Glossary
The language of the AI-native practice.
Plain-language definitions for the terms adnah uses across the method, the audit, and the journal - so nothing here requires decoding.
- AI-native practice
- A legal practice rebuilt around AI as a default, systematic first step on every matter - not a firm that occasionally uses an AI tool. Defined by seven markers: transparent pricing, automated intake, low-friction client contact, AI running first by default, measurable improvement over time, fast turnaround, and technical capability treated as core to the practice.
- MATTER Method
- An operating doctrine claiming all legal work decomposes into six primitives - Matter, Actions, Time, Team, Evidence, Research - that must be named, then systematised, then automated, in that fixed order.
- Matter (primitive)
- The atomic unit of legal work and the container every other primitive attaches to. A practice has 'named' this primitive when a competent stranger can open any matter and understand its complete state in ten minutes without asking anyone.
- Action (primitive)
- A discrete, named, repeatable step that moves a matter from opened to resolved. Extracting a firm's action library turns tacit expertise held in one lawyer's head into a written, improvable, automatable playbook.
- Evidence anchoring
- A standing rule that no factual assertion enters a work product without a citation to a specific, checkable source - page and paragraph, not just a document name. The primitive that answers the fear of AI hallucination with a workflow rule rather than a promise about model quality.
- Research stock
- Treating legal research as a compounding, searchable body of firm knowledge rather than a one-off memo that evaporates into a folder once its matter closes. The opposite of researching the same question from zero every time it recurs.
- Billable hour
- The traditional legal pricing unit: time recorded and invoiced after the fact. Trains a practice to record time rather than manage it, and structurally cannot survive automation, because every hour AI removes is revenue the billing model has no way to recapture.
- Fixed fee
- A price quoted to the client before work starts, made survivable only once a practice has real duration data on its named actions - otherwise fixed pricing is a guess, not a policy.
- Agent (legal AI)
- Software that executes a named action - drafting, checking, monitoring - inside an explicit doer/reviewer structure, with a human lawyer retaining review responsibility. Distinct from a chatbot a lawyer pastes text into occasionally.
- Hallucination
- A confident but false assertion produced by an AI system - a citation that doesn't exist, a holding that's inverted. Addressed structurally by evidence anchoring rather than by waiting for better models.
- AI-augmented (vs. AI-native)
- A firm that has adopted AI tools without rebuilding its underlying operating model - pricing stays hourly, intake stays manual, AI use is incidental rather than systematic. The overwhelming majority of large-firm 'AI adoption' falls here.
- Legal ops
- The operational infrastructure underneath legal delivery - intake, matter management, pricing, measurement - as distinct from legal judgment itself. Treated as core, not a support function, in an AI-native practice.
- Transformation (adnah usage)
- adnah's term for a full engagement: naming, systematising, and automating a practice's six primitives end to end, typically six to fourteen weeks, producing working artefacts the firm owns and can run without the studio afterward.
- Team primitive
- The explicit assignment of doer, reviewer, and decider to every named action - the delegation structure that makes it safe to hand routine actions to a non-human doer while a human keeps review responsibility.
- Time primitive
- Treating time as a property of the matter - structured deadlines and measured action durations - rather than a product sold to the client in six-minute increments.
See it applied
Read the method, or score your own practice.