By Oleg Sidorkin, CTO of Cinevva

Andrej Karpathy coined the term "vibe coding" in February 2025 to describe building software by describing what you want and letting AI handle the implementation. A year later, Collins Dictionary made it their Word of the Year. Searches for the term jumped 6,700% that spring.

For most software, vibe coding means faster prototyping. For game development, it means something more specific. The barrier between "weird idea" and "playable prototype" collapsed.

A Breaker Belt: Snake meets Arkanoid, vibe coded in three days on the Cinevva Engine

What actually changed

Game jams exist because game development takes too long for most experiments. You get 48 hours, a theme, and whatever energy you can sustain on caffeine and adrenaline. The constraint forces creativity. You can't build anything ambitious, so you build something weird. Some of the best games in history started as jam projects.

Vibe coding does something similar but removes the artificial time pressure. When describing a mechanic, a mood, or a behavior gets you a working prototype in minutes instead of days, you can try ideas that nobody would greenlight. The economics of experimentation changed.

We built A Breaker Belt in three days. Two people, on and off, not crunching. Snake meets Arkanoid. 50 waves. 23 brick types. Reactive music. AI narration. Real-time synthesized sound effects. Shipped to web, mobile, and PC. That scope would normally take a team of eight or nine people several months. The weird mashup that would die in a brainstorm doc instead got built over a long weekend.

That's what vibe coding actually does for games. It doesn't make great games automatic. It makes experiments cheap.

The numbers behind the trend

The investment tells you how seriously the industry is taking this. Cursor raised $2.3 billion in Series D. Lovable raised $330 million at a $6.6 billion valuation. An estimated 25% of Y Combinator's Winter 2025 startups ran on codebases that are 95% AI-generated.

In game development specifically, Three.js is now the primary library for vibe-coded web games, with 2.7 million weekly npm downloads. Platforms like Cinevva, Phaser, and a growing list of AI tools are building development environments where describing intent is the primary input.

Karpathy himself has already moved on to the next concept. He's calling it "agentic engineering," where AI agents write code themselves rather than responding to human prompts. "There is an art and science and expertise to it," he wrote. The field is moving faster than the vocabulary.

What doesn't change

The limits are real and worth being honest about. As projects grow, context management becomes the bottleneck. AI model performance degrades when your project gets complex enough that the full context doesn't fit in a single window. The code you get is often good enough to run but not good enough to maintain. When something breaks, debugging AI-generated complexity that nobody fully understands is its own special challenge.

There's also the taste problem. AI can generate a mechanically functional game very quickly. It can't tell you whether the game is fun. Whether the difficulty curve feels right. Whether the music matches the mood. Whether the pacing keeps you engaged or slowly bores you. That layer of judgment, the thing that separates a prototype from a game worth playing, still requires a human who cares about the result.

Game jams work because the time pressure forces you to make hard choices about what matters. Vibe coding removes the time pressure but not the need for choices. The best vibe-coded games will come from people who know what they want, not from people who accept whatever comes back.

What I think happens next

More games that shouldn't exist will exist. Some of them will be terrible. Some of them will be brilliant. The ratio might not change, but the volume will. And in that volume, you'll find games that could never have been made before. Genres that don't have names yet. Mashups nobody would have funded. Personal projects that one person built because the tools finally got out of the way.

That's always been the promise of better tools. Not that everything gets better, but that more things get to exist. The game jam energy, the "let's just try this and see," is no longer confined to a 48-hour window. It's Tuesday afternoon and you have an idea. By Thursday, it's playable.

Cinevva's engine is free to use. Your weird game idea might be three days away from existing.

Related:

• A Breaker Belt: Snake meets Arkanoid, vibe coded in three days
• We didn't expect to build a radio station
• Agentic AI code tools — Claude Code, Cursor, and GitHub Copilot for game development
• Game Jams & Hackathons — the original 48-hour game creation format
• Web Game Engines Comparison — engines that pair well with AI-assisted workflows

By Oleg Sidorkin, CTO of Cinevva

Steam Next Fest isn't just an event. It's a dataset. Over 2,200 games showed up in February 2026 with demos, trailers, and hopes for wishlists. The results are in, and they confirm something indie developers feel but don't always say out loud.

Next Fest rewards games that already have an audience. If you're starting from zero, the festival alone won't change that.

Standout indie games from Steam Next Fest February 2026

The numbers

presskit.gg analyzed the data and the tiers are pretty stark:

The median game earned 460 wishlists. That's with a demo available, a store page live, and Steam actively promoting the event. Four hundred and sixty wishlists for a week of dedicated visibility on the largest PC gaming platform on Earth.

Momentum compounds. Obscurity compounds too.

The Diamond tier games almost all entered with 10,000+ existing wishlists. They had content creator coverage before the festival started. Their capsule art communicated instantly at thumbnail sizes. They'd done the marketing work before showing up.

The games entering with fewer than 1,000 wishlists? They mostly gained a few hundred more. The festival amplified what was already there. It didn't manufacture something from nothing.

This pattern isn't unique to Next Fest. It shows up everywhere in discovery. YouTube recommends videos that are already performing well. Spotify surfaces songs with existing listens. Store algorithms everywhere reward engagement with more engagement.

If you have momentum, Next Fest is a multiplier. If you don't, it's a participation certificate.

Genre matters more than you'd think

Co-op games overperformed across the board. Content creators want to play with friends on stream. That social dynamic generates clips, which generates views, which generates wishlists. The social play loop feeds the social media loop.

Survival and crafting games stayed strong despite how crowded the genre feels from the developer side. Players still want these games. The supply hasn't exceeded the demand.

Narrative games and visual novels struggled. The format of Next Fest works against them. Demo browsing rewards fast visual clarity. You need to understand what a game is within seconds of seeing its capsule art and maybe watching ten seconds of gameplay. Story-driven games need context that thumbnails can't provide.

Roguelikes could still break through, but only with strong differentiation. "It's a roguelike with a twist" needs the twist to be visible at a glance.

Why we're watching this closely

This data matters to us because Cinevva was built specifically for the problem it reveals. Our reels-first discovery shows real gameplay, not curated screenshots. You scroll through clips, see something that looks fun, and you're playing it instantly in your browser.

We're not trying to replace Steam or compete with Next Fest. The data tells us these platforms work great for games that already have visibility. The question we care about is: what happens to the other 2,000 games? The ones that are genuinely good but didn't enter with an existing audience?

Those games need a discovery path that doesn't depend on pre-existing momentum. Somewhere a player can stumble onto a game they'd never find in a store, because they saw five seconds of it and it looked interesting. That's the gap we're building into.

The Steam Next Fest strategy guide we published earlier this year covers the tactical side. This piece is about the structural takeaway. Discovery on the biggest platform in PC gaming is increasingly a rich-get-richer system. If that's the only system, a lot of great games will stay invisible.

Related:

• Steam Next Fest February 2026 data
• Steam Next Fest strategy guide — tactics for making Next Fest work for you
• Co-op Game Design — co-op games consistently overperform at festivals
• How to Launch Your Game on itch.io — an alternative discovery path for smaller games

By Oleg Sidorkin, CTO of Cinevva

Rémi Verschelde is one of the people who keeps Godot running. Not as a side project or a hobby. As a life's work. He's been maintaining the engine since before most people had heard of it, reviewing contributions, merging patches, making sure the thing millions of developers depend on actually works.

Last month, he described what's happening to Godot's contribution pipeline as "draining and demoralizing."

The cause: AI-generated pull requests. Lots of them.

Godot has 4,681 open pull requests on GitHub right now. A growing percentage of new submissions are generated by people who typed a prompt, got some code, and submitted it without understanding what it does. The code often looks plausible at first glance. It compiles. The variable names make sense. Then a maintainer spends twenty minutes figuring out that it introduces a subtle bug, breaks an edge case, or solves a problem that doesn't exist.

The time spent rejecting bad PRs is time not spent reviewing good ones.

The irony writes itself

AI tools are supposed to make developers more productive. That's the pitch. That's why companies are raising billions to build them. And at the individual level, they do. I use AI tools every day. Our entire platform uses AI for game creation, music generation, 3D models, and more. I'm not anti-AI.

But there's a system-level effect that nobody talks about in the investor decks. When AI makes it trivially easy to generate a contribution, and the cost of submitting drops to zero, but the cost of reviewing stays exactly where it was, you get a pollution problem.

The people submitting these PRs aren't malicious. Most of them genuinely want to contribute. They've been told that AI tools let them contribute to open source without deep expertise. And the tools do let them generate something that looks like a contribution. It just isn't one.

Verschelde acknowledged that using AI to detect AI-generated PRs would be "horribly ironic." He's right. Fighting AI output with AI detection is an arms race nobody wins.

What this really tells us

Making something is now cheap. Making something good still costs the same.

That's the lesson showing up everywhere, not just in open-source code review. It shows up in game development, in music production, in content creation. AI dropped the floor. The minimum viable contribution, the minimum viable game, the minimum viable blog post can now be generated in seconds. But the ceiling didn't move.

The people who were already good at their craft are now faster. The gap between "made a thing" and "made a thing worth someone's time" is actually wider than it used to be, because the volume of mediocre output has exploded while the number of people who can evaluate quality hasn't changed.

Godot's contribution guidelines require disclosure of AI assistance. People ignore them. You could make the rules stricter, but enforcement requires the same human review time you're trying to save.

The real solution is boring

Verschelde's primary ask is funding. Hire more maintainers. More humans reviewing the work. That's not a technical solution. It's an organizational one. And it's probably the only one that works.

Open-source projects are getting the same lesson the rest of us are learning: AI doesn't eliminate the need for human judgment. It increases it. The more AI-generated content flows into any system, the more you need people who can tell the difference between something that looks right and something that is right.

We think about this constantly when building Cinevva's tools. The goal was never to remove human judgment from game creation. It's to let creative people focus their judgment on what matters: does this feel right, does this work, would someone enjoy this? The grunt work gets handled. The taste doesn't get automated.

Godot will figure this out. The engine is too important and the community too strong for it not to. But the pattern they're dealing with isn't going away. Every open-source project, every creative platform, every system that accepts contributions from the public is going to face this same question: how do you handle a world where producing something is nearly free but evaluating it isn't?

Related:

• Agentic AI code tools — responsible use of AI coding tools
• Frontier Open-Source Gen AI Models — the open-source models driving this shift
• AI controversy, trust, and the post-AI economy — the broader trust question around AI in creative work
• Web Game Engines Comparison — Godot and other engines affected by this trend

By Oleg Sidorkin, CTO of Cinevva

In February 2026, the following things happened within about three weeks of each other.

Unity's CEO went on record saying they'll demo prompt-to-game at GDC. Roblox shipped a 4D creation tool that generates interactive objects from text. Moonlake AI opened a beta for their Generative Game Engine backed by $30 million from Nvidia, Jeff Dean, and YouTube's co-founder. Phaser Editor v5 launched with AI built directly into the scene editor through MCP. And at least half a dozen startups I'd never heard of popped up on Product Hunt with some variation of "describe a game, we'll build it."

Roblox's VP of AI on their Cube foundation model and 4D creation

This isn't a complaint. It's an observation about timing.

Two years ago, when we were pitching what Cinevva does, VCs from Sequoia, Pear, Draper, and dozens of other firms told us the market wasn't there. B2C game creation? Indies don't pay for tools. You can't simplify game development without gutting capability. The standard deck of objections dressed up as market analysis.

Now the biggest names in gaming are spending hundreds of millions racing to build variations of the same thing they said couldn't work.

These tools are not the same thing

Here's what matters and what most coverage misses. "AI game creation" is an umbrella that hides fundamentally different products.

Text-to-demo tools generate something that looks impressive in a tweet. You type a prompt, get a playable thing, share the GIF. The output is real, but it's a demo. Getting from that demo to a game someone would play for an hour is a different problem entirely. Moonlake and some of the newer startups live here. They're solving the initial spark.

AI copilot tools sit inside an existing engine and help you work faster. Phaser Editor v5 with MCP does this. Ziva does this for Godot. They don't replace the development process, they accelerate it. You still need to understand what you're building. The AI handles the grunt work.

Platform-native AI creation is what Roblox is doing with 4D. The AI is embedded in the runtime. Objects don't just look right, they behave right because the generation model understands the platform's physics and interaction systems. The tradeoff: you're locked to that platform.

Full-stack AI game engines are trying to handle everything from concept to shipping. That's what Unity is promising for GDC. That's what we've been building at Cinevva for years. Describe what you want, iterate on what comes back, ship to web, mobile, desktop, Steam. The game you prompt is the game you publish.

Phaser Editor v5 integrates AI through MCP for scene-level assistance

The gap between demo and ship

Every tool in this space can generate a thing that runs. That part got easy fast. The hard part is everything after. Does the game feel good on a phone? Does it handle edge cases? Can you iterate on the music, the difficulty curve, the pacing? Can you ship it to five platforms from the same project? Does the AI understand what makes a game actually fun versus what makes a screenshot look cool?

Some of these announcements will turn into real products. Some will get a round of funding, generate nice demos, and quietly disappear when the "ship a real game" part proves harder than the "generate a prototype" part.

What I think is actually happening

The market validation we couldn't get in a Sand Hill Road meeting is now coming from the industry itself. When Unity and Roblox bet their roadmaps on AI creation, they're confirming what we've been building toward: the tools should adapt to how creative people think.

The race isn't about who announces first. It's about who ships something people actually use to make games they're proud of. We have thousands of people doing that on Cinevva today. A Breaker Belt was two people and three days. Cinevva Radio has 362 community-created tracks. That's the difference between promising to build the future and already living in it.

The competition is good. It means the market exists. We've known that for a while.

Related:

• Web Game Engines Comparison — how traditional engines compare on web output
• Frontier Open-Source Gen AI Models — the AI models powering game generation
• Agentic AI code tools — the AI copilot layer that accelerates development
• A Breaker Belt — a game built in three days with AI tools