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What is openopc?

hkuds/openopc — explained in plain English

Analysis updated 2026-05-18

955PythonAudience · developerComplexity · 4/5LicenseSetup · moderate

In one sentence

A Python framework that assembles a team of AI agents into a virtual company, assigning them roles and tasks to complete real projects.

Mindmap

mindmap
  root((OpenOPC))
    What it does
      Builds an AI company
      Assigns roles and tasks
      Learns across projects
    Tech stack
      Python
      React
      Phaser
    Stages
      Self Built staffing
      Self Run execution
      Self Grown learning
    Use cases
      Investment research
      Video production
      Software MVP
    Interfaces
      CLI
      Office UI

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Assemble an AI team to research and draft an investment memo or market map.

USE CASE 2

Have an AI team plan, script, and produce a short video from a single goal.

USE CASE 3

Build a software MVP by letting an AI team break the work into assigned tasks.

USE CASE 4

Watch an AI company's progress on a kanban board through the browser office interface.

What is it built with?

PythonReactPhaser

How does it compare?

hkuds/openopczai-org/scailasz798838958/freeagentidentity
Stars955955974
LanguagePythonPythonPython
Setup difficultymoderatehardmoderate
Complexity4/55/53/5
Audiencedeveloperresearcherdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires Python 3.10 or newer plus configuring access to an LLM to power the AI employees.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

So what is it?

OpenOPC is a Python project that lets you build a small company made entirely of AI agents, each one filling a specific job role, working together toward a goal you set. The idea is that instead of hiring people, the system automatically assembles a team of AI employees, assigns them tasks, and coordinates their work, learning from each completed project to improve future ones. The system works in three stages. First, given a goal, it drafts an organization chart, figuring out what roles are needed and how they report to each other, then a recruiter agent either reuses an AI employee from a past project or brings in a new one from a pool of available roles. Second, once the team exists, a manager style process breaks the work into individual items, assigns them, and reviews the results, deciding whether to accept, redo, or escalate each piece. Work that does not depend on other tasks can run at the same time, while dependent work waits its turn. If something blocks progress, the system first tries to resolve it inside the team, and if it is beyond the team's authority, it is passed up to the human who owns the project for a decision. Third, after a run finishes, the system attributes outcomes to the specific roles responsible for them, rather than crediting or blaming the whole company at once, and turns what it learned into longer term organizational knowledge. OpenOPC covers a wide range of use cases across nine areas, including AI development, software engineering, financial investment research, sales, video and content production, e-commerce, accounting, education, and various industry specific assistants. It includes both a command line interface and a browser based office style interface built with React and a game engine called Phaser, where you can watch the AI team's kanban board and activity in something like a virtual office. The project is released under the MIT license. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1
Help me set up OpenOPC and give it a goal to build a simple software MVP.
Prompt 2
Explain how OpenOPC decides which AI employee gets reused versus hired fresh for a role.
Prompt 3
Show me how to use the OpenOPC CLI versus the Office UI.
Prompt 4
Walk me through how OpenOPC escalates a blocked task to a human decision.

Frequently asked questions

What is openopc?

A Python framework that assembles a team of AI agents into a virtual company, assigning them roles and tasks to complete real projects.

What language is openopc written in?

Mainly Python. The stack also includes Python, React, Phaser.

What license does openopc use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is openopc to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is openopc for?

Mainly developer.

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