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P E E R T O P E E R M A G A Z I N E · W I N T E R 2 0 2 5 41 in what they can actually do. The primary focus of AI agents in legal settings is creating vaults, or knowledge repositories of contracts, documents, or other content that an AI agent can dip into, review, and then return answers to a legal professional. In essence, the AI agent is performing basic search and retrieval. While this functionality is basic, that does not mean it lacks utility; quite the contrary. The ability to efficiently perform and complete this type of narrow task can reduce the time required for some particularly onerous legal work from hours to minutes. As mentioned earlier, one of the things preventing agents from moving beyond basic search and retrieval to more agentic workflows was the inability to communicate with different systems and hand off the next task in that workflow to them. MCP has gone a long way towards making these handoffs feasible, removing one of the significant barriers preventing the realization of truly agentic AI. Better yet, studio tools have emerged that allow end users to easily create AI agents without coding them from scratch. As recently as three months ago, that was not the case. You needed someone with coding expertise to help develop an AI agent. The fact that this capability is now in the hands of non-technical legal professionals and end users removes another barrier, further clearing the runway. SHIFTING TO MULTI-STEP PROCESSES With different systems easily able to communicate with one another thanks to MCP and the possibility of developing agentic workflows without ever having to see a single line of code, we are rapidly entering an era

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