The case for long-running AI agents and outcome-based pricing

a16z argues enterprise AI could move from assistants handling brief tasks and agents handling single interactions to long-running agents pursuing goals for weeks or months. It suggests vendors could price that work around outcomes rather than just cost savings. The firm also notes obstacles, including restrictions on non-lawyers sharing legal fees, procurement resistance and questions about how much of a result an agent contributed.