FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.
A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.
The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.
Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.
Agents interact with FLE through a REPL pattern:\n1. They observe the world (seeing the output of their last action)\n2. Generate Python code to perform their next action\n3. Receive detailed feedback (including exceptions and stdout)
We provide two main evaluation settings:\n- Lab-play: 24 structured tasks with fixed resources\n- Open-play: An unbounded task of building the largest possible factory on a procedurally generated map
We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).
The code is available at https://github.com/JackHopkins/factorio-learning-environment.
You'll need:\n- Factorio (version 1.1.110)\n- Docker\n- Python 3.10+
The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.
We would love to hear your thoughts and see what others can do with this framework!"},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Factorio Learning Environment \u2013 Agents Build Factories"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://jackhopkins.github.io/factorio-learning-environment/"}},"_tags":["story","author_noddybear","story_43331582","show_hn"],"author":"noddybear","children":[43331679,43331782,43331833,43331881,43331894,43331903,43331920,43331931,43331962,43331980,43331994,43332022,43332084,43332121,43332218,43332245,43332331,43332346,43332479,43332483,43332539,43332931,43332962,43333045,43333312,43333333,43334138,43334194,43334233,43334329,43334576,43334618,43334620,43334839,43335216,43335404,43335537,43335590,43335768,43335980,43336487,43336510,43337129,43337878,43338731,43341652,43342548,43343680,43346300],"created_at":"2025-03-11T12:02:02Z","created_at_i":1741694522,"num_comments":209,"objectID":"43331582","points":749,"story_id":43331582,"story_text":"I'm Jack, and I'm excited to share a project that has channeled my Factorio addiction recently: the Factorio Learning Environment (FLE).
FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.
A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.
The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.
Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.
Agents interact with FLE through a REPL pattern:\n1. They observe the world (seeing the output of their last action)\n2. Generate Python code to perform their next action\n3. Receive detailed feedback (including exceptions and stdout)
We provide two main evaluation settings:\n- Lab-play: 24 structured tasks with fixed resources\n- Open-play: An unbounded task of building the largest possible factory on a procedurally generated map
We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).
The code is available at https://github.com/JackHopkins/factorio-learning-environment.
You'll need:\n- Factorio (version 1.1.110)\n- Docker\n- Python 3.10+
The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.
We would love to hear your thoughts and see what others can do with this framework!","title":"Show HN: Factorio Learning Environment \u2013 Agents Build Factories","updated_at":"2026-05-26T16:19:40Z","url":"https://jackhopkins.github.io/factorio-learning-environment/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"bpierre"},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["factory"],"value":"The Pixel Factory"},"url":{"matchLevel":"none","matchedWords":[],"value":"http://acko.net/files/gltalks/pixelfactory/online.html#0"}},"_tags":["story","author_bpierre","story_10180608"],"author":"bpierre","children":[10180750,10180780,10180857,10180859,10180870,10180992,10181052,10181085,10181144,10181260,10181305,10181345,10181573,10181594,10181628,10182574,10182699,10182865,10182932,10182980,10183702,10183858,10183941,10184045,10192249,10197657],"created_at":"2015-09-07T08:55:04Z","created_at_i":1441616104,"num_comments":47,"objectID":"10180608","points":739,"story_id":10180608,"title":"The Pixel Factory","updated_at":"2024-09-19T22:15:22Z","url":"http://acko.net/files/gltalks/pixelfactory/online.html#0"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"HieronymusBosch"},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["factory"],"value":"Intel's $20B Ohio factory could become world's largest chip plant"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://www.reuters.com/technology/intel-plans-new-chip-manufacturing-site-ohio-report-2022-01-21/"}},"_tags":["story","author_HieronymusBosch","story_30025695"],"author":"HieronymusBosch","children":[30026068,30026082,30026096,30026111,30026117,30026138,30026202,30026217,30026358,30026533,30026593,30026680,30026734,30026810,30026854,30027184,30027401,30027490,30027498,30027746,30027812,30027858,30028219,30028267,30028329,30028384,30029310,30029578,30029623,30029732,30029981,30030550,30030988,30031048,30031493,30031593,30032183,30032606,30033067,30033809,30035699],"created_at":"2022-01-21T16:21:45Z","created_at_i":1642782105,"num_comments":603,"objectID":"30025695","points":708,"story_id":30025695,"title":"Intel's $20B Ohio factory could become world's largest chip plant","updated_at":"2026-07-04T08:48:10Z","url":"https://www.reuters.com/technology/intel-plans-new-chip-manufacturing-site-ohio-report-2022-01-21/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"ytch"},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["factory"],"value":"TSMC to build second Japan chip factory"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://finance.yahoo.com/news/tsmc-build-second-japan-chip-105111276.html"}},"_tags":["story","author_ytch","story_39273830"],"author":"ytch","children":[39288342,39288453,39288535,39288626,39288705,39288994,39289167,39289376,39289612,39290553,39290624,39291463,39291772,39291792,39291991,39292971,39292974,39293303,39295071,39295090,39295941,39297586,39304222],"created_at":"2024-02-06T13:12:36Z","created_at_i":1707225156,"num_comments":466,"objectID":"39273830","points":634,"story_id":39273830,"title":"TSMC to build second Japan chip factory","updated_at":"2026-04-11T01:40:23Z","url":"https://finance.yahoo.com/news/tsmc-build-second-japan-chip-105111276.html"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"latexr"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["factory"],"value":"Optifye.ai is a dystopian company backed by Y Combinator. They\u2019re using AI to further dehumanise and abuse individual factory workers and treat them like disposable automatons.
See a now deleted post where they show how it works:
https://hachyderm.io/@YvanDaSilva/114063748264591929
The founders look to be a couple of rich kids with little world and work experience:
> We\u2019re CS grads from Duke and because our families run manufacturing companies (\u2026)
They also display a profound lack of empathy by bragging about lowering stress for rich company owners, which they do by increasing the stress of everyone who works for them:
> Know any manufacturing company owners?
> Let us know at founders@optifye.ai, and we\u2019ll help them drop their cortisol levels :)
https://www.ycombinator.com/companies/optifye-ai
This is the AI world we all know is coming, brought to you by Y Combinator investors and founders. It doesn\u2019t \u201cbenefit humanity\u201d, it just serves to \u201cput you in your place\u201d."},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["factory"],"value":"Tell HN: Y Combinator backing AI company to abuse factory workers"}},"_tags":["story","author_latexr","story_43170850","ask_hn"],"author":"latexr","children":[43170866,43171022,43171056,43171209,43171257,43171276,43171286,43171306,43171307,43171315,43171321,43171329,43171360,43171368,43171369,43171378,43171394,43171419,43171431,43171452,43171561,43171569,43171573,43171593,43171625,43171699,43171792,43171824,43172198,43172357,43172554,43173884,43174226,43174230,43174274,43176048,43177510,43179822,43180707,43180962,43181174,43181299,43182516,43183449],"created_at":"2025-02-25T12:04:00Z","created_at_i":1740485040,"num_comments":188,"objectID":"43170850","points":631,"story_id":43170850,"story_text":"Optifye.ai is a dystopian company backed by Y Combinator. They\u2019re using AI to further dehumanise and abuse individual factory workers and treat them like disposable automatons.
See a now deleted post where they show how it works:
https://hachyderm.io/@YvanDaSilva/114063748264591929
The founders look to be a couple of rich kids with little world and work experience:
> We\u2019re CS grads from Duke and because our families run manufacturing companies (\u2026)
They also display a profound lack of empathy by bragging about lowering stress for rich company owners, which they do by increasing the stress of everyone who works for them:
> Know any manufacturing company owners?
> Let us know at founders@optifye.ai, and we\u2019ll help them drop their cortisol levels :)
https://www.ycombinator.com/companies/optifye-ai
This is the AI world we all know is coming, brought to you by Y Combinator investors and founders. 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