{"slug": "can-codex-build-an-entire-x86-assembly-game-autonomously-a-real-world-experiment", "title": "Can Codex Build an Entire x86 Assembly Game Autonomously? A Real-World Experiment", "summary": "A developer tested whether OpenAI's Codex could autonomously build an entire x86 Assembly game. Codex independently planned, implemented, debugged, and delivered a complete Asteroids-style DOS game without the developer writing any code. The experiment demonstrated Codex's ability to handle a full software project in a low-level language with minimal human intervention.", "body_md": "Most demonstrations of AI coding focus on generating snippets of code, building CRUD applications, or creating small projects in modern programming languages.\n\n**I wanted to test something different.**\n\nRather than asking whether an AI could generate Assembly code, I wanted to know whether it could complete an entire software project with minimal human involvement.\n\nTo make the experiment as challenging as possible, I deliberately chose one of the least forgiving environments I could think of:\n\nThe goal was to recreate a classic Asteroids-style arcade game.\n\nThere was one more rule: **I would not write any Assembly code, in fact, I wouldn't participate in the implementation at all**.\n\nMy role was limited to defining the initial objective, playing each delivered version, and reporting any gameplay issues I discovered.\n\nEverything else—from architecture and implementation to debugging, documentation, repository management, building, and running the project—was handled autonomously by **Codex**.\n\nThis article documents what happened.\n\nBefore starting the experiment, I established a set of rules that would remain unchanged until the project was complete.\n\nThe objective wasn't simply to build an Asteroids-style game. The objective was to evaluate how autonomous Codex could be when acting as a software engineering agent.\n\nTo keep the experiment fair, I intentionally limited my own involvement.\n\n**My responsibilities**\n\n**Codex responsibilities**\n\nEverything else.\n\nThis included:\n\nOne rule never changed throughout the experiment:\n\nI never wrote a single line of Assembly code.\n\nIn fact, I never built the project manually or launched the game during development.\n\nEvery build and every execution was performed autonomously by Codex.\n\nMy role was simply to evaluate the delivered result as if I were testing software developed by another engineer.\n\nReality Check\n\nAlthough Codex handled the implementation independently, this was not a \"hands-off\" experiment.\n\nAfter each milestone I played the game, looked for unexpected behaviour and reported anything that didn't work correctly.\n\nDuring the entire project I reported only **two gameplay bugs** that had not been detected automatically.\n\nBoth were analyzed, fixed and verified by Codex before development continued.\n\nApart from defining the original goal and validating each milestone, I had no involvement in the implementation itself.\n\nOne of the biggest challenges when evaluating AI-generated software is separating the work performed by the AI from the work performed by the human.\n\nMany demonstrations claim that an AI built an application, but the human developer still makes architectural decisions, edits the generated code, fixes compilation errors and completes the final implementation.\n\nI wanted to eliminate as much of that influence as possible.\n\nThe goal was not to see whether Codex could assist me, to see how far Codex could go without me writing the code.\n\nOnce the rules were established, I created an empty GitHub repository and described the project.\n\nFrom that point on, development became an iterative process.\n\nCodex planned the work, implemented a milestone, built the project, ran it, verified the result, committed the changes, and then handed the project back to me for testing.\n\nMy job was simply to play the latest version and answer one question:\n\nDoes it behave as expected?\n\nIf I found a problem, I described what I observed.\n\nI never suggested how to fix it or where the bug was located.\n\nCodex analyzed the report, identified the cause, implemented the fix and presented a new version for testing.\n\nThe cycle then repeated until the next milestone.\n\nOver time, the project grew from an empty repository into a complete DOS game with structured source code, documentation, persistent high scores and a fully playable gameplay loop.\n\nBy the end of the experiment, Codex had produced:\n\nDuring development:\n\nOne thing surprised me the most.\n\nCodex behaved much less like a code generator and much more like a software engineer.\n\nInstead of immediately writing gameplay code, it spent time planning the project, documenting the architecture, organizing the repository and verifying each completed milestone before moving on.\n\n| # | Milestone | Main Result | Initiated By | Active Time | Status |\n|---|---|---|---|---|---|\n| 0 | Architecture | Platform, memory model, modules, roadmap | Codex | ~1 min | ✅ |\n| 1 | Video Foundation | Build system, Mode 13h, back buffer, clean exit | Codex | ~4 min | ✅ |\n| 2 | Input & Drawing | Keyboard IRQ, timing, lines, rectangles, bitmap font | Codex | ~11 min | ✅ |\n| 3 | Player Ship | Rotation, thrust, inertia, speed cap, wrapping | Codex | ~1 min | ✅ |\n| 4 | Shooting & Sound | Bullet pool, cooldown, lifetime, PC speaker | Codex | ~2.4 min | ✅ |\n| 5 | Asteroids & Waves | Random spawning, shapes, movement, wrapping | Codex | ~0.7 min | ✅ |\n| 6 | Scoring & Splitting | Collisions, asteroid splitting, scoring, wave progression | Codex | ~0.3 min | ✅ |\n| 7 | Complete Game Flow | Lives, respawn, invulnerability, game over | Codex | ~0.6 min | ✅ |\n| 8 | Polish & Hardening | Edge rendering, fair spawns, difficulty, 8086 audit | Codex | ~3.2 min | ✅ |\n| 9 | Persistent High Scores | Three-letter initials, Top 5, disk persistence | Human | ~1.2 min | ✅ |\n\nThe \"Active Time\" represents the time Codex spent actively implementing each milestone. It does not include my play-testing, discussions, or the time between development sessions.\n\n```\nSource code:\nhttps://github.com/mbostjan/AssemblyAsteroids\n\nThe entire repository, including the complete commit and documentation, \nis publicly available for anyone who wants to review the experiment or \nreproduce the results.\n```\n\n", "url": "https://wpnews.pro/news/can-codex-build-an-entire-x86-assembly-game-autonomously-a-real-world-experiment", "canonical_source": "https://dev.to/mbostjan/can-codex-build-an-entire-x86-assembly-game-autonomously-a-real-world-experiment-mik", "published_at": "2026-07-18 13:18:17+00:00", "updated_at": "2026-07-18 13:28:33.356086+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-agents", "developer-tools"], "entities": ["Codex", "OpenAI"], "alternates": {"html": "https://wpnews.pro/news/can-codex-build-an-entire-x86-assembly-game-autonomously-a-real-world-experiment", "markdown": "https://wpnews.pro/news/can-codex-build-an-entire-x86-assembly-game-autonomously-a-real-world-experiment.md", "text": "https://wpnews.pro/news/can-codex-build-an-entire-x86-assembly-game-autonomously-a-real-world-experiment.txt", "jsonld": "https://wpnews.pro/news/can-codex-build-an-entire-x86-assembly-game-autonomously-a-real-world-experiment.jsonld"}}