Roadmap
AVM Strategic Roadmap
Last updated
AVM Strategic Roadmap
Last updated
Overview: This document details the strategic roadmap for the AVM protocol, outlining the path from MVP to global agent-native marketplace.
This roadmap defines a five-phase plan for the AVM protocol, reflecting both present status and long-term strategic vision. Phase 1 covers foundational deliverables—MVP dashboard and beta SDK release. Subsequent phases focus on token launch, decentralization, scalable global adoption, and the final stage of agent-native execution infrastructure.
AVM advances through a structured timeline to establish robust compute capabilities, expand functionality, decentralize network operations, and scale global adoption. The protocol’s MVP dashboard is imminent and the SDK is live for beta testers; the token launch is scheduled for Phase 2. The final phase outlines the long-term goal of cementing AVM as the global compute backbone for autonomous agents.
1
Foundation
Q3 2025
MVP dashboard + SDK
2
Expansion
Q4 2025
1,000 developers
3
Decentralization
Q1-Q2 2026
Permissionless node network, 100 nodes
4
Scaling
Q3-Q4 2026
10,000 users, ecosystem integration
5
Ascension
2027 – Q3 2028
Global agent-native marketplace
✅ Completed:
Python virtual machine deployment
TypeScript virtual machine deployment
Tools reuse infrastructure
Reusable sandboxes (permanent tools)
Core execution capabilities and SDK for beta testers
Initial web dashboard for monitoring compute tasks
MCP integrations with leading AI automation platforms
🔄 In Progress:
Security, monitoring, and developer support infrastructure
PHP virtual machine deployment
Go virtual machine deployment
Sandboxes Marketplace: Developers can now monetize their custom toolkits
Real-time analytics and reporting dashboards
Ecosystem grants and strategic partnerships
Multi-modality support: Enable output of images and videos, not just text
Self-hosted virtual machines: Enable users to run their own AVM nodes
AVM consensus mechanism: Coordinate decentralized compute providers
Transition to fully permissionless, decentralized execution network
Launch DAO governance modules for protocol parameter management
Tokenized incentives for compute providers
Distributed storage: Enable sandboxes to save and reuse files for long-term memory
Execute full-scale marketing and adoption campaigns
Expand global node infrastructure for AI agent networks
Advanced performance optimization (GPU support, dynamic load balancing)
Cement AVM as the global backbone for AI execution.
Fully equipped virtual machines: Complete desktop experience where agents have their own personal computer and achieve real-world tasks with minimal assistance
AVM Code: Claude Code-style development environment enabling agentic coding loops from zero to goal
Mature agent-native marketplace for compute, tools, and automation
The initial AVM deployment (v0) is hosted on distributed cloud infrastructure, with an alpha dashboard for task monitoring. Future versions will incorporate a proprietary VM Solver, enabling peer-to-peer contributions of compute resources for LLM processing, enhancing network resilience and reducing centralization.
Developers integrate AVM via:
High-Performance HTTP API — Direct LLM-to-AVM solver communication for efficient task execution.
Comprehensive SDKs — Available for TypeScript (@avm-ai/avm-vercel-ai
) and MCP server (@avm-ai/avm-mcp
), supporting Python code execution through the Vercel AI SDK and MCP-compatible clients.