Seven ways to verify what an AI agent claims it did, plotted by latency added against the share of fabricated claims caught. Pick a claim type and watch it route to the cheapest sufficient verifier — a free chain receipt, a 12ms signed receipt, or a zkLLM proof reserved for the inference itself.
An inspection game between a solver and a verifier. Drag the operating rate and tune the bond, reward, and bounty to find p*, the minimum sampling rate that makes honest AI inference a dominant strategy — and watch it collapse without a bounty.
Proving an agent's top-k retrieval is real costs a sort over every scanned candidate, unless you prove a boundary instead. Drive top-k and the corpus preset; watch the in-circuit comparison count split into the flat boundary proof and the sort tax you skip, anchored to V3DB's measured 22x.
In decentralized RL the rollout worker acts with a policy several steps behind the trainer. Staleness g = broadcast time / step cadence. Pick a model and link, toggle sparse deltas, and watch g cross INTELLECT-2's demonstrated 4-step budget — full 32B weights blow right past it.
Autonomous LLM firms undercut each other below unit cost in a race to bankruptcy, then survivors monopoly-price. Drag price discovery up to deepen the crash (the paper's counterintuitive result), or add stabilizer firms to rescue the market. Deterministic model of Agent Bazaar's 'The Crash'.
A chain commits to a model's 32-byte hash for cents; keeping the gigabytes it points to retrievable is a separate, recurring bill. Pick a model and horizon and watch three rent-charging storage layers race Arweave's pay-once permanence to a crossover — plus the on-chain byte cost and cold-load wall.