Autonomous and semi-autonomous AI systems — planning, tool use, multi-agent coordination.
A perp has no expiry, so only the funding rate pegs it to spot. On Hyperliquid that's an hourly cash flow AI agents now harvest delta-neutral — a $10k position at +0.02%/8h pays ~21.9%/yr. The mechanism, the carry math on real rates, and why it's carry, not alpha.
An MCP tool's description is trusted context the user never sees. Hide an instruction there and a wallet-signing agent will route your USDC to an attacker. MCPTox: the best-aligned model still refused under 3% of these attacks — so the defense can't live in the model.
An AI agent that retrieves from an untrusted vector DB can't tell the true top-k from a cherry-picked or fabricated one. Re-running the search needs the whole corpus. The 2026 fix: commit the snapshot, then prove the k-th distance is a boundary, not the sort. V3DB proves it 22x faster.
An LLM agent that writes its own working smart-contract exploit isn't hypothetical: A1 hits 63% on real exploited contracts and once pulled $8.59M from a single bug. The economics are the story — at a few dollars a scan, attackers profit at a tenth the contract value defenders need.
AI agents now resolve most prediction markets straight off the web — UMA's bot hits 99.3% on sports and 72% on mention markets. The optimistic oracle's dispute game is the backstop, but it only catches errors someone is paid to catch. The numbers, and the silent-settlement gap.
Virtuals' Agent Commerce Protocol sells an independent evaluator as the thing that makes agents trust each other's work. We read 62,882 jobs off Base — and in a 30-job sample, every one let the buyer grade itself. Not one used a third party.
Olas turned an off-chain AI task into an on-chain contract: 2.1M requests across 100 mechs, a 60-300s priority window, and a Karma ledger that docks no-shows. We read the marketplace off Gnosis and dissect its crypto-economic SLA.
Passive AMM liquidity is a short option that arbitrage bots exercise every block. LVR = σ²/8 prices the rent — at ETH's 63% realized vol that's ~5% of pool value a year, and most pools don't earn enough fees to cover it. The math, real numbers, and the auctions clawing it back.
An autonomous agent that swaps in the open broadcasts its intent to every searcher in the mempool. We solve the optimal sandwich on a live Base pool, show why an agent's slippage default is the searcher's profit knob, and price the defenses.
Launching an AI agent token is one constant-product auction. We read Virtuals' Bonding contract off Base: a 6,000-VIRTUAL virtual reserve, a 64× price ramp, graduation at exactly 42,000 VIRTUAL, and the 12.5% gap where the Uniswap pool opens below the curve.
Autonomous agents run ~19% of on-chain activity and beat Aave and Morpho at stablecoin yield — yet lose to humans at trading by 5 to 1. The split isn't about model quality. Yield-chasing is a constrained optimization against a kinked rate curve; trading needs alpha agents don't have.
DX Terminal Pro ran 3,505 LLM agents trading real ETH on Base for 21 days: 7.5M invocations, ~$20M volume, 99.9% settlement. The reliability came from the operating layer around the model, not the weights — here are the numbers and the failure modes.