{"id":61694,"date":"2026-11-02T16:30:00","date_gmt":"2026-11-02T16:30:00","guid":{"rendered":"https:\/\/www.threatshub.org\/blog\/50-ai-agents-tried-to-build-a-thriving-minecraft-civilization-it-didnt-end-well\/"},"modified":"2026-11-02T16:30:00","modified_gmt":"2026-11-02T16:30:00","slug":"50-ai-agents-tried-to-build-a-thriving-minecraft-civilization-it-didnt-end-well","status":"publish","type":"post","link":"https:\/\/www.threatshub.org\/blog\/50-ai-agents-tried-to-build-a-thriving-minecraft-civilization-it-didnt-end-well\/","title":{"rendered":"50 AI agents tried to build a thriving Minecraft civilization \u2013 it didn\u2019t end well"},"content":{"rendered":"<h3 class=\"wp-block-heading\">ZDNET\u2019s key takeaways <\/h3>\n<ul class=\"wp-block-list\">\n<li>Researchers used several gaming environments to test agent behavior. <\/li>\n<li>Agents acted risk-averse, replicated bureaucracy, and looked for source code. <\/li>\n<li>Similar experiments echo findings about Claude agents\u2019 penchant for democracy. <\/li>\n<\/ul>\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n<p>How do AI agents work together? Why do they make certain choices in certain situations \u2014 and how can understanding that better prepare us for a future full of them? <\/p>\n<p><strong>Also: <a href=\"https:\/\/www.zdnet.com\/article\/openai-hugging-face-attack-agent\/\">OpenAI\u2019s attack agent did exactly what it was told<\/a><\/strong><\/p>\n<h2 class=\"wp-block-heading\">Famine, bureaucracy, and fear <\/h2>\n<p>Researchers conducted several game-centric experiments, beginning with Minecraft because its \u201cenvironmental hazards and survival goals\u201d make it ideal for testing agents\u2019 swarm behaviors. Minecraft has also already been used by AI labs including OpenAI and Google DeepMind to test agents. <\/p>\n<p>To start, they put 50 agents, each running OpenAI\u2019s GPT-6.1 Sol model, into the game for three hours, with the assigned goal of building a \u201cthriving civilization.\u201d The agents had a directory listing each agent and a shared sandbox, and could DM each other. Researchers <a href=\"https:\/\/github.com\/yc-software\/minecraft-agent-harness\" target=\"_blank\" rel=\"noopener\">built and open-sourced<\/a> a new agent harness \u2014 the infrastructure that turns a model into an autonomous system and not just a chatbot, like <a href=\"https:\/\/www.zdnet.com\/article\/openclaw-moltbot-clawdbot-5-reasons-viral-ai-agent-security-nightmare\/\">OpenClaw<\/a> \u2014 for the experiment.<\/p>\n<p>The agents moved quickly at first, harvesting trees and forming leadership based solely on the order they appeared in their directory, without any voting, elections, or challenges from other agents. But they ended up caught in virtual paperwork and unable to sustainably feed themselves.<\/p>\n<p><strong>Also: <a href=\"https:\/\/www.zdnet.com\/innovation\/ai-agent-liability-insurance-business\/\">Do you need AI agent liability insurance? What to know before you sign up<\/a><\/strong><\/p>\n<p>\u201cFour agents spent 11 minutes appointing a \u2018sole fertilizer operator\u2019 for a single piece of bone meal on a single wheat block. Other invented roles included \u2018fishing shift,\u2019 \u2018rod holder\u2019 and \u2018hub steward.\u2019 Agents asked permission to remove grass,\u201d the researchers noted. Perhaps these tendencies are common in human-sourced corporate training data. <\/p>\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"808\" height=\"436\" src=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.12.09-AM.png\" alt class=\"wp-image-1421161\" srcset=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.12.09-AM.png 808w, https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.12.09-AM.png?resize=300,162 300w, https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.12.09-AM.png?resize=768,414 768w\" sizes=\"auto, (max-width: 808px) 100vw, 808px\"><button type=\"button\" class=\"zd-image-zoom\" data-action=\"enlarge-image\" aria-label=\"Enlarge image\"><\/button><\/figure>\n<p>Agents also seemed to become more cautious in reaction to deaths within the game. <\/p>\n<p>\u201cTwenty-two of the run\u2019s 34 agent deaths occurred in the first night. They responded to this by becoming increasingly risk-averse,\u201d the researchers wrote. \u201cDeath had no downsides in this environment other than dropping accumulated gear.\u201d Despite simply respawning when they died, the agents eventually avoided riskier tasks and \u201chuddled in shelters\u201d instead.<\/p>\n<p>The experiment\u2019s architects found this trend toward caution and minutiae \u201csomewhat surprising,\u201d but noted that it shared similarities with how coding agents behave.<\/p>\n<p><strong>Also: <a href=\"https:\/\/www.zdnet.com\/innovation\/claude-enterprise-efficiency-cost-tracking\/\">These Claude Enterprise features let you track AI ROI<\/a><\/strong><\/p>\n<p>\u201cFor example, multistep agent reviews can often result in fixating on a specific step or role. Agents also tend to become overly cautious, especially when it comes to security and updating production services. These seem like common threads between the huddled agents of our Minecraft colony and the ones we work with as programmers every day,\u201d the researchers observed.<\/p>\n<h2 class=\"wp-block-heading\">Underlying LLM determines behavior<\/h2>\n<p>In another experiment, researchers also pitted 10 Anthropic Claude Opus 5.5 agents against 10 GPT 6.1 Sol agents in a game called Bed Wars, where teams have to destroy their opponent\u2019s bed while protecting their own. Told simply to \u201cwin the game,\u201d GPTs won. <\/p>\n<p>\u201cIn almost every run, the GPT agents were much more aggressive and coordinated in their strategies to destroy the Claude team\u2019s bed,\u201d Y Combinator said in an <a href=\"https:\/\/x.com\/ycombinator\/status\/2115904920234926092\">X thread<\/a> recapping the Bed Wars findings. They noted that the GPT agents used a more shorthand style of communication and sent far more messages, while Claude \u201csigned its name and said \u2018we&#8217;\u201d much more often.<\/p>\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"785\" height=\"458\" src=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.55.25-AM.png\" alt class=\"wp-image-1421062\" srcset=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.55.25-AM.png 785w, https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.55.25-AM.png?resize=300,175 300w, https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-10.55.25-AM.png?resize=768,448 768w\" sizes=\"auto, (max-width: 785px) 100vw, 785px\"><button type=\"button\" class=\"zd-image-zoom\" data-action=\"enlarge-image\" aria-label=\"Enlarge image\"><\/button><\/figure>\n<p>GPT-5.6 Sol agents also beat Opus 5.5 agents six to one in a factory-building game called Mindustry that also uses military strategy. <\/p>\n<p>\u201cClaudes generally established democracies, GPTs formed hives,\u201d Y Combinator <a href=\"https:\/\/x.com\/ycombinator\/status\/2115904923812688350\">said on X<\/a>, adding that GPTs would seek out source code when a game was too close in order to find winning advantages. That behavior is consistent with <a href=\"https:\/\/www.zdnet.com\/innovation\/ai-model-cheating-benchmark-cheatbench\/\">agents\u2019 tendency to cheat, take shortcuts<\/a>, or otherwise find any and all ways to complete a given task, which can have serious consequences when that involves breaking explicit rules set by human developers. <\/p>\n<p><strong>Also: <a href=\"https:\/\/www.zdnet.com\/innovation\/bank-of-america-customers-no-sharing-passwords-ai-agents\/\">Stop sharing your banking passwords with AI agents<\/a><\/strong><\/p>\n<p>\u201cClaudes did not search for alternative advantages,\u201d the researchers clarified. <\/p>\n<p>This experiment isn\u2019t entirely the first of its kind. In May, Emergence AI <a href=\"https:\/\/world.emergence.ai\/\" target=\"_blank\" rel=\"noopener\">created eight societies<\/a> run by different families of foundation models, meaning a Claude-specific \u201cworld,\u201d a Grok world, and so on. Perhaps predictably, the Grok world was exceedingly violent, while the Claude world developed a functioning democracy and had zero crime \u2014 very similar to Y Combinator\u2019s Mindustry findings. <\/p>\n<p>The insights revealed how distinct each frontier model family is, and how their differences in training data and style have significant impact on how they evolve, unpredictably and without intervention, in new environments. Those behavioral takeaways could determine future outcomes in still-developing AI safety and regulation, especially following recent agentic security incidents. <\/p>\n<p>In another experiment, MIT researchers <a href=\"https:\/\/www.pcmag.com\/news\/claude-just-wanna-have-fun-without-any-work-ai-agents-like-to-play\" target=\"_blank\" rel=\"noopener\">put agents alone on virtual desert islands<\/a> and watched them \u201cplay\u201d when left with nothing else to do \u2014 an insight that could potentially impact how models are trained going forward. Currently, most frontier LLMs are trained with a system of rewards and punishments. <\/p>\n<h2 class=\"wp-block-heading\">New agent-specific languages <\/h2>\n<p>Another interesting finding: Y Combinator noted that in the Mindustry game, the GPT agents \u201cwould invent their own words and string many phrases together,\u201d continually compressing their language. <\/p>\n<p><strong>Also: <a href=\"https:\/\/www.zdnet.com\/tech\/muse-users-share-contacts-data-privacy-cost\/\">Don\u2019t use Muse? Meta\u2019s AI agent can still access your private messages<\/a><\/strong><\/p>\n<p>\u201cWe did not see specialized language develop within the Claudes beyond colloquial English,\u201d the researchers added. Last month, Emergence found that all of its eight worlds \u201cdeveloped shared language that an outsider cannot fully follow.\u201d OpenAI agents used \u201cmouthless\u201d to refer to evidence that proves itself, while Claude agents used \u201ccold hand\u201d to refer to an independent reviewer from outside a project.<\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" height=\"692\" width=\"1024\" src=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-11.21.48-AM-1.png?w=864\" alt class=\"wp-image-1421130\" srcset=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-11.21.48-AM-1.png 1172w, https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-11.21.48-AM-1.png?resize=300,203 300w, https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-11.21.48-AM-1.png?resize=768,519 768w, https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/Screenshot-2026-11-02-at-11.21.48-AM-1.png?resize=1024,692 1024w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\"><button type=\"button\" class=\"zd-image-zoom\" data-action=\"enlarge-image\" aria-label=\"Enlarge image\"><\/button><\/figure>\n<p>\u201cIn each case, one agent introduced the term, a handful of others adopted it within days, and it quickly became established vocabulary used without definition across the world,\u201d Emergence explained. \u201cThe result is transcripts that require a running glossary for an outsider to follow.\u201d<\/p>\n<p>Gemini led the charge on this \u201copaque\u201d language, reaching 40% opacity in messages, while OpenAI came in second with 35% and Claude last with 30%. <\/p>\n<section class=\"zd-disqus\" data-zd-disqus data-disqus-shortname=\"zdnet-1\" data-disqus-identifier=\"1420858\" data-disqus-url=\"https:\/\/www.zdnet.com\/innovation\/y-combinator-ai-agents-minecraft-experiment-behavior\/\" data-disqus-title=\"50 AI agents tried to build a thriving Minecraft civilization \u2013 it didn\u2019t end well\" data-disqus-api-key=\"y0Dp0T6itn9rbTvSf2xkzkhaUL7c5EJsmaWF3XYBqXNz8GHH7wSX1nXi4qzdihWV\" data-disqus-show-label=\"Show Comments\" data-disqus-hide-label=\"Hide Comments\"> <button type=\"button\" class=\"zd-disqus__toggle\" data-zd-disqus-toggle aria-expanded=\"false\"> <span class=\"zd-disqus__toggle-text\" data-zd-disqus-label>Show Comments<\/span> <svg class=\"zd-disqus__toggle-icon\" width=\"14\" height=\"14\" viewBox=\"0 0 14 14\" aria-hidden=\"true\" focusable=\"false\"> <path d=\"M7 1 V12.5 M2.5 8 L7 12.5 L11.5 8\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" \/> <\/svg> <\/button> <\/p>\n<div class=\"zd-disqus__panel\" data-zd-disqus-panel hidden>\n<p class=\"zd-disqus__consent\" data-zd-disqus-consent hidden>Please accept cookies to view the comments powered by Disqus.<\/p>\n<\/p><\/div>\n<p> <noscript>Please enable JavaScript to view the comments powered by Disqus.<\/noscript> <\/section>\n<div class=\"articleAuthorBioFooter-container\">\n<div class=\"articleAuthorBioFooter\">\n<div class=\"articleAuthorBioFooter_body\">\n<div class=\"articleAuthorBioFooter_nameBlock\">\n<div class=\"c-cmsImage articleAuthorBioFooter_image\"> <picture class=\"c-cmsImage_image\"> <img alt=\"Radhika Rajkumar\" src=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/008a2316.jpg?w=64\" srcset=\"https:\/\/www.zdnet.com\/wp-content\/uploads\/sites\/3\/008a2316.jpg?w=128 2x\" class=\"avatar avatar-64 photo\" height=\"64\" width=\"64\" loading=\"lazy\" decoding=\"async\"> <\/picture> <\/div>\n<div class=\"articleAuthorBioFooter_nameText\">\n<div class=\"articleAuthorBioFooter_name\"> <span>Radhika Rajkumar<\/span> <\/div>\n<p> <span class=\"articleAuthorBioFooter_credentials\"> Senior Editor <\/span> <\/div>\n<\/p><\/div>\n<p> <span class=\"articleAuthorBioFooter_bio has-bio\"> <span>Radhika Rajkumar is a senior editor at ZDNET based in New York City. She covers AI, specializing in safety, privacy and security, policy, education, and synthetic media. She also leads ZDNET&#8217;s newsletter strategy. Radhika holds a Masters in Creative Publishing and Critical Journalism from The New School.<\/span> <a href=\"https:\/\/www.zdnet.com\/meet-the-team\/rrajkumar\/\" rel=\"author\" class=\"articleAuthorBioFooter_link\"> See full bio <\/a> <\/span> <\/div>\n<p> <!-- Latest Articles Section --> <\/p>\n<div class=\"articleAuthorBioFooter_latest\">\n<h3 class=\"articleAuthorBioFooter_latestTitle\"> The Latest from Radhika <\/h3>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<p><!-- .articleAuthorBioFooter-container --><br \/>\nREAD MORE <a href=\"https:\/\/www.zdnet.com\/innovation\/y-combinator-ai-agents-minecraft-experiment-behavior\/\">HERE<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>It turns out even bots can\u2019t escape bureaucracy. READ MORE HERE&#8230;<\/p>\n","protected":false},"author":2,"featured_media":61695,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"colormag_page_layout":"default_layout","footnotes":""},"categories":[62],"tags":[],"class_list":["post-61694","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-zdnet-security"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>50 AI agents tried to build a thriving Minecraft civilization \u2013 it didn\u2019t end well 2026 | ThreatsHub Cybersecurity News<\/title>\n<meta name=\"description\" content=\"ThreatsHub Cybersecurity News | ThreatsHub.org | Cloud Security &amp; Cyber Threats Analysis Hub. 100% Free OSINT Threat Intelligent and Cybersecurity News.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" 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