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# Agent Architecture & Design
This page summarizes the intended design of Mycelium Agents, based on the public descriptions on the main site. The details may evolve as we approach the 2026 launch.
## HighLevel View
From the **Agent Design** and **Advantages** sections:
- Each agent **runs entirely inside your environment**.
- Agents **communicate peertopeer** across trusted nodes.
- Agents **access data locally** without exposing it to external providers.
- Agents are **portable**, moving with your infrastructure rather than with a single cloud vendor.
Conceptually:
```mermaid
graph TD
A[Your Devices & Nodes] --> B[Agent Runtime]
B --> C[Local Data & Tools]
B --> D[Mycelium Network]
D --> E[Other Agents & Nodes]
```
- The **runtime** executes agent logic.
- Agents load and store data through local backends (files, QSFS, databases).
- Communication uses **Mycelium Network** between environments.
## Core Properties
### Local Execution
From the "Local Execution" highlight:
> *“Agents run entirely inside your environment. Models, logic, and memory stay within your own trusted hardware, never behind thirdparty APIs.”*
Implications:
- You choose where agents run: laptop, homelab, edge cluster, or VDC.
- No requirement to send prompts or data to centralized AI APIs.
- Compliance and sovereignty become much easier to reason about.
### Mesh Connectivity
From the "Mesh Connectivity" highlight:
> *“They communicate peertopeer across trusted nodes. Agents form direct encrypted paths between environments, without relays or central servers.”*
This leverages **Mycelium Network** to:
- Give agents a global, encrypted address space.
- Enable crosssite coordination (home ↔ office ↔ cloud ↔ edge).
- Avoid central bottlenecks and single points of failure.
### Private Data Access
From the "Private Data Access" highlight:
> *“They use your data without sending it elsewhere. Your datasets, embeddings, and context never leave your boundaries.”*
Design goals:
- Agents can work directly against local file systems, QSFS, and internal services.
- Sensitive inputs and outputs remain in environments you choose.
- Remote calls (if any) are explicit and policycontrolled.
### Portability
From the "Portability" highlight:
> *“They move with you, not with a cloud provider. Agents follow your devices, networks, and workflows, remaining sovereign across every location.”*
Over time the framework aims to allow:
- Redeploying agents between different nodes and VDCs.
- Maintaining state while moving execution closer to data or users.
- Using heterogeneous infrastructure (homelab + hoster nodes + VDCs) as one fabric.
## Example Deployment Topologies
### SingleNode Local Agent
- Agent runtime on your workstation.
- Local data and tools only.
- Mycelium Network used for optional remote access.
### MultiNode Mesh
- Agents running on several nodes (e.g. laptop, homelab, hoster node).
- P2P coordination over Mycelium.
- Some agents specialized for data access, others for orchestration.
### VDCBacked Agent Cluster
- Runtime deployed into a **VDC** as a set of Kubernetes workloads.
- Agents expose services reachable only via Mycelium Network.
- QSFS and other Mycelium components used for storage.
## Security & Trust (Preview)
From the "Security Architecture" and related messaging:
- **Provable sovereignty** Assign workloads to trusted zones and verify state with cryptographic proofs.
- **Autonomous zerotrust** Identity, policy, and attestation enforced continuously.
- **Planetaryscale resilience** Mesh routing around failures, including regional outages.
As the framework evolves, expect more detailed specifications around:
- Identity & authentication between agents.
- Policy models for where and how agents may run.
- Auditability and observability of agent behavior.
## Status
The architecture described here is intentionally highlevel and forwardlooking. For timelines and how to prepare, see **[Overview](/ai-agent-framework/overview)** and **[Getting Ready for Agents](/ai-agent-framework/getting-ready)**.