Use AI in Your Work
Move from a clear assignment to source-linked work products, focused revision, and repeatable quality checks.
Give AI a brief it can actually follow
Turn a broad request into a reviewable assignment.
Build a reusable task pack
Save the brief, examples, and checks that make a recurring task work.
Keep evidence, instructions, and inference separate
Prevent a summary from quietly becoming a source of facts.
Package source material so the model can use it
Lists, tables, JSON, and tagged documents each suit different material. Choose the format deliberately, give every source an ID, and put long material before the question.
Ask for the working: chain of thought and reasoning models
Asking a model to reason step by step improved accuracy on multi-step tasks. Newer reasoning models do this on their own. Either way, written reasoning is output to check, not proof.
Build a chronology that survives checking
Extract events, preserve conflicting dates, and audit coverage.
Turn a transcript into useful examination preparation
Preserve questions, answers, qualifications, and source locations.
Research with AI without outsourcing the authority check
Separate finding candidates from verifying propositions.
Build a drafting workflow around the record
Move from issues to an outline, then draft and verify one section.
Use AI to challenge an argument
Turn simulated opposition into source-linked questions you can investigate.
Improve a draft without changing its meaning
Review substance and expression in separate passes.
Design a review table before generating it
Make each column answer one question you can check.
Test an AI workflow on work you can assess
Measure omissions, unsupported additions, and total review effort.
Map where information goes before using a tool
Turn confidentiality questions into a concrete system review.
What courts expect when you use AI
Check the rule, verify the source, and keep a record of the review.