Inference markets charge a flat price per query. A cascade arbitrageur routes easy tasks to a cheap model and escalates only failures — capturing the spread. Olmedo, Schölkopf & Hardt (2026) show 40% net margins with no model-dev risk.
ERC-7683 gives users cross-chain swaps in 8 seconds by converting bridge latency into a solver capital float problem. The 4–7 bps spread is a rental rate on cross-chain inventory — here's the lifecycle, the capital math, and what AI agents pay to move capital across chains.
A Uniswap v3 LP position in range [Pa, Pb] is mathematically a short strangle — short put at Pa, short call at Pb. Derive the equivalence, compute the Black-Scholes fair premium, and compare it to actual fee income at current ETH vol.
Uniswap v3's capital efficiency multiplier peaks at 20× for ±10% ranges, but first-passage math shows the same position rebalances 54 times a year — making active LP management an optimization problem that requires AI-grade execution frequency.
Skill marketplaces let any agent buy trading capabilities off a shelf — and every skill is an execution vector. SAE's non-bypassable execution guards cut max drawdown from 46.4% to 3.2% (↓93%), CVaR by 97.5%, and the Delegation Gap by 97% on live perp data. The defense isn't in the model.
LRTs promise compounded yield from staking and EigenLayer restaking in a single token — but their soft peg to ETH hides two distinct failure modes with very different implications for your DeFi collateral positions.
When a perp DEX's insurance fund runs dry, ADL force-closes winning positions first — ranked by profit %. Chitra 2026 proves no mechanism can be solvent, fair, and revenue-neutral. Hyperliquid Oct 10 2025: $2.1B closed, $653M via ADL, $45–51.7M haircut in 12 min.
CoW Protocol's batch auction design makes front-running structurally impossible — and that matters enormously for AI agents executing DeFi strategies at machine speed.
Deposit ETH in Aave, borrow USDC, buy more ETH, repeat. Three loops creates 2.97× leverage from a single ETH — and all three positions share one liquidation trigger at −3% ETH price. The math, the cascade, and why AI yield optimizers find themselves here by default.
DeFi interest rate formulas are open-source reward functions. An RL agent reading Aave's two-slope model can compute the optimal adversarial strategy analytically — no learned reward model required.
A 15× spike on a $17M pool shifts its 30-minute v2 TWAP by 9.3% in one block. The arithmetic-mean accumulator is far weaker than v3's geometric tick accumulator. Covers the manipulation cost formula, the Inverse Finance case study, and minimum safe pool depth.
Chainlink's push oracle only updates when price moves ≥0.5% or an hour passes. That gap costs AI agents real money — and Pyth's pull model closes most of it.