AI-assisted contract review, drafting, and risk analysis

I spent 30 days building a massive AI contract management system. Then I built a standalone agent in 2 days that did 80% of the same work.

When Claude’s Legal plugin was released, the industry was shocked. But after testing it myself, I realized the "fastest path" to a working AI agent has almost nothing to do with code. It’s about capturing the judgment calls an expert carries in their head.

Most guides start with the technology. Pick a model. Choose a framework. Define a stack. Wire up an API. That's starting a house with the roof.

But a senior legal advisor doesn't review contracts by reading every word. They check 24 specific things against an acceptable range. That's the decision framework your agent needs.

𝐌𝐲 𝐛𝐢𝐠𝐠𝐞𝐬𝐭 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬 𝐟𝐫𝐨𝐦 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐚𝐧 𝐀𝐈 𝐋𝐞𝐠𝐚𝐥 𝐀𝐠𝐞𝐧𝐭:
1. 𝐃𝐞𝐟𝐢𝐧𝐞 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐖𝐡𝐚𝐭, 𝐛𝐮𝐭 𝐖𝐡𝐨. Frame the role: "You act as a contract analyst, not legal counsel. You represent the seller. You surface findings—humans decide." This single sentence prevented more errors than pages of instructions.
2. 𝐆𝐢𝐯𝐞 𝐭𝐡𝐞 𝐚𝐠𝐞𝐧𝐭 𝐠𝐫𝐨𝐮𝐧𝐝 𝐭𝐫𝐮𝐭𝐡𝐬. AI needs absolute guardrails: "Unlimited liability is never acceptable." Establish these early so the agent doesn't "reason" its way into a plausible-but-wrong conclusion.
3. 𝐀 𝐩𝐫𝐨𝐦𝐩𝐭 𝐬𝐩𝐞𝐜 𝐢𝐬 𝐧𝐨𝐭 𝐚𝐧 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐬𝐩𝐞𝐜. The vocabulary optimized for a developer is not what an AI model needs. Write your prompt spec to be self-explanatory in full.
4. 𝐍𝐞𝐯𝐞𝐫 𝐚𝐬𝐬𝐮𝐦𝐞 𝐭𝐡𝐞 𝐚𝐠𝐞𝐧𝐭 𝐰𝐢𝐥𝐥 𝐢𝐧𝐟𝐞𝐫. If you think something is "obvious," write it down. Explicitness is the baseline requirement for reliable behavior.
5. 𝐑𝐞𝐩𝐞𝐚𝐭 𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐜𝐨𝐧𝐭𝐞𝐱𝐭. Don't assume Module 4 remembers the "Who" from Module 1. Repeat the most critical guardrails at every stage.

The bottleneck was never the AI. It's getting a domain expert to decompose "this feels risky" into specific, testable conditions. That's the hard work. Everything else is configuration.

What domain are you thinking about building an agent for?