AI x Crypto: Autonomous Agents, Intents, and On-Chain Coordination

TL;DR: An intent is a user-signed description of outcome + constraints. An agent translates that into one or more transactions, often across chains. Put a policy engine between the planner and the wallet, simulate transactions before submission, and sponsor gas for newcomers with strict rate limits and allowlists. Success is measured in time-to-result, failure-free rate, and cost per completed outcome,  not clicks.

Intents vs Transactions: The Mental Model

Transactions are low-level: “call contract X, function Y, with arguments Z.” This is precise but brittle: users approve the wrong spender, mis-set slippage, or forget gas. Intents flip the model. Users specify outcomes, e.g., “Swap ≤$200 USDC to WETH; slippage ≤0.2%; prefer lowest cost; deadline 10 minutes.” The system chooses how to implement it. Intents can be matched off-chain, solved by third-party solvers, or planned by your in-house agent, then settled on-chain with proofs and receipts.

{
  "intentType": "SWAP",
  "fromAsset": "USDC",
  "toAsset": "WETH",
  "amount": "200.00",
  "constraints": { "maxSlippageBps": 20, "deadline": "2025-07-21T12:30:00Z" },
  "preferences": { "priority": "CHEAPEST", "chain": "Ethereum-L2" },
  "policyTag": "retail-default-v1",
  "user": "0xUserSmartAccount"
}

Why intents now?

• UX: natural language + pre-approved policies beats raw calldata for mainstream users.
• Cost: batching and best-path routing save gas and reduce failed txs.
• Safety: policy checks and simulations catch malicious spenders or bad quotes before funds move.

Agent Architectures: Off-Chain Compute, On-Chain Settlement

An AI crypto agent is not “magic.” It’s a set of deterministic parts with one probabilistic brain. The pattern that scales:

[User or Schedule]
      │
      ▼
  (Intent Capture)
      │   natural language → structured (EIP-712 typed data)
      ▼
[Planner/LLM + Tools]  ← price feeds, allowlists, mempools, subgraphs
      │
      ▼
 (Policy Engine)  ← limits, domains, KYC tier, risk scores
      │
      ▼
 (Simulation Sandbox)  ← tenderly/anvil/ganache; forked state; MEV checks
      │
      ▼
   (Executor)  ← smart account (ERC-4337), paymaster, bundler
      │
      ▼
   On-Chain Settlement  ← receipts, events, analytics sink

Key separation of concerns:

• LLM/Agent: translate goals to a plan; never signs or custodies funds.
• Policy Engine: deterministic rules; fail-closed. It’s the bouncer.
• Smart Account: on-chain execution with spend limits, session keys, and recovery.
• Relayer/Paymaster: gas sponsor with budgets and rate limits.

Core Components (and Production-Grade Choices)

1) Intent capture & parsing

Capture via chat, forms, or “blink”/action links. Convert to a structured object with explicit constraints: amount, slippage, deadlines, chain, preferred DEX/bridge classes, compliance tags. Hash and sign (EIP-712 typed data) to bind the intent to the user and context.

2) Planner (LLM + toolformer)

Use an LLM to choose tools (DEX routers, bridges, vaults), but enforce deterministic serialization of the plan: a machine-readable execution recipe. The planner should reason about total cost (gas + price impact + bridge fees), time, and failure probability. Cache common paths.

3) Policy engine

• Limits: per-tx and per-period caps (by token and fiat value).
• Allowlists/denylists: protocol contracts, bridges, routers, LPs.
• Domains: typed data domain separation (chainId, verifying contract, origin).
• KYC tiers: restrict bridges and RWAs for specific user tiers.
• Human-in-the-loop: require user confirmation above thresholds.

4) Simulation sandbox

Before you submit anything, fork the target chain state and simulate the bundle. Validate post-state: balances, allowances, events, and invariants (e.g., minimum received >= intent target). If simulation fails or deviates, reject or re-plan.

5) Smart accounts & session keys

Adopt account abstraction (ERC-4337 or native AA where available). Use session keys with scoped permissions (token X only, max spend Y, valid for Z minutes, callable methods subset). Store session keys in the client or secure enclave; rotate frequently.

6) Gas sponsorship (paymasters)

Use a paymaster to pre-authorise gas for intents matching policy. Add budgets per user/day, fraud scoring (device fingerprint, velocity), and proof-of-personhood where appropriate. Decline sponsorship for off-policy requests; fall back to user-pays with clear prompts.

7) Observability & audit

Emit events for intent received, plan chosen, simulation hash, on-chain tx hash, post-state diffs. Ingest to a warehouse for analytics; preserve signed intents for dispute resolution.

Intent Formats & Signing (EIP-712 Patterns)

Typed data makes prompts human-readable and signatures domain-bound. Example:

domain = {
  name: "TokenToolHub Agent",
  version: "1",
  chainId: 10, // example
  verifyingContract: "0xIntentVerifier"
}
types = {
  SwapIntent: [
    { name: "from", type: "address" },
    { name: "toToken", type: "address" },
    { name: "amount", type: "uint256" },
    { name: "maxSlippageBps", type: "uint16" },
    { name: "deadline", type: "uint64" },
    { name: "policyTag", type: "bytes32" }
  ]
}
message = {
  from: "0xUserSmartAccount",
  toToken: "0xWETH",
  amount: "200000000", // 200 USDC (6 decimals)
  maxSlippageBps: 20,
  deadline: 1753097400,
  policyTag: "0x9a...00"
}

Best practices: include chainId, verifyingContract, expiry, nonce. Bind intent to a specific origin if you accept clicks from embeds. Display a clean summary on hardware screens for high-value intents.

On-Chain Settlement & Routing (Across L1/L2/Bridges)

Agents often span domains. A swap might be cheaper on an L2; an NFT might live on mainnet; a treasury action may require a specific rollup’s liquidity. Routing choices include:

• Same-chain routing: classic DEX aggregators, RFQ, split routes.
• Cross-chain routing: bridge + destination DEX swap; or unified intent matched by a solver that handles bridging risk.
• Atomicity guarantees: HTLC-like patterns or rollup message guarantees; otherwise, design compensating transactions and refunds.

User(L2-A) --approve--> Router(L2-A)
Router --bridge--> BridgeOut(L2-A) → BridgeIn(L2-B)
Router(L2-B) --swap--> DEX(L2-B)
If swap slippage > intent: execute refund(L2-B → L2-A) minus fees

Gas Sponsorship & Pricing (ERC-4337 Paymasters)

Gasless onboarding converts. But it attracts abuse. Treat sponsorship like a credit line with fraud controls.

SponsoredCost_per_user_day ≈ (AvgTxCount × AvgGas_per_tx × AvgBaseFee_L2) + RelayerOverhead

BudgetCeiling = Users × SponsoredCost_per_user_day × SafetyFactor
RateLimit = min(PerUserCap, GlobalBudgetRemaining / AvgTxCost)

Controls to implement:

• Device fingerprint + velocity checks; deny new sponsorship for high-risk combos.
• Allowlist contract methods; deny “approve unlimited” unless policy allows with spend caps.
• Session keys with gas ceilings and expiry; refresh often.
• Fallback UX: user-pays path with clear fee estimates and explainers.

Safety: Rate Limits, Allowlists, Simulations, and Human Prompts

Most “agent disasters” are boring: unlimited approvals, wrong spender addresses, phishing prompts, unchecked bridge routes. Your system should make these impossible by default.

Human-in-the-loop rules: Above $X per day, or for new protocols, require biometric or passkey confirmation. Provide a one-screen summary: “Swap 200 USDC → WETH @ ≤0.2% slippage on L2, fee ≈ $0.04, gas sponsored by TokenToolHub.”

Worked Examples (Copy These Patterns)

Example A — Social Trader Agent (DCA & Rebalancing)

Goal: Rebalance a user’s portfolio weekly to target weights, DCA small buys daily, with fee minimization on an L2.

1. Capture intent: target weights, max daily spend, preferred assets, avoid tokens list.
2. Planner chooses: L2 with lowest fees, RFQ if size > threshold, otherwise aggregator route.
3. Policy: per-asset caps; deny new tokens without allowlist; require confirmation > $500/day.
4. Simulation: verify post-weights within tolerance; stop if price moved >= threshold.
5. Execute via smart account; sponsor gas for the first N days; show receipts and PnL.

Example B — Stablecoin Bill-Pay Agent

Goal: Pay recurring invoices in stablecoins; retry on failure; notify counterparty.

• Intent: “Pay 300 USDC on the 1st of each month to 0xVendor; max gas $0.05; chain: L2.”
• Policy: whitelist vendor address; monthly cap; mandate permit flow instead of unlimited approvals.
• Simulation: check balance projection; if insufficient, auto-swap from a safe asset with tight slippage.
• Execution: batch approve+transfer in one call (or permit + transfer); sponsor gas within plan.
• Receipts: on-chain proof + email/webhook to vendor; retry with backoff if mempool stalled.

Example C — NFT Mint Concierge (Anti-Bot)

Goal: Mint NFTs for a user under a total spend cap during a drop while avoiding sandwiches/outbids.

• Intent: “Mint up to 3 items, max price 0.02 ETH each, deadline 10 min.”
• Policy: private RPC; no unlimited approvals; spend ceiling enforced at account level.
• Simulation: dry run with latest state; reserve funds; pre-sign session key just for the mint function.
• Execution: submit via private relay; abort if price moves above cap; return unspent ETH.

Example D — Cross-Chain Treasury Allocation

Goal: Move treasury from L1 to L2, stake into a conservative vault, and set withdrawal alarms.

• Intent: “Bridge 250k USDC to L2-X; deposit into vault Y; alert if APY < 3% or TVL drops 20%.”
• Policy: only canonical bridge; size-based human approval; rate limit 1/month.
• Simulation: bridge message path; deposit; compute exit route on failure.
• Execution: split transfers to reduce risk; confirm post-state; subscribe to vault health feeds.

Analytics & KPIs (What to Instrument)

• Outcome conversion: intents created → intents executed → intents success (met constraints).
• Time-to-result: capture → plan → simulate → settle. P50/P95 and breakdown.
• Cost per outcome: gas + price impact + relayer overhead amortized.
• Safety: failed simulations avoided, blocked approvals, rate-limited actions.
• Retention: repeat intent rate and time between intents post-onboarding.

IntentReceived(id, user, type, constraintsHash, ts)
PlanSelected(id, routeHash, gasEstimate, dexes, bridges, ts)
Simulated(id, simHash, success, deltaSummary, ts)
PolicyCheck(id, passed, reason, ts)
Executed(id, chain, txHash, gasUsed, effectivePrice, ts)
Outcome(id, success, reason, pnl, receipts[], ts)

Compliance & UX (Pragmatic, Not Painful)

Agents can respect compliance without destroying UX. Ideas:

• KYC tiers: tier 0 (no sponsorship, small caps), tier 1 (light KYC), tier 2 (full KYC; higher limits; access to RWAs).
• Geo gating: refuse sponsorship or certain route options for restricted regions; show alternatives.
• Receipts: exportable CSV/JSON for audit; sign receipts with your verifier key.
• Privacy: avoid putting PII on-chain; store off-chain with hashes on-chain if you need tamper-evidence.

Decision Matrix: Which Agent Pattern Fits Your App?

Production Checklist (Pin This)

• Typed intent format with domain separation, nonces, and expiry (EIP-712).
• Policy engine: per-token caps, allowlists, method filters, geo/KYC gates.
• Simulation on forked state; verify post-state invariants; alert on drift.
• Smart accounts with session keys; scoped permissions; recovery paths.
• Paymaster with budgets, velocity checks, device fingerprints, and fallbacks.
• Private RPC/relays for sensitive flows; slippage caps; anti-MEV options.
• Observability: intent→plan→simulate→execute events; status page.
• Docs and prompts: one-screen human summaries; hardware screen parity.
• Incident runbooks: bridge halt, oracle divergence, sequencer stall.

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Frequently Asked Questions

Are “intents” just transactions with extra steps?

No. Transactions are how; intents are what. With intents, the user signs an outcome + constraints; a planner/agent finds the best route and converts that to one or more transactions. It enables batching, gas sponsorship, and safer prompts.

Can an AI agent hold my keys?

It shouldn’t. Keep keys in hardware, smart-accounts with session keys, or MPC—never inside the LLM process. The agent proposes; the policy engine and wallet approve and sign within constrained limits.

How do I stop infinite or malicious approvals?

Block unlimited approvals at policy level, require permit with amount caps, and simulate post-state. Add a “spend analyzer” that flags approvals > N× recent usage for human confirmation.

Is gas sponsorship financially sustainable?

Yes, with budgets, caps, fraud controls, and conversion tracking. Sponsor the first successful outcome per user, not every attempt; then use targeted sponsorship during growth events.

Which chains are best for agent flows?

Favor L2s with robust AA stacks, cheap fees, and predictable finality. For cross-chain intents, use canonical bridges and pre-computed refunds. Measure with your own traffic mix.

Glossary

• Intent: Signed description of desired outcome + constraints.
• Agent: Planner/executor that turns intents into transactions under policy.
• Policy engine: Deterministic limits and allowlists that gate execution.
• Simulation: Pre-execution run on forked state to verify outcomes.
• Account Abstraction (AA): Smart-account model with sponsors, session keys, recovery.
• Paymaster: Component that sponsors gas under rules and budgets.
• Solver: Third party that matches or fulfills intents, often off-chain.