage: if you want it done right, you have to do it yourself. Maybe LLMs get us 80% of the way there without any oversight, but skipping the context and being completely ignorant of what the machine is doing is typically not a good idea, partly for the reasons that the panelists laid out. So the human in the loop is still relevant for now. But the bottom line is that vibe coding is something so new and fundamental that we'll probably be spending a lot of time figuring out how to do it best.
Indian Express
4 days ago
- Business
- Indian Express
The tech job market is changing: Here's what software engineers need to know in 2025
Artificial intelligence is becoming the new reality of the job market. If you are aiming to become a software engineer—or aspire to be one—you should expect that automation and intelligent systems will be an integral part of the workplace by the time you are ready to start your first job. In fact, according to estimates, 60 per cent of current jobs will require significant adaptation due to AI. This means that to remain competitive, you will need more than just critical thinking skills—you will also need digital fluency and a solid understanding of AI. For those already in the workforce, AI will play a crucial role in reinventing careers. As the job market is rapidly changing and new roles are emerging, here are five key shifts that every software engineer should know about. For years, the process of writing computer programs—also known as coding—was done entirely by humans. But AI is now changing the landscape of software development. Today, it's possible to write code using only a text prompt, thanks to generative AI tools like ChatGPT. This marks a major departure from traditional coding methods, where code generation tools were largely structured and domain-specific. The new approach has been referred to as 'vibe coding' by Andrej Karpathy, an OpenAI co-founder who previously led AI efforts at Tesla. Vibe coding focuses on the 'vibe' of the software rather than the code itself. This means you no longer need to master programming languages or understand complex data structures—a simple natural language prompt can do the trick. Vibe coding relies on standard patterns in technical language, which AI systems use to assemble original code from their training data. With tools like GitHub Copilot or CursorChat, you can input a few prompts and let the AI do the job. As vibe coding gains more prominence, it could signal a gradual shift toward using natural language as a viable tool for developing certain types of software. However, don't expect vibe coding to replace experienced software engineers or developers anytime soon. Still, as AI models continue to improve, vibe coding may further blur the line between AI and human programmers. If you look at what's currently happening at Silicon Valley's top tech companies—and even at Indian IT firms—they are no longer announcing sudden layoffs or letting people go abruptly, as they did two years ago. Those high-profile exits often triggered PR disasters and damaged company morale. Instead, many companies are now opting for silent layoffs or quiet firing, a more calculated approach where roles are made less desirable—often targeting employees over the age of 40, for example—thereby demotivating them to the point that they choose to resign on their own. It's all happening, but without making much noise. This new tactic allows companies to offer severance packages while requesting employees not to disclose the details of their exit. The goal of silent layoffs is to minimise public backlash and avoid drawing negative attention to the company. Although compensation in tech remains among the highest across industries, salaries for software engineers have stabilised. The days of a gold rush to hire engineers—with exponential pay increases driven by remote work demand and tech hiring booms—are largely over. Software engineers and data professionals are still in high demand, but salary growth has slowed compared to previous years. In fact, the salary gap between employees who stay in their roles and those who switch jobs has shrunk to its lowest level in 10 years, according to The Wall Street Journal, citing the latest federal data. As hiring budgets stall and companies put the brakes on internal 'moonshot' projects, the better-than-expected annual salary increase a tech worker can expect has diminished. Even Counteroffers that are still common in tech but are not as aggressive as they were during the hiring frenzy of the past few years. However, top-tier engineers—especially those with expertise in AI or cloud technologies—can still command premium compensation. The right skills are what you need to stand out from the crowd and land a job—especially when opportunities are limited and competition is sky-high. Simply switching jobs might no longer guarantee a better position as it once did, but having the right skills still can. AI and Machine Learning – Even if you are not from a computer science background, understanding how AI integrates into workflows is something you should know. Cloud and DevOps – Tech companies are paying top dollars if they have an expertise in cloud security, AWS/Azure platforms, and scalable infrastructure. Cybersecurity and Compliance – With increasing data hacks and changing regulations, security specialists are in high demand and can draw premium salaries. Data Storytelling and Analytics – Data is the new oil but insights are just as important for running a successful business. If you have a knack for numbers and know how to turn them into actionable strategies, you have a strong chance of succeeding in your career. Your career progress often depends on the nature of your new role. fsSome people take a new job for better long-term career opportunities, while others may be motivated by short-term financial gain. Whatever option you choose, always consider whether the company offers long-term stability or if it's hiring aggressively but cutting just as quickly. Also, think about whether the perks and flexibility are worth as much—or even more—than a higher base salary. Anuj Bhatia is a personal technology writer at who has been covering smartphones, personal computers, gaming, apps, and lifestyle tech actively since 2011. He specialises in writing longer-form feature articles and explainers on trending tech topics. His unique interests encompass delving into vintage tech, retro gaming and composing in-depth narratives on the intersection of history, technology, and popular culture. He covers major international tech conferences and product launches from the world's biggest and most valuable tech brands including Apple, Google and others. At the same time, he also extensively covers indie, home-grown tech startups. Prior to joining The Indian Express in late 2016, he served as a senior tech writer at My Mobile magazine and previously held roles as a reviewer and tech writer at Gizbot. Anuj holds a postgraduate degree from Banaras Hindu University. You can find Anuj on Linkedin. Email: ... Read More
Fast Company
08-06-2025
- Fast Company
Vibe coding lets anyone write software—but comes with risks
Whether you're streaming a show, paying bills online or sending an email, each of these actions relies on computer programs that run behind the scenes. The process of writing computer programs is known as coding. Until recently, most computer code was written, at least originally, by human beings. But with the advent of generative artificial intelligence, that has begun to change. Just as you can ask ChatGPT to spin up a recipe for a favorite dish or write a sonnet in the style of Lord Byron, now you can ask generative AI tools to write computer code for you. Andrej Karpathy, an OpenAI co-founder who previously led AI efforts at Tesla, recently termed this ' vibe coding.' For complete beginners or nontechnical dreamers, writing code based on vibes—feelings rather than explicitly defined information—could feel like a superpower. You don't need to master programming languages or complex data structures. A simple natural language prompt will do the trick. How it works Vibe coding leans on standard patterns of technical language, which AI systems use to piece together original code from their training data. Any beginner can use an AI assistant such as GitHub Copilot or Cursor Chat, put in a few prompts, and let the system get to work. Here's an example: 'Create a lively and interactive visual experience that reacts to music, user interaction, or real-time data. Your animation should include smooth transitions and colorful and lively visuals with an engaging flow in the experience. The animation should feel organic and responsive to the music, user interaction, or live data and facilitate an experience that is immersive and captivating. Complete this project using JavaScript or React, and allow for easy customization to set the mood for other experiences.' But AI tools do this without any real grasp of specific rules, edge cases, or security requirements for the software in question. This is a far cry from the processes behind developing production-grade software, which must balance trade-offs between product requirements, speed, scalability, sustainability, and security. Skilled engineers write and review the code, run tests, and establish safety barriers before going live. But while the lack of a structured process saves time and lowers the skills required to code, there are trade-offs. With vibe coding, most of these stress-testing practices go out the window, leaving systems vulnerable to malicious attacks and leaks of personal data. And there's no easy fix: If you don't understand every—or any—line of code that your AI agent writes, you can't repair the code when it breaks. Or worse, as some experts have pointed out, you won't notice when it's silently failing. The AI itself is not equipped to carry out this analysis either. It recognizes what 'working' code usually looks like, but it cannot necessarily diagnose or fix deeper problems that the code might cause or exacerbate. Why it matters Vibe coding could be just a flash-in-the-pan phenomenon that will fizzle before long, but it may also find deeper applications with seasoned programmers. The practice could help skilled software engineers and developers more quickly turn an idea into a viable prototype. It could also enable novice programmers or even amateur coders to experience the power of AI, perhaps motivating them to pursue the discipline more deeply. Vibe coding also may signal a shift that could make natural language a more viable tool for developing some computer programs. If so, it would echo early website editing systems known as WYSIWYG editors that promised designers 'what you see is what you get,' or 'drag-and-drop' website builders that made it easy for anyone with basic computer skills to launch a blog. For now, I don't believe that vibe coding will replace experienced software engineers, developers, or computer scientists. The discipline and the art are much more nuanced than what AI can handle, and the risks of passing off 'vibe code' as legitimate software are too great. But as AI models improve and become more adept at incorporating context and accounting for risk, practices like vibe coding might cause the boundary between AI and human programmer to blur further.
India Today
05-06-2025
- India Today
What is Vibe Coding and why are IT professionals talking about it all the time? The new tech trend explained
For a long time, writing code meant sitting for hours in front of a computer, typing out lines and lines of instructions in a programming language. It needed technical skills, a lot of patience, and even more practice. But recently, a new way of writing code has become popular — and people are calling it vibe coding. It sounds like a trend on social media, but it's actually about using AI to build software just by describing what you want in plain, simple language. No need for complex code, no stress — just a simple conversation with your computer that turns into an app, game, or website. Let's break it down exactly is vibe coding?If we have to define vibe coding, you can think of it as a way of creating software without writing all the code yourself. Instead, you just talk to an AI tool — by typing or even speaking — and explain what you want to build. The AI does the heavy lifting and writes the code for don't have to worry about the way code has to be written, or remembering commands, or finding bugs. You just describe your idea clearly, and the AI takes care of the rest. That's why it's called vibe coding — because you're going with the flow and trusting the AI to figure out the did this idea come from? The term vibe coding was made popular by Andrej Karpathy, who has worked with companies like Tesla and OpenAI. He described it as letting go of the old-school way of thinking about code and just focusing on your idea. You don't have to be a pro coder any more. You just need to have a clear picture of what you want, and AI tools will help you turn it into himself said he doesn't even check the code line by line any more — he just describes what he wants, accepts whatever the AI suggests, and moves on. It might sound lazy, but for quick projects or experiments, it works surprisingly does vibe coding actually work?Here's a simple step-by-step example of how someone might vibe code:Pick from the many tools available, like Replit, Cursor, or ChatGPT that can generate you need to type your idea. You might say something like, 'I want to create a calculator app with buttons for plus, minus, multiply, and divide.'After this, the AI will write the code for you. The tool will create the base version of your you need to test and tweak accordingly. If something doesn't work or looks odd, you just tell the AI what to the end, you have a working app that you created without doing any actual traditional coding is being used by both developers and non-developers. People who never wrote a line of code in their life are now able to build apps and vibe coding the same as AI-assisted coding?Not quite. AI-assisted coding still involves a developer writing most of the code, with the AI giving suggestions or helping fix mistakes. Vibe coding, on the other hand, is when the AI takes the lead, and the person mostly just gives we be worried about vibe coding?advertisementSome people in the tech industry are worried that vibe coding might make programmers lazy, or that it could lead to poorly written code, especially if people don't review what the AI creates. There's also concern that beginners might never learn the basics of real others believe it's just a new chapter in how we build software. It doesn't replace serious programming, especially for complex systems — but it does make building simple apps faster and more fun.
Economic Times
04-06-2025
- Business
- Economic Times
Amazon racing to roll out AI chatbot Cursor amid employee pressure: Report
Tech major Amazon is in advanced talks to roll out an artificial intelligence (AI) chatbot, Cursor, across its workforce, amid pressure from its employees seeking access to the popular AI chatbot, according to internal company communications reviewed by Business Insider. The report added, an Amazon HR manager who oversees the company's AI adoption told employees via messaging platform Slack that the company is working "asap" to integrate Cursor. Though they added that the deployment might take some time, as 'a few high priority security issues' to Amazon's tight security requirements. This move indicates a significant shift for the US tech major, which typically doesn't encourage its employees to use any external AI tools since the company provides its own AI coding assistant called Q and an internal AI chatbot named 'Cedric'. The report further added that in a Slack group dedicated to Cursor discussion, approximately 1,500 Amazon employees participated to show interest in the tool. Internal polling results within the group showed more than 60 Amazon employees preferred Cursor over other competing tools, such as Windsurf, which only 10 people chose. Last year, Cursor's desktop application gained popularity, particularly for its ability to assist with coding using Anthropic's Claude 3.5 Sonnet model. Its features got a further boost when Microsoft added the model to GitHub Copilot. The platform's rise continued after AI researcher Andrej Karpathy helped popularise the idea of 'vibe coding', where developers let AI take the lead on writing code. By March, the tool had over one million daily users, highlighting its rapid growth and appeal. Company chief Andy Jassy acknowledged Cursor's popularity during last month's earnings call, citing the company as a key driver behind the "explosion of coding agents."Also Read: Windsurf vs Cursor: Inside OpenAI's quest for an AI coding startup
