Ah, the 2025 Hot Vibe Code Summer. Throw on your flip flops, open a beach chair, and drink your coffee out of a coconut with a little umbrella. Now, let’s vibe code some silly web apps and fun AI experiments! Vibe coding is laid-back, casual, and a tiny bit lazy, much like my favorite summer days.
Now that it’s September I’m restless. Is this an Endless Summer situation or is the AI winter upon us? Does vibe coding need the heat of novelty to persist, or does it have staying power on its own? Here’s what we do know: new tools and features to support vibe coding are flooding the market, the merits of vibe coded apps remain hotly debated, and vibe coding is still fun. So let’s discuss!
What is Vibe Coding?
Vibe coding is still new enough that definitions are rampant and contested. In simplest terms, it’s coding on cruise control. It’s letting LLMs do the heavy lifting while the developer kicks back and guides the process in using natural language. It’s describing a program to an AI like you’re ordering a pizza—for best results, be specific.
Andrej Karpathy coined the term and idea in a now famous tweet:
There’s a new kind of coding I call “vibe coding”, where you fully give in to the vibes, embrace exponentials, and forget that the code even exists.
Karpathy goes on to describe himself building a project by just talking to an AI-powered editor (Cursor’s Composer—the company that brought us YOLO mode—with a speech interface), and then accepting every suggestion, and lazily copy-pasting error messages for the AI to fix. In his words, the code practically writes itself while “I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works.”
The vibe coding idea took off and others have joined to both expand Karpathy’s definition. Simon Willison, for instance, explains:
When I talk about vibe coding I mean building software with an LLM without reviewing the code it writes.
In other words, vibe coders describe what they want in natural language, let the AI generate or modify the code, and don’t bother to meticulously check that code line-by-line. Willison goes on to emphasize vibe coding’s potential for learning and experimentation. Although it should not become synonymous with professional software engineering practices—especially because he doesn’t want the term to become a slur for “irresponsible” coding—vibe coding’s greatest strength is as a celebration of creativity. By removing the initial tedious barriers to writing software, Willison sees vibe coding as a potentially massive democratizing force:
I believe everyone deserves the ability to automate tedious tasks in their lives with computers. You shouldn’t need a computer science degree or programming bootcamp in order to get computers to do extremely specific tasks for you.
If vibe coding grants millions of new people the ability to build their own custom tools, I could not be happier about it.
I recently had Shawn “swyx” Wang on the MonkCast, and I asked him to help me differentiate between AI Engineering (something I’ve been thinking a lot about) and vibe coding. Swyx is much less bullish about coding with vibes. While he admits “it gives everyone the warm fuzzies,” it also encourages carelessness:
vibe coding is a slop attractor. Like it excuses slop because I was, like, I was just vibe coding.
In Shawn’s view, it’s the 80/20 rule gone awry: people stop at the “good enough” point (the 80%) and never finish the hard 20% of polishing and bug fixing. While he doesn’t deny that vibe coding can boost velocity, he insists the vibes should ultimately be about efficiency and quality, not just goofing off. As a fix, he points to the more rigorous discipline of AI Engineering and his own “Tiny Teams” idea, meaning “teams with more millions in ARR than employees.”
With those definitions in mind, I tend to think about vibe coding as a practice that turns programming into a collaboration with your AI: heavy on intuition and “go with the flow” energy, light on strict planning or painstaking manual coding. Developers speak/ type their intent in natural language, the AI translates it into code, and then roll with whatever the AI comes up with, tweaking via more plain-English prompts as needed.
It’s the Hot Vibe Code Summer because now more than ever coding feels akin to jamming with an AI bandmate than performing a solo concerto. Instead of RTFM, it’s “Roll With The Suggestions.” Instead of painstaking debugging, it’s “ask the AI to fix it, and if it can’t, just vibe around the bug or build something else.” It’s chaotic, it’s fun, and it’s producing everything from apps nobody asked for to surprisingly useful tools. And crucially, it feels like summer. Many vibe coders are giddy, experimenting freely, not too worried about long-term consequences. Just ignoring the haters and living in the moment.
New Tools Fueling the Vibe Coding Wave
Tech companies large and small saw the vibe and raised it with tools that make AI-assisted coding easier and more accessible than ever. Let’s begin with the LLMs. Vibe coders would be nowhere without good models, and the models just keep improving. DeepSeek-v3, Google’s Gemini, Anthropic’s Claude, xAI’s Grok-4, and OpenAI’s ChatGPT are all so good on benchmarks that they can enable more devs to try vibe coding, even outside of specialized IDEs and platforms.
Vibe coders already have access to many tools to get started, including IDEs like Cursor and Windsurf, and SaaS platforms like Lovable, v0, Bolt, and Replit, but this summer it feels like every week there’s a new AI coding tool dropping. Below are some highlights from the tool and feature-palooza contributing to the Hot Vibe Code Summer.
Perhaps the most on-the-nose example is Kiro, AWS’s AI-powered IDE (see my colleagues Rachel Stephens’s and James Governor’s thoughts on Kiro). Interestingly, Kiro has a toggle for two modes: “Vibe” and “Spec.” Yes, AWS explicitly built a “vibe coding” button right into the IDE. While spec mode is a more structured approach in which the AI will first gather a requirements spec from you, then design, then implement with your sign-off at each step, making it more like traditional planning, just AI-assisted, in vibe mode, by contrast, you just describe what you want, and the agent goes off to generate code and infrastructure, making a lot of assumptions along the way.
Another major boost to vibe coding came from GitHub. In addition to GitHub Copilot, which has long been many vibe coders’ tool of choice (especially now that there’s a free tier), GitHub recently introduced Spark, an AI-powered platform that promises to “transform your ideas into full-stack intelligent apps and publish with a single click.” Spark is positioned as an all-in-one playground where you describe an application in natural language and it generates a working project (frontend, backend, and all) on the fly.
But while the vibe is strong and the tools are slick, not everything is sunshine and shipped prototypes. As more developers hand over the reins to AI tools and skip code reviews in pursuit of flow, one big issue keeps floating to the surface that vendors have been forced to take seriously: security.
Vibing with Security Guardrails
— Amjad Masad (@amasad) February 27, 2025
Security is a growing concern in the world of vibe coding that is leaving some vendors on the back foot. Replit proudly markets its platform as “Vibe Coding Made Easy.” But that carefree ethos came under scrutiny after a recent incident where Replit AI went rogue and a user lost their production database. The fallout prompted Replit to double down on its security posture—a clear sign that even the most vibe-forward platforms are being forced to reconcile their “Fun!” philosophy (to quote Replit CEO Amjad Masad‘s pithy tweet) with the hard realities of risk and reliability.
Another high-profile security pitfall for vibe coders has been MCP (Model Context Protocol), which has sparked controversy after incidents involving data leaks. Both GitHub and Supabase faced blowback this summer when their MCPs inadvertently exposed user information. These episodes prompted public concern about how much trust developers—AI Engineers and vibe coders alike—should place in AI-assisted tooling.
Unfortunately these folks didn’t follow our security procedures when publishing thishttps://t.co/KelIgGP2hT
Nonetheless, the security team discovered this post when it was released and we put heavy guardrails around this exploit (which we will explain once the General Analysis…
— Paul Copplestone – e/postgres (@kiwicopple) July 6, 2025
Austin Parker, Director of Open Source at Honeycomb, weighed in on this tension in his blog post “How Does ‘Vibe Coding’ Work With Observability?” His advice? Enjoy the vibes, but verify the results. He urges developers to treat AI-generated code like any other production system: instrument it with good observability, write tests, and monitor it in real time. “If something breaks in production,” he warns, “you’ll really wish you had telemetry on that code the AI wrote.” It’s classic DevOps wisdom applied to the new world of vibe coding: don’t just ship it and forget it. Ship it and observe it.
Blazing Tokens
Another area of uproar this summer was Cursor’s pricing fiasco. As the de facto vibe coding tool that Karpathy mentions by name, Cursor’s change to its pricing model incensed the vibe community. In June, Cursor introduced a new expensive “Ultra” plan and adjusted the “Pro” plan’s limits in a confusing way, effectively charging heavy users more for certain AI model usage. The communication was poor, and some users got hit with surprise charges or found features limited. Since then Reddit and Twitter have been filled with complaints that Cursor had ruined its vibe.
I'm officially going back to @code.
Incredible progress by the Copilot team catching up to Cursor. It's at a point where I can't justify having both subscriptions anymore. pic.twitter.com/4Kac8OvwUy
— Santiago (@svpino) August 3, 2025
The backlash was so intense that by July 4, Cursor’s CEO Michael Truell publicly apologized in a blog post titled “Clarifying Our Pricing.” He admitted:
Our recent pricing changes for individual plans were not communicated clearly, and we take full responsibility. We work hard to build tools you can trust, and these changes hurt that trust.
Cursor offered refunds for unexpected charges and attempted to clarify how the new plan actually worked. The community’s reaction to the apology was mixed. Some appreciated the refund gesture, others remained skeptical.
The Cursor pricing debacle laid bare an uncomfortable truth at the heart of Hot Vibe Code Summer: vibe coding burns tokens fast and vendors can’t keep footing the bill. Vibe coding thrives on open-ended prompts, iterative generation, and lots of back-and-forth with LLMs, which adds up to massive token usage. Cursor’s attempt to quietly tighten limits and introduce new pricing tiers wasn’t just a business misstep, it was a signal flare.
I have a Cursor bill of close to $200 😬.
Didn’t realise I was burning through extra cash by using GPT-5 – thought it was part of the subscription.
Also hate the fact that there is no budget alert or easy way to find out how much I’ve spent already.
Disappointed.
— Eddie Forson (@Ed_Forson) September 6, 2025
The reality is that none of the major players can sustainably offer unlimited, unmetered access to powerful models when users are out there blasting gigabytes into the prompt window every day. Developers have come to expect constraints and restrictions from vendors including OpenAI and Anthropic. Many call for visible usage bars and express frustration over stealthy throttling tactics. The economics of vibe coding just don’t scale without limits, and while the summer’s been hot, autumn may bring token rationing for all.
Agentic Vibes and the Windsurf Acquisition
We have also seen the heretofore emergent category of “agentic” coding tools blossom. These are systems where the AI doesn’t just suggest code, but can take higher-level tasks and break them into coding subtasks autonomously. More and more AI code assistants have added an “Agent Mode” such as Copilot and Windsurf that promises to push vibe coding to the extreme. Speaking of Windsurf, this AI dev tool offered one of the summer’s spiciest dramas.
Windsurf was reportedly in acquisition talks with OpenAI for a whopping $3 billion (yes, with a b) valuation. That alone shows how high the stakes (and hype) are for vibe coding tech, with investors seeing it as the next big platform. The OpenAI deal fell through amid antitrust concerns, and then things got wild: Google’s DeepMind swooped in to hire the CEO and key team members directly, licensing Windsurf’s tech instead of buying the company. This left Windsurf as a bit of a ship without a captain. Morale at the startup plunged. “The mood was very bleak,” according to interim CEO Jeff Wang, describing an all-hands meeting where employees realized the big acquisition they hoped for wasn’t happening. But just when Windsurf’s vibe coding dream seemed to be turning into a nightmare, there was a twist! A smaller AI company called Cognition, the makers of Devin, swooped in and acquired what remained of Windsurf in a deal that finalized in July.
My take away from this story is that while the vibes may be casual, the business of vibe coding is serious, and everyone wants a piece of that vibe-driven ARR.
When the Vibe Gets Too Hot
The developer community has been vocal in discussing the pros and cons of this vibe coding trend, and not everything is sunshine and Megan Thee Stallion hits. On the enthusiastic side, many developers on Reddit and Hacker News are loving their newfound superpowers. I have discussed it before, but any doubters should check out the r/vibecoding subreddit to see takes like this:
Don’t ever waste your time on critics who don’t get it. They just don’t understand AI. Vibe coding is the future and gets better every day.
Not sure I agree with Redditor “Busy-Awareness420” on all points, but with a username like that I fully acknowledge they can probably teach me a thing or two about vibes. What’s important to understand is that there’s a palpable sense in many communities that a whole new world has opened up, and it’s fun.
While novice and nontechnical users tend to get the most attention, even more experienced devs are finding joy in vibe coding. Unsurprisingly, their perspective tends to be much more sober. You’ll hear accounts like this Hacker News user:
I’ve really enjoyed working on some throwaway projects where I can work like this and not sweat the small stuff at all. That said, the one area that’s tricky to reconcile in this mode is security: in my (fairly extensive) experience with the current state of AI coding assistants, prompting for security is nowhere near sufficient for me to be comfortable putting a web app on the internet without reviewing the code carefully.
Just in the past few weeks I can think of several instances where an AI assistant added sensitive API endpoints with no authentication whatsoever, updated API endpoints with methods that didn’t follow my guidance on authorization or existing authorization patterns in the codebase, or created templates with brutal potential for XSS.
I’m all in on coding with LLMs and use them every single day, but I’m quite confident there will be plenty of work for security engineers as we explore this future.
What I like about this post is its balance of enthusiasm and skepticism. Security is a perennial concern among experienced devs that deign to vibe code. The danger of AI inserting some dangerously insecure code or even malicious NPM packages when vibe coding is very real. But for local experiments many just don’t care that the code isn’t perfect.
The consensus among the pro-vibe quotient—or even the vibe-tolerant—is that for prototypes, small niche apps, landing pages, quick hacks, and learning projects, we can let the vibes flow. We have linting, tests, and code reviews for the serious stuff, and not every codebase needs to be a cathedral. Sometimes a sandcastle is enough, especially in summertime.
Conclusion: Vibe On, Vibers
Summer 2025 will be remembered as the Hot Vibe Code Summer, a season when coding felt fresh and fun, powered by leaps in AI tech that made the complex suddenly easy. The term “vibe coding” may have started as a tongue-in-cheek joke that Karpathy later tried to reframe as “context engineering,” but it struck a chord by capturing a real shift in how many people approach programming, with a more intuitive, exploratory, and devil-may-care mindset.
Will the vibe last, or will it be swept away with the market froth now making headlines like “Is the A.I. Boom Turning Into an A.I. Bubble?” As autumn rolls in, some developers may stash their Hawaiian shirts just as investors begin to snap their wallets shut. Still, something tells me that the spirit of vibe coding will stick around—even if the cringe name doesn’t.
AI-empowered developers have seen what’s possible when you “embrace the vibes,” and with the tools only getting better, some core features of what we now call vibe coding will become standard parts of the dev toolkit. The key will be learning when to coast on vibes and when to buckle down. For now, I’m soaking it in. At its best, the Hot Vibe Code Summer is about freedom and enjoyment. Never before could a solo dev whip up a complex app over a weekend just by describing it to an AI. Never before could a newbie skip the months of slog to get a “Hello World” app by having an AI agent guide them step by step to a working project. Sure, there are pitfalls (hallucinated code, security issues, spaghetti logic), but with the community and vendors working together I’m optimistic.
Summer’s not over yet here at RedMonk, and there are plenty more apps to be built before the leaves turn. It’s a Hot Vibe Code Summer, and we’re all invited. Happy coding, and happy vibing, y’all!
Disclaimer: AWS, Microsoft, Honeycomb, GitHub, and Google are RedMonk clients.
Header image from Beach Party (1963).