First hour with LQ.AI

Why this project exists

Commercial in-house legal AI products treat their prompt engineering as proprietary moat. The skills, playbooks, citation logic, and verification heuristics that shape what the user sees are hidden inside closed-source applications, presented as "AI" but functionally indistinguishable from "a system prompt the vendor refuses to show you." Customers pay significant per-seat fees for software whose only real innovation is a hidden prompt — without any way to see, debug, or improve it.

LQ.AI inverts this. Every artifact that shapes the user's experience is visible work product. The skills are open source. The playbooks are open source. The citation engine's verification logic is open source. The Enhance Prompt rewriter is open source. The Organization Profile that captures org-wide voice is open source. When a user clicks "view this skill" on any active skill, they see the actual SKILL.md and supporting files, formatted for human reading, with provenance and the ability to fork.

The position implied by all of this is uncomfortable for the rest of the legal-AI category, and that is intentional. Customers who have been paying for software whose only real innovation is a hidden system prompt are entitled to see what they have actually been buying. When the curtain is pulled back, some products will hold up. Many will not. LQ.AI's bet is that an open, transparent product built on community-curated skills is better than a closed, opaque product built on the assumption that the user cannot see what is happening — and that the resulting trust is worth more than the marketing.

For more on this philosophy, see PRD §1.3 Transparency as a Founding Principle and §7.1 Project Philosophy.