1. Project Overview
What is EverOS and why this campaign matters
EverOS is an open-source long-term memory operating system for AI agents, developed by the EverMind AI team. It is designed to help agents remember, accumulate experience, and reuse skills across sessions — rather than starting from scratch each time.
This campaign is focused on educating the AI builder community on why memory is becoming the next core layer of agent infrastructure, and driving hands-on exploration of the EverOS project.
2. Campaign Goal
What success looks like
We are looking for creators who can help introduce EverOS to technical audiences on X — including AI infrastructure builders, agent developers, ML researchers, and hands-on indie builders.
Audience actions we want to encourage:
3. What We Want You To Communicate
Your content should help your audience quickly understand at least one of these
Why memory is the bottleneck for the next generation of AI agents
Why EverOS is more than a toy demo — built as a serious open-source umbrella project
How builders can go from idea to memory-enabled agent faster with EverOS
What makes the EverCore / HyperMem architecture technically interesting
Why EverMind AI is a research team worth paying attention to in the agent memory space
4. Suggested Content Angles
Pick one angle that best fits your style and audience — you don't need to cover everything
Memory Is The Missing Layer For Agents
- Explain why current agents forget context, repeat mistakes, and fail to improve across sessions
- Position memory as the next core infra layer after reasoning and tooling
- Use EverOS as a concrete example of memory infrastructure for self-evolving agents
EverOS Is An Umbrella Project, Not Just A Repo
- Highlight architecture methods, benchmarks, and 25+ use cases
- Builders can learn by comparing methods and running real examples
- Recommended for project roundups, repo reviews, and builder walkthroughs
Fastest Path To A Learning Agent
- Show how builders can go from idea to running demo quickly
- Good formats: speed-runs, build-in-public posts, or quick setup demos
- If relevant, mention EverOS Cloud as a lower-friction setup path
The Architecture Behind EverCore / HyperMem
- Break down how the memory system works and why it's different from standard vector-memory approaches
- Good for deep-dive threads, paper walkthroughs, or architecture explainers
- Relevant hook: HyperMem was accepted to ACL 2026
Why EverMind AI Is Worth Watching
- Frame EverOS as part of EverMind AI's broader memory research line
- Relevant context includes MSA, HyperMem, and the team's long-term research direction
- Good for research-curation or ecosystem-watch style creators
5. Recommended Content Formats
6. Messaging Guidance
7. Required Mentions & CTA
- Mention or tag the official EverOS / EverMind AI X account(s)
- Include the EverOS GitHub repo link: github.com/EverMind-AI/EverOS
- Invite followers to give a star for this project
- If writing a thread, put the GitHub link in the second tweet
- Use hashtags #EverOS and/or #EverMindAI
Please also encourage your audience to do at least two of the following:
8. Draft Review Process
How to submit and get your draft approved
9. Brand Assets & References
Review before posting
📦 EverOS GitHub
Review relevant use cases, benchmarks, and architecture materials before posting.
github.com/EverMind-AI/EverOS
🌐 EverMind Website
Official project page with overview and resources.
evermind.ai/everos
🐦 Official X Account
@evermind — follow and tag in your posts.
x.com/evermind
⚠️ Disclosure
Paid partnership disclosure or #ad wording is not required.