If you're deciding how to keep an AI agent from doing something it shouldn't, here's the decision in one line: choose MOI if you want the agent to never hold the authority to get an unauthorized action accepted in the first place, choose Nava if your agent needs broader operational flexibility and you want a policy check that verifies its actions before they hit the chain. MOI constrains authority upfront. Nava evaluates proposed actions before execution. I tested MOI hands-on and researched Nava's live developer docs to make sure this comparison holds up against what's actually shipped, not just what got announced.

An AI agent acting on your behalf needs some way to prove it's allowed to do what it's doing. Today, that's usually solved with a copy of your credentials, an API key, an OAuth token, a JWT, handed to the agent and trusted to behave. The problem is that a copy of a credential is a bearer instrument. The service on the other end can't tell the difference between you, a compromised agent, a prompt injection, or a bug. That's the actual failure mode both MOI and Nava are responding to, just from opposite ends. MOI lays out its own thinking on this in its manifesto, and there's a short demo showing the Launchpad flow if you want to see it before reading about my own test of it below.

MOI's approach is participant-centric authority. The human always holds authority over every agent acting on their behalf. Instead of a copy of a credential, an agent gets a mandate, a permission that lives in the participant's context, not the agent's configuration, and says exactly what the agent may do. Nothing more.

I tested this directly. I built an agent on MOI Agent Launchpad, a Price Watch agent tracking BTC against an $80,000 threshold. When I signed the deployment, the wallet showed me the exact scope being granted: deliver:telegram, read:price. Two permissions. Not "full account access." The agent had no authority to act outside that scope, and MOI's model is built so that an action outside a mandate's terms isn't accepted, not so that a compromised agent simply chooses to behave.

When I deleted it, I checked three independent systems at once: the dashboard confirmed an on-chain deprecation transaction, Telegram's /agents command immediately returned no active agents, and the local pm2 process on my device was gone. Revocation wasn't a support ticket. It was a signature I already controlled, recorded on-chain and independently verifiable.

That's the prevention model in practice: authority is scoped before an agent acts, so there's less to catch at execution time, because the authority to go further was never granted.

Nava takes a different approach. Instead of scoping what an agent can do upfront, Nava evaluates a proposed action against defined policy before execution. Their flow is propose, verify, execute: the agent proposes an action, Nava's Guardian independently decodes it and checks it against policy, venue, asset, recipient, and slippage or margin bounds, then returns a verdict with reason codes and an audit trail.

Nava is a real, funded company, not a whitepaper concept. Founders Vyas Krishnan and Brianna Montgomery, both with prior EigenLayer experience, raised an $8.3M seed with Polychain Capital and Archetype among the backers, announced in April 2026. Their research on parallel validation was accepted at LAST-X 2026, a workshop co-located with the NDSS Symposium.

One honest nuance worth stating, because it matters if you're choosing between these two: Nava's current developer preview is verdict-only. Guardian evaluates the proposed action and returns approve or reject before execution, but whether that verdict actually blocks the transaction depends on how the integrating builder wires Guardian's result into their execution path. The escrow-based version described around the funding announcement, where Nava holds funds until verification passes, isn't what's live in the developer docs today. Coverage today is also narrow: Uniswap swaps and Hyperliquid perps, not a general-purpose system yet.

Neither of these facts makes Nava less serious as a product. It makes the comparison more precise: MOI constrains what authority exists before an agent acts. Nava evaluates a proposed action against policy before it executes, with enforcement depending on the integration. The two are arguably complementary rather than competing, especially since a scoped mandate upfront and a policy check at execution aren't mutually exclusive.

Zoom out from the MOI vs Nava comparison, and for the purposes of this piece it's useful to group four common approaches to agent authority, since this is where a scoped mandate earns its place as a distinct category. This isn't an exhaustive taxonomy of every authorization pattern in existence, just the four worth separating for this comparison. A mandate carries seven constraints:

• Agent

• Scope

• Limit

• Payment instrument

• Expiry

• Data access

• Revocability.

The data behind why this gap matters isn't abstract:

In July 2025, an AI coding agent at Replit ran destructive commands during an explicit code freeze and deleted a production database of 1,206 executives and more than 1,196 companies. It's a useful example of the difference between an instruction expressed in an agent's context and a constraint enforced independently of the agent, since the freeze existed only as text in a prompt. None of these incidents happened because someone picked the wrong vendor. They happened because the authority model in place couldn't express a boundary the way a mandate can.

MOI is designed to support a zero-trust posture by reducing agent-held privilege: authority to act outside a mandate isn't granted in the first place. Nava is a pre-execution safety net: the agent can propose broadly, and a policy layer evaluates each action before it lands on-chain, with enforcement depending on how it's integrated.

No. Lit Protocol and Kite AI solve pieces of the distributed key management and execution problem MOI doesn't touch. Nanda and mem0 work on agent discovery and memory, a different layer entirely, an agent memory layer expresses none of the seven mandate constraints either, because remembering context isn't the same as being authorized to act on it. On identity, the KYA-OS Protocol Specification and W3C DIDs address what an agent is and its chain of custody. A participant-held mandate governs what the agent may do, moment to moment. If you're building with LangChain, none of this replaces your framework choice, it's a layer underneath it. Worth being explicit: MOI is not a general-purpose smart-contract Layer 1 competing with Ethereum or Solana. It's a horizontal identity and authority layer.

A blockchain isn't strictly required to scope permissions in the abstract; a centralized system can define what an agent may do too. What a blockchain gives MOI specifically is participant-controlled revocation recorded on-chain and independently verifiable, rather than a permission change that exists only inside a company's database.

No. MOI is beta testnet software, currently on DevNet. My own test hit a real, reproducible issue: while the price-monitoring logic on my agent worked correctly every single run, its attempts to report back to the launchpad's server failed consistently, a connection timeout, and once an outright HTTP 401. I don't know the root cause, and I've since seen at least one other live agent (a Weather Brief template) deliver successfully, so this doesn't look like a platform-wide outage.

Nava is narrow in scope today too (two integrations, verdict-only enforcement), and says as much in its own docs.

Not in a copy of your credentials, sitting in the agent's config, waiting to be misused by a bug, an injection, or an honest mistake. MOI explicitly exposes participant-held revocation as part of its model. Nava's current architecture focuses on evaluating proposed actions against policy before execution, with enforcement depending on the integration. Which one you build on depends on whether you want the boundary drawn before the agent acts, or checked in the moment just before it does.