Traditional contracts are written with disputes and litigation or arbitration in mind. This tends to prioritise a precise form of legal drafting that is coded for legal purposes, rather than for the practical purposes of performing the contract. The resulting disconnection is known as the implementation gapImplementation gap. Bridging the gap requires, among other things, an understanding of the objectives and what information is of most relevance to each type of business user. The ability of generative AIGenerative AI (GenAI) to simplify the language of contracts is well established, but in this chapter we explore what else it can do to bridge the gap and how well it can anticipate the needs of particular audiences—including people responsible for implementation in the field, without a background in law. We begin by using Anthropic’s ClaudeClaude and OpenAI’s ChatGPT4o as our brainstorming and ideation partners in the problem-framing and solution-finding phases. While they provide significant support, we also evaluate how much help they can be as our contract assistants. We give ChatGPT4o contract simplificationContract simplification tasks and test how good it is at creating a contract guideContract guide: a tool that is often used to help contract implementation personnel to do their job. We use de Beaugrande and Dressler’s classic standards of textualityTextuality to challenge ChatGPTChatGPT, asking it to explain its own limitations, and the level of human oversightHuman oversight required. Finally, we discuss how effective promptingPrompting can help us get the most usable results from our AI assistants.