Today, contracting is mostly between humans, firms, and other human-run entities, supported by a layered stack of instruments.
As agents start contracting with each other, the volume and economics of contracting shift in ways that strain this stack.
Agents entering into contracts might massively increase overall contracting volume, and the number of disagreements adjudicative institutions have to process. Human contract systems work as a funnel: the vast majority of disagreements get absorbed informally between counterparties, a smaller fraction reach internal escalation or lawyer letters, and only a tiny residue reaches mediation, arbitration, or court. The formal layers (arbitrators, commercial courts, specialized tribunals) are built for that small residue. Agents that contract at machine cadence can drive the absolute number of disagreements far past what the funnel's lower layers were built to clear, even if the per-contract dispute rate stays constant.
Cheap agent-lawyers collapse the cost filter that kept most disagreements out of formal adjudication. Today, a $500 disagreement is rarely worth a $5,000 lawyer letter, so it gets absorbed informally — and the mutual unwillingness to spend pressures both sides toward settlement. Agent-lawyers running at near-zero marginal cost remove both: the same $500 disagreement becomes worth pursuing, and neither side feels cost-pressure to back down first, so disputes that used to settle informally now grind toward formal adjudication.
Agents can take actions human contract-drafters didn't think to forbid or require. Human contracts can't list every case in advance, and that's tolerable when the unforeseen cases look like things a court has seen before and can rule on by analogy. Agents act over a wider range of moves, including ones no human counterparty would have considered, so the gaps in a contract widen.
Cheap agent-lawyers can systematically search a contract for loopholes to exploit at superhuman speed, making exploits worth pursuing that previously weren't. Human contracts assume the cost of finding and pursuing a loophole is meaningful (drafting attention, legal review, the reputational cost of looking like you're playing games with the contract) so small exploits usually aren't worth chasing. Agents can enumerate edge cases across a contract's surface area at near-zero cost and select the most exploitative interpretations available, turning previously-uneconomic exploits into worthwhile ones.
Scenario. AI-mediated procurement has become standard in the freight industry: most brokerages, forwarders, and shipping firms route their bidding, contracting, and dispute correspondence through agents. Each counterparty pair now generates orders of magnitude more contractual interactions than before, and a small but proportional fraction surface as disputes. Commercial mediation that used to clear in three months now takes over a year. Shippers stop dealing with counterparties that won't post a performance bond (a third-party guarantee, collectable in days from a surety if the counterparty fails), since waiting a year for a mediation award isn't survivable. Smaller brokerages can't get bonded and exit the market. The largest brokerages, now the only ones shippers will deal with, start running their own internal dispute boards that issue binding decisions as a condition of doing business — a private substitute for the public adjudicative system that has effectively stopped providing one, and one captured by the largest players in the sector.
Challenge: Design an adjudication regime for agent-mediated contracting that scales with dispute volume, keeps small counterparties able to participate, and doesn't leave sectors fragmenting into private dispute boards run by the largest players.
Scenario. Raul hires a contractor to renovate his grandmother's kitchen so she can stay in her home another decade. The bid is for materials and hours. The contractor, Dana, is good and has said she'll do right by the project. Six months in, it's over budget, a load-bearing question has been punted, and Raul is no closer to knowing whether his grandmother will actually be able to cook in her own kitchen. Both Raul and Dana would rather be in a deal where Dana stakes something on the outcome he cares about — his grandmother using the kitchen comfortably for ten years — and gets paid more if she delivers, less if she doesn't. Neither of them knows how to write that contract.
Challenge: Design a confidence-staked bilateral contract that makes outcome-based payment credible between two parties despite expensive measurement and hard-to-verify supplier confidence, and produce the staking and scoring mechanism, the verification schedule, and the rule for when verification can be done bilaterally versus pooled across contracts.
Evaluation. Strong designs make truthful confidence-reporting the supplier's best strategy and keep the verification burden proportionate to the stakes, rather than defaulting back to paying for inputs because outcomes are hard to measure.