# Beyond A2A: How Rust-Powered Shared State Machines Turn Agent Protocols Into Executable Infrastructure

> Protocols define how agents talk, GI shows how they act

**Published by:** [General Impression](https://paragraph.com/@gi/)
**Published on:** 2025-04-16
**Categories:** a2a, ai, rust, mcp, gi, infra
**URL:** https://paragraph.com/@gi/beyond-a2a

## Content

Rethinking Agent Collaboration: From Schema to RuntimeProtocols like Google’s A2A (Agent-to-Agent) and Anthropic’s MCP (Model Context Protocol) have begun to standardize how agents communicate and access tools. However, most current implementations treat these schemas as abstract interfaces—relying on stateless message-passing systems, disconnected execution layers, and external orchestration logic. At General Impressions (GI), we believe this approach misses the critical point: multi-agent systems need more than a schema. They require a coherent runtime that can execute these structures efficiently, verifiably, and across both local and remote contexts. Our answer is the Shared State Machine: a Rust-native execution layer that unifies agent collaboration, memory, and lifecycle management into a single programmable substrate.The Shared State Machine: Execution as CommunicationIn GI, agent coordination is not abstracted away in queues or black-box middleware. Instead, it is made explicit through a Shared State Machine:Every agent is modeled as a finite-state processAll coordination is encoded as state transitions within a global state graphTransitions are composable, deterministic, and persistently recordedThis allows agents to not just talk to each other but also operate on shared logic. It transforms communication into structured computation.The A2A Protocol Queue: Unified Local and Remote CollaborationTo mediate both local interactions and remote collaborations, GI introduces the A2A Protocol Queue.Internally, it routes state transition intents between co-located agents in the shared state graphExternally, it serializes A2A-compliant messages and dispatches them to remote agentsSymmetrically, it reconciles remote responses back into local state transitionsThe A2A Protocol Queue acts as the single coordination bus, enabling seamless continuity between in-memory FSM logic and cross-network protocol execution. Whether a task involves a local actor or a remote LLM agent, the coordination flow is structurally identical.Why Rust?Rust is not just a high-performance systems language—it is a compiler-enforced framework for correctness and safety. For agent infrastructure, it provides:Zero-cost abstractions: expressive agent logic without runtime penaltySafe concurrency: multi-agent coordination with thread-safe guaranteesAsync orchestration: embedded scheduling and tool chaining with native async / awaitCompile-time validation: state transitions are validated before executionDeterministic performance: suitable for critical workflows and traceable behaviorRust enables GI to treat agent orchestration as a first-class systems problem, not a duct-taped abstraction layer.Infrastructure OverviewGI as an Executable Agent SubstrateRather than layering protocol support on top of a generic platform, GI embeds A2A and MCP directly into the execution logic. This turns protocol structure into live, observable behavior. LayerProtocolGI's Execution RoleTool AccessMCPNative ToolUse engine supports MCP schemas as runtime callsAgent CoordinationA2AA2A semantics are compiled into the shared state graphOrchestration(Missing in most stacks)Rust async engine powers state execution, lifecycle, and remote coordinationConclusion: Protocols are the Schema, GI is the MachineThe future of agent collaboration is not just about defining schemas. It is about compiling them into live, verifiable execution environments. GI achieves this by:Embedding A2A coordination into runtime logicManaging local and remote agents as one unified swarmUsing Rust to enforce safety, composability, and concurrencyCapturing execution in transparent, on-chain stateProtocols define how agents talk. GI shows how they act.

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