The AI Documentation Audit

Brittney Ball

Founder; Ex-Meta; MIT AI Safety Fellow

The audit that grades AI documentation before a regulator does.

I spent years as a documentation engineer at Meta, serving 3,000+ developers, and the hardest part was never the writing. It was being handed a mandate with no standard behind it. Someone tells you to improve the docs before the deadline, then leaves you to define "good enough." You reach for what everyone reaches for: a longer FAQ, a legal disclaimer, a feature list. None of it tells you whether a real person could understand what your AI does and where it fails.

Every Wednesday I grade real AI companies on exactly this, in public. The EU AI Act's Article 50 transparency obligations apply from August 2, 2026. California's training data law is already in effect. Colorado's rewrite arrives January 1, 2027. The dates keep moving, and every team I audit has quietly decided that means the work can wait. The obligation underneath them has not moved, and good intentions are not something you can hand a regulator.

This course is where I hand you the instrument I built and tested. You will audit the product that worries you and grade it against a framework that holds up when an engineer pushes back. You cannot fix a gap you cannot measure. In four weeks, you will measure yours.

What you’ll learn

Learn to audit, grade, and fix any AI product's documentation, and become the person in the room who can prove what it scores.

  • Run the 7-Question Audit and the ADECP framework on any product and produce a letter grade that holds up when an engineer pushes back.

  • Leave with a repeatable method, so you can audit the next product, and the one after that, without starting from scratch.

  • Apply the same instrument I use to grade AI companies in public every week on the product that actually worries you.

  • Stop scoring on instinct. Cite the evidence for every grade, so "I think it's fine" is never your answer to leadership again

  • Replace vague quality debates with a number and a band your whole team can agree on and act from.

  • Defend any score against pushback, because it rests on what a real user sees, not on what the company says it intended.

  • Rewrite failing limitation statements so your warnings guide users instead of shielding lawyers, using a formula you will reuse for years.

  • Turn "AI may be inaccurate" into a statement that names the failure, the trigger, and what the user should do about it.

  • Give users warnings they can act on, which cuts the support tickets that come from people misjudging what the AI can do.

Learn directly from Brittney

Brittney Ball

Brittney Ball

AI Doc Strategist. Engineer. Author. Community Builder. 2x Founder. Ex Meta

See all products from Brittney

Who this course is for

  • The Documentation Engineer or DevRel Pro: You own the AI docs and were handed no standard to hold them to.

  • The Founder or Product Lead: You ship AI features and suspect your documentation would not survive a regulator or a burned customer.

  • The Career Shifter: You are moving into tech writing, AI governance, or compliance. You want a real skill the market is about to demand

What's included

Brittney Ball

Live sessions

Learn directly from Brittney Ball in a real-time, interactive format.

Community of peers

Stay accountable and share insights with like-minded professionals.

Certificate of completion

Share your new skills with your employer or on LinkedIn.

Maven Guarantee

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Course syllabus

Week 1

Aug 21—Aug 23

    The Gap You Have Been Trained Not to See

    1 item

Week 2

Aug 24—Aug 30

    Scoring Without Flinching

    1 item

Schedule

Live sessions

1-2 hrs / week

Projects

2 hrs / week

Async content

1 hr / week

Frequently asked questions

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Reimbursement

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Team discount

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Save 20%+ when 2 or more teammates enroll in the same cohort.

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Private cohort

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A dedicated cohort with a custom schedule and curriculum, tailored to your team.

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$1,950

USD

Aug 21Sep 13
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