I published an AI skill on Lawve AI: Contract Intelligence & Workflow Reviewer
This started as a contract review skill and evolved into an experiment: How far can an LLM be pushed toward Contract Lifecycle Management (CLM) capabilities?
The skill includes:
• Structured intake
• Playbook normalization
• Clause-by-clause review
• Deviation scoring
• Negotiation planning
• Approval routing
• Workflow states
• QA & benchmarking
• Actions
I wanted to explore where AI models are useful and where they fall short. LLMs are very good at:
• Contract intelligence
• Issue spotting
• Negotiation support
• Playbook comparison
• Workflow guidance
• Drafting
• Contract review
But they struggle with CLM capabilities, including:
• Persistent records
• Structured metadata
• System-of-record
• Workflow engines
• Obligation management
• Reporting & analytics
• Enterprise integrations
• Governance/controls
AI helps people do contract work. It can support parts of the contract lifecycle. It is not yet a CLM. Harvey and Legora continue expanding contract review and workflow capabilities. CLM vendors such as Conga, Ironclad, Agiloft, Icertis, Docusign, & Sirion continue to embed AI in their platforms. Contract AI vendors such as Ivo, Spellbook, Luminance, & DocJuris are expanding their capabilities. Anthropic is expanding Claude through Skills, agents, workflows, MCP, and document analysis. OpenAI appears headed in a similar direction.
As capabilities once requiring specialized contract AI products increasingly become available from the platforms, the question becomes: what remains differentiated?
My suspicion is that contract review is becoming a feature rather than the product. The competitive advantage increasingly comes from workflow, governance, integrations, knowledge, playbooks, data, controls, and adoption. The model matters, but execution matters more.
A lesson from this project: this skill can consume a lot of tokens. When using an LLM to replicate aspects of a CLM, large agreements, playbooks, comparison reviews, and detailed reports can result in significant token consumption and cost. I intentionally optimized this skill for thoroughness and process over efficiency because I wanted to understand the limits.
If you never use this skill, there may be useful ideas in the design related to:
• Legal AI strategy
• Contract intelligence & operations
• CLM modernization
• Legal workflow automation
• The future of legal service delivery
I’m exploring my next leadership opportunity. If you know of a relevant role, please reach out.