OpenLoop 🔄

OpenLoop is a community initiative that aims to build a repeatable workflow for bringing Pseudo Lab projects to global audiences — connecting content discovery with opportunities to participate and contribute.

Why OpenLoop?

OpenRel = Open Source Relations

Based in South Korea, Pseudo Lab is home to a growing community of builders, researchers, and open-source contributors exploring AI and emerging technologies.

Across the community, projects continuously generate research, technical insights, experiments, and stories worth sharing.

OpenLoop aims to bring these projects and stories to wider audiences by building a repeatable global communication workflow.

By curating existing project content, adapting it for global audiences, and sharing it across social media platforms, we aim to create new entry points into the Pseudo Lab community.

Problem Statement

Our goal is to build a sustainable loop that helps global audiences discover, understand, and contribute to Pseudo Lab projects.

OpenLoop explores how existing project content can be transformed into accessible global content and, ultimately, create pathways from project discovery to open-source contribution.

Key Milestones

BUILD THE LOOP

• Review existing Pseudo Lab assets and collect references for global content
• Establish the foundation for a repeatable content workflow

CURATE THE LOOP

• Establish a content calendar and begin content curation
• Develop standardized formats for blog translation, LinkedIn posts, and visual content

LAUNCH THE LOOP

• Finalize and publish the first OpenLoop collection on LinkedIn
• Apply the standardized content and visual formats in practice

AMPLIFY THE LOOP

• Experiment with AI-powered workflows for blog translation, LinkedIn post creation, and visual generation
• Refine the workflow through repeated content creation
• Publish additional OpenLoop collections using the AI-powered workflow

SCALE THE LOOP

• Explore content and visual formats for X and Instagram
• Extend the AI-powered workflow to additional platforms
• Build toward a one-source, multi-platform content workflow

Expected Outcomes

Our goal is to build a sustainable loop that helps global audiences discover, understand, and contribute to Pseudo Lab projects.

By the end of the season, OpenLoop aims to establish:

• Content workflow connecting Blog → LinkedIn/X/Instagram → Global Audiences
• AI-powered workflow for content translation, adaptation, and visual generation
• Foundation for adapting one source of content across multiple global platforms

Weekly Roadmap

Every Monday | 19:00-20:00 KST | ONLINE / OFFLINE

Week	Stage	Date	Time	Format	Key Activities	Expected Outcome
W01	OT	2026.10.05	19:00–20:00 KST	OFFLINE	Project introduction & orientation	Team alignment
W02	BUILD	2026.10.12	19:00–20:00 KST	ONLINE	Review Pseudo Lab assets & collect LinkedIn references	Content references
W03	CURATE	2026.10.19	19:00–20:00 KST	ONLINE	Set content calendar & begin curation	Content plan
W04	CURATE	2026.10.26	—	BREAK	Break	—
W05	CURATE	2026.11.02	19:00–20:00 KST	ONLINE	Standardize blog, LinkedIn & visual formats	Unified content formats
W06	LAUNCH	2026.11.09	19:00–20:00 KST	OFFLINE	Finalize & publish first LinkedIn collection	Collection #1 published
W07	AMPLIFY	2026.11.16	19:00–20:00 KST	ONLINE	Experiment with AI-powered translation & post creation	AI workflow development
W08	AMPLIFY	2026.11.23	19:00–20:00 KST	ONLINE	Experiment with AI-powered visuals & content integration	AI workflow refinement
W09	AMPLIFY	2026.11.30	19:00–20:00 KST	ONLINE	Create & publish second and third collections	Collections #2–3 published
W10	SCALE	2026.12.07	19:00–20:00 KST	OFFLINE	Collect X/Instagram content references	Platform references
W11	SCALE	2026.12.14	19:00–20:00 KST	ONLINE	Standardize X/Instagram post & visual formats	Multi-platform formats
W12	SCALE	2026.12.21	19:00–20:00 KST	ONLINE	Extend AI workflow to X/Instagram	Multi-platform AI workflow
W13	SCALE	2026.12.28	19:00–20:00 KST	ONLINE	Review project results, workflow & learnings	Season retrospective

The OpenLoop Workflow

One source can become many paths for global discovery.

Pseudo Lab Projects
        ↓
Existing Project Content
        ↓
Curate & Select
        ↓
Translate & Adapt
        ↓
Standardize Content
        ↓
AI-Powered Workflow
        ↓
Global Discovery
        ↓
Project Contribution
        ↻

OpenLoop explores how existing Pseudo Lab content can be curated, adapted, and distributed through a repeatable workflow.

As the project progresses, we aim to use AI to streamline translation, post creation, and visual generation — making it easier to adapt a single source of content across multiple global platforms.

Team

OpenLoop encourages all members to contribute across content curation, translation, storytelling, design, publishing, AI workflow development.

Core Team

Role	Name	Focus
Builder	@Alice	Project direction & coordination
Runner	@name
Runner	@name
Runner	@name
Runner	@name
Runner	@name

How We Work

Our Principles

• Create Together — Share ownership across curation, writing, translation, design, publishing, and workflow development.

• Experiment & Learn — Test new formats and AI-powered workflows, learn from the results, and improve the next iteration.

• Build for Repeatability — Turn successful experiments into simple, reusable workflows that can continue beyond a single season.

Who We're Looking For

OpenLoop welcomes anyone interested in bringing open-source projects to global audiences through content curation, global engagement, and AI-powered workflow automation.

We're looking for people with:

• Interest in open-source communities and global engagement
• Working proficiency in English
• Experience or interest in content curation and storytelling
• Experience or interest in visual content design using Canva, Figma, or similar tools
• Familiarity with LinkedIn, X, Instagram content formats
• Interest in AI-powered workflow automation for content and marketing
• Willingness to collaborate, experiment, and contribute consistently

Archive

This section documents the content, experiments, and learnings created throughout OpenLoop.

Content & Resources

• 🔗 Repository: URL
• 💼 LinkedIn: URL
• 📝 Blog / Articles: URL

Content Collections

Collection	Featured Projects	Platform	Link
Collection #1	TBD	LinkedIn / Blog	URL
Collection #2	TBD	LinkedIn / Blog	URL
Collection #3	TBD	LinkedIn / Blog	URL

Project Log

Date	Update	Link
2026.10.05	Project Kickoff	URL
2026.11.09	Collection #1 Published	URL
2026.11.30	Collections #2–3 Published	URL
2026.12.28	Season Retrospective	URL

🌱 How to Engage

Let's OPEN the LOOP together.

There are many ways to participate in OpenLoop:

• 🧭 Builder — Help shape and coordinate the project
• 🏃 Runner — Contribute to curation, localization, content, design, and AI workflow experiments
• 👀 Open Participant — Join open sessions, follow the project, and share feedback
• 💻 Contributor — Discover featured Pseudo Lab projects and contribute directly through their GitHub repositories

❗️Join the community: Pseudo Lab Discord

❗️Communication channel: Discord #{{channel-name}}

Anyone interested in OpenLoop is welcome to join our open sessions.

You can participate by:

1. Joining our regular open sessions through the Pseudo Lab Discord
2. Participating during Magical Week
3. Meeting the OpenLoop team at Pseudo Lab community events
4. Exploring featured projects and contributing directly through GitHub

🙏 Acknowledgement

OpenLoop is developed as part of Pseudo Lab's Open Academy.

This project is made possible by the builders, runners, contributors, and project teams who openly share their work and ideas across the Pseudo Lab community.

Special thanks to everyone helping make Pseudo Lab projects more accessible to the global open-source community. Every contribution opens another path between project discovery and participation — and keeps the loop moving.

About Pseudo Lab 👋🏼

Pseudo Lab is a non-profit community focused on advancing machine learning and AI through open collaboration.

Built around the values of Sharing, Motivation, and Collaborative Joy, Pseudo Lab brings together builders, researchers, learners, and contributors to experiment, share knowledge, and create open-source projects together.

Contributors 😃

License 🗞

This project is licensed under the MIT License.