Making an Indie Game with Claude: A Full Record of AI-Assisted Development

The Birth of an Indie Game Built with AI

In the world of indie game development, solo developers often have to wear many hats: programmer, artist, narrative designer, level designer, and even DevOps engineer. Recently, a Reddit developer shared the latest progress on their game No Name Squish Game, built with the help of Claude and other AI tools, offering us a vivid case study of how "AI + indie development" actually works in practice.

The game features a cast of soft, squishy blobs that deform when squeezed. The developer ported an early demo to a web version and wrapped it in a PWA (Progressive Web App) shell, letting players jump right in from their browser without downloading anything. The blob characters' "squish and deform" effect involves simulating Soft Body Dynamics — traditionally implemented using spring-mass models or Position-Based Dynamics (PBD) algorithms that require real-time calculation of constraints between numerous nodes every frame. However, with simplified APIs from lightweight 2D physics engines like Matter.js and Planck.js, combined with visual deformation effects at the Shader level, developers can achieve a satisfying "jelly-like" feel on the web at a relatively low performance cost — a technical choice that fits perfectly within a PWA game's performance budget.

PWA Makes "Click and Play" Possible

The technical choice behind this port deserves attention. Instead of going the traditional native app distribution route, the developer chose the PWA approach.

PWA (Progressive Web App) is a set of web technology standards that Google began actively promoting around 2015. It uses Service Workers for offline caching, Web App Manifest for an "add to home screen" near-native experience, and supports push notifications among other features. For game developers, PWA's biggest advantage is bypassing App Store and Google Play review processes and their 30% platform fees, while retaining an immersive experience close to native apps. In recent years, as underlying technologies like WebAssembly and WebGPU have matured, the performance bottleneck for web games is being rapidly broken, further highlighting PWA's value as a distribution shell.

For this specific game, the PWA approach delivers several clear advantages:

• Zero installation barrier: Players can play by simply clicking a link, avoiding the friction of app store reviews and download/install processes;
• Cross-platform compatibility: Best experience on desktop, but also runs on mobile (landscape mode + built-in touch controls);
• Rapid iteration: The web version makes it easy for the developer to push updates anytime, ensuring players always have access to the latest content.

The developer was also upfront that this web version "isn't an optimized final release" — it exists solely to let people quickly try the game, not as the definitive web or mobile game experience. This "get it running first and collect feedback" mindset is a textbook example of lean development. The Lean Startup methodology was systematically articulated by Eric Ries in his 2011 book of the same name, with the core idea of reducing product risk through rapid Build-Measure-Learn cycles. In the gaming industry, this philosophy gave rise to a "playable prototype first" development culture — validate whether the core gameplay is fun with a Minimum Viable Product (MVP) before gradually adding content and polish. AI tools have compressed the MVP build cycle from weeks to days or even hours, making this methodology far more practical for indie developers.

What Role Does AI Play in the Indie Game Development Process?

From the title "Made with Claude + other AI," it's clear that Anthropic's Claude was one of the core tools powering this project. While the original post didn't break down AI's contribution at every stage, we can reasonably infer AI's value based on common indie development pain points:

Coding Acceleration: Lowering the Implementation Barrier

For indie developers lacking a full development team, AI coding assistants can significantly lower the barrier to code implementation — from game logic and physics collision to PWA packaging configuration, tools like Claude can provide usable code scaffolding, letting developers focus their energy on creativity and gameplay design.

Claude, developed by Anthropic, is one of the leading products in the large language model space, forming a three-way competition with OpenAI's GPT-4o and Google's Gemini in code generation capabilities. Claude's distinguishing features include its long context window (supporting up to 200K tokens) and relatively careful output style, which make it particularly strong at handling large codebases and understanding complex project contexts. For indie game developers, Claude can do more than generate code snippets — it can serve as an "architecture consultant," helping developers evaluate technical approaches, debug issues, and even write technical documentation. Since 2024, Anthropic's Claude Artifacts feature has even allowed the generation of previewable front-end interfaces directly within conversations, further lowering the barrier to web game prototyping.

Content and Asset Generation: Rapidly Populating the Game World

The developer mentioned that "a lot of assets are still being made" and that they're designing a new character — "two blobs in a trenchcoat pretending to be one person, thinking nobody can tell." This kind of humor-filled character design, combined with AI-assisted art and copy generation, enables small teams to quickly populate game content.

AI generation of game assets has already formed a relatively mature toolchain. For 2D art, Midjourney, Stable Diffusion, and DALL-E 3 can quickly generate concept art and character design drafts, which can be converted to game-ready vector assets using tools like Vectorizer. In the pixel art domain, specialized tools like Aseprite with AI plugins can also accelerate sprite creation. However, it's worth noting that AI-generated art assets often suffer from style consistency issues — assets generated in different batches may show variations in color tone, line weight, and lighting direction, still requiring manual adjustment for uniformity. This explains why the developer mentioned "a lot of assets are still being made" — AI accelerates individual asset production, but integrating them into a stylistically cohesive game world still requires significant human oversight.

Story and Copy Polishing: AI Is the Starting Point, Not the Finish Line

Interestingly, the developer specifically noted: "The story still needs polishing, and the dialogue is being rewritten in my own voice." This reveals a key attitude — AI is the starting point, not the finish line. AI-generated first drafts provide efficiency, but the developer still insists on re-polishing copy with their personal style, preserving creative uniqueness. This is precisely the healthiest practice for AI-assisted creation today: let AI handle the heavy lifting of initial work, while humans maintain control over the final taste and tone.

What This Case Tells Us About AI Indie Game Development Today

There's Still a Gap Between "Playable" and "Fun"

The developer is remarkably clear-eyed, listing a series of to-do items: the storyline needs completion, biome layouts will be adjusted, a huge backlog of assets needs to be added, and the game will eventually take players all the way to "outer space."

The concept of biomes originally comes from ecology, referring to large ecological regions with similar climate conditions and biological communities, such as tropical rainforests, deserts, and tundra. In game design, biome systems are widely used to build world diversity — Minecraft is the most classic example, using procedural generation to divide the world into dozens of different biomes, each with unique terrain, vegetation, creatures, and resource distribution. For this blob game, a biome system means players will experience regions with drastically different visual styles and gameplay mechanics as they progress, all the way to the developer's mentioned "outer space" — a narrative ambition in spatial scope that hints at a quite ambitious level structure.

This shows that even with AI assistance, taking a complete game from prototype to finished product still requires extensive human design decisions and iterative polishing. AI compresses implementation costs but doesn't eliminate the thinking required for design.

Community Feedback-Driven Agile Development

The core purpose of this post was actually soliciting feedback. The developer hopes players will provide "brutally honest" opinions on controls and feel, points of confusion, moments that made them smile, and performance across different devices. This approach of putting a half-finished product in front of the community early and using real user feedback to drive iteration pairs perfectly with AI's rapid prototyping capabilities — quickly build a playable version, quickly collect feedback, quickly course-correct.

This development model has deep roots in the indie game world. Since Steam's Early Access program launched in 2013, countless indie games have built loyal player communities during development, with Hades and Baldur's Gate 3 being prime examples of success through this model. Reddit, as a major hub for game developer communities, sees developers sharing prototypes and soliciting feedback daily in subreddits like r/indiegaming and r/gamedev. AI tools make the "build" phase of this feedback loop faster, thereby accelerating the entire cycle.

Creativity and Warmth Remain the Soul of Games

Whether it's the "squishy, adorable creatures" or the whimsical concept of "two blobs in a trenchcoat pretending to be one person," these smile-inducing ideas are what truly give this game its charm. AI can help developers turn ideas in their heads into playable reality faster, but the ideas themselves — and that warmth of humor — still come from the creator.

Conclusion: AI Makes Solo Game Development No Longer Out of Reach

No Name Squish Game may be just one unremarkable project among many AI-assisted developments, but the trend it reflects is worth paying attention to: AI is dramatically lowering the technical barriers to independent creation, making "one person making a game" shift from grueling to feasible.

Looking back at the evolution of game development tools, this trend of "lowering barriers" has actually been happening all along. From the 1990s when developers had to program directly against hardware, to the 2000s when the proliferation of Unity and Unreal engines enabled individual developers to create 3D games, to the 2010s when lightweight engines like GameMaker and Godot allowed complete beginners to get started — each tool revolution spawned a new wave of indie games. AI-assisted development is very likely the latest link in this historical chain, lowering not just the programming barrier but simultaneously compressing costs across art, copywriting, testing, and multiple other domains — achieving a full-stack reduction in barriers to entry.

More importantly, this developer demonstrates an ideal model of human-AI collaboration — using AI to speed up development, PWA to lower the barrier to trying the game, community feedback to calibrate direction, while insisting on rewriting dialogue in their own voice and preserving creative personality. In an era of increasingly powerful AI tools, how to leverage AI without losing yourself — this little game about squishy blobs offers a warm and clear-headed answer.