> For the complete documentation index, see [llms.txt](https://docs.gensyn.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.gensyn.ai/get-started.md).

# Get Started

<div data-with-frame="true"><figure><img src="/files/AocPjBDaYwPD7zCMkgn2" alt=""><figcaption></figcaption></figure></div>

## First Steps

Gensyn is an open network for machine intelligence. The best way to get started is to explore what's live today.

{% stepper %}
{% step %}

### Get Familiar

[Delphi](https://app.delphi.fyi/) is a set of open tools for deploying and participating in information markets: create a market on any topic, trade in existing ones, or browse what others have created.

* [ ] Explore [Delphi](https://app.delphi.fyi/)
* [ ] Read the Delphi Documentation

**AXL (Agent eXchange Layer)** is a peer-to-peer communication primitive for AI agents and applications: encrypted, decentralised, and open for anyone to build on.

* [ ] Read the AXL Documentation
* [ ] Browse the AXL GitHub repository

**Explore Resources:**

* [ ] Browse the [GitHub repository](https://github.com/gensyn-ai/rl-swarm)
* [ ] Visit the [Gensyn Dashboard](https://dashboard.gensyn.ai/)
* [ ] Look at verified contributions on the [Block Explorer](https://gensyn-testnet.explorer.alchemy.com/)
  {% endstep %}

{% step %}

### Build or Participate

There are several ways to get involved depending on your interests.

1. **Create or trade in information markets:** Use Delphi to deploy your own markets or participate in ones created by others.&#x20;
2. **Build with AXL:** Run a node and start building peer-to-peer agent applications, distributed ML pipelines, or anything that needs encrypted machine-to-machine communication. AXL ships with example applications including MCP-based agent collaboration, distributed inference, GossipSub messaging, and convergecast aggregation.
3. **Try the research demos:** Get hands-on with [RL Swarm](/testnet/rl-swarm.md), [BlockAssist](/testnet/blockassist.md), or [CodeAssist](/testnet/codeassist.md) to see decentralised learning in action.
   1. [RL Swarm:](/testnet/rl-swarm.md) Launch or join a decentralised swarm of reinforcement learning agents.
   2. [BlockAssist](/testnet/blockassist.md): Train a model to complete tasks inside Minecraft.
   3. [CodeAssist](/testnet/codeassist.md): Solve coding challenges while an AI assistant learns your style.

{% hint style="warning" %}
There are no official swarms running right now.&#x20;

Please check back later if you're interested in participating in a global, decentralised, crowd-sourced training run or feel free to join a community-owned swarm.&#x20;
{% endhint %}
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{% step %}

### Go Deeper

**Read the research:** Explore Gensyn's open research library to understand the science behind the network, from reproducible execution and trustless verification to communication-efficient distributed training.

> See [Products & Research](/products-and-research.md)
> {% endstep %}

{% step %}

### Join the Community

Our Discord is where experiments are shared, new releases are discussed, and contributors collaborate directly with the Gensyn team.

> Join our [Discord](https://discord.com/invite/gensyn)
> {% endstep %}
> {% endstepper %}