Description

A focused course, tailored for you

The Associate GC AI Product Launch Review Playbook

Run model-card scrutiny, the provenance memo, and the multi-jurisdiction launch packet for a consumer AI feature on engineering's clock.

A product-counsel review on a consumer AI feature is rarely held up by a hard legal question. It is held up because the review packet has no agreed shape. Engineering ships dry runs while counsel is still negotiating what 'reviewed' means.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

An Associate General Counsel covering AI product launches sits between three accelerating pressures. Product wants the legal review on the shared roadmap as a single Jira ticket. Privacy counsel wants the provenance memo before the data is loaded into the training pipeline. Policy counsel wants the deceptive-design and consumer-protection risk register reviewed before the launch communications draft is locked. None of those teams has the same template, the same checklist, or the same definition of 'cleared'. So every launch turns into a renegotiation of the review process itself. The course gives the Associate GC the standing review packet: the artefacts every reviewer signs, the order they sign them in, and the matrix that maps EU AI Act, UK pre-enforcement posture, California ADMT, Texas TRAIGA, Colorado AI Act, and the Brazil ANPD AI consultation onto a single launch readiness sheet. The output is a launch review that runs at engineering pace because the shape is agreed before the feature is built.

What you walk away with

A model-card scrutiny checklist a product-counsel reviewer can complete in one sitting.
A training-data provenance memo template a reviewer signs in under an hour.
A deceptive-design and dark-patterns risk register product managers will keep current.
A multi-jurisdiction launch readiness matrix covering EU, UK, California, Texas, Colorado, and Brazil on one page.
A privileged pre-launch counsel memo template that survives a litigation hold review.

The 12 modules

Module 1. The launch review packet, end to end

What an in-house product-counsel review actually consists of on a consumer AI feature: the seven artefacts the launch review committee expects to see, who owns each one, and the order signatures arrive in. The module walks an example feature from product brief through committee approval and shows where most reviews stall (the provenance memo and the deceptive-design register, almost always). Templates for each of the seven artefacts ship with the module.

Module 2. Model card scrutiny without depositions

A model-card review checklist tuned to what a reviewer actually has to assess: training corpus boundaries, evaluation methodology, known failure modes, deployment scope, retraining cadence. Built so a reviewer signs the checklist in one sitting, not a week of back and forth with the modelling team. Includes the three follow-up questions every reviewer ends up asking and the standard form the modelling team responds in.

Module 3. Training-data provenance memo

The provenance memo template that addresses the three questions every privacy counsel and every external regulator will ask: where the data came from, what consent or licensing basis the company is relying on, and what filtering was applied before training. Built to be signed in 40 minutes by a reviewer who has the engineering inputs ready. Includes the three common gap patterns and how to flag them without blocking the launch.

Module 4. Deceptive design and dark patterns register

A working risk register for consumer-facing AI features: persuasive design choices, default settings, opt-out friction, AI-generated content disclosure, and the FTC consumer-protection posture. Built so product managers update it the same week the UX changes, not three weeks after launch. Includes the prioritisation rubric and the two-line escalation rule that keeps the register live.

Module 5. EU AI Act launch readiness

The launch readiness slice of the EU AI Act tuned to a consumer AI feature: risk categorisation, transparency obligations under Article 50, GPAI model obligations where relevant, and the operator-deployer split. The module gives the launch matrix entry for the EU column: what evidence the product team needs to show, where it lives, and which artefact in the launch packet covers it.

Module 6. UK pre-enforcement posture and ICO guidance

The UK column of the launch readiness matrix: the cross-regulator pre-enforcement posture, ICO AI guidance, CMA market study read-outs, and the principle-based approach a reviewer needs to articulate. Templates for the UK-specific evidence sheet and the two-page principles memo a reviewer attaches to the launch packet.

Module 7. California ADMT and the multi-state US picture

California Automated Decision-Making Technology rules in operational form: which features in scope, what notices the consumer sees, how the opt-out architecture maps onto the product, and how California sits alongside Colorado AI Act, Texas TRAIGA, and the federal NIST AI RMF voluntary posture. The module ships the US column of the launch readiness matrix and the cross-state decision tree.

Module 8. Brazil ANPD and the LatAm posture

The Brazil ANPD AI consultation outputs, the LGPD intersection, and the LatAm posture a launch packet has to address when the feature ships in Portuguese or Spanish. Includes the ANPD evidence sheet, the LGPD provenance overlay, and the rapid-update sheet the team uses when ANPD issues new guidance mid-launch cycle.

Module 9. Children, minors, and age-appropriate design

The age-appropriate design slice across the UK Children's Code, California Age-Appropriate Design Code, Australian draft codes, and the EU best-interests overlay. Templates for the minors-impact memo, the age-assurance evidence sheet, and the launch packet annex that addresses default privacy settings, advertising controls, and content moderation behaviour for under-18 users.

Module 10. Privileged pre-launch counsel memo

The single privileged memo the product-counsel team writes before the launch review committee. Built so it survives a litigation hold review: clear identification of legal advice purpose, clean separation of business decisions from legal advice, named counsel of record, and the artefact list it covers. The module ships the template and three worked examples redacted from real launch reviews.

Module 11. Engineering pod working rhythm

How the product-counsel review actually runs at engineering pace. The standing weekly with the engineering pod. The asynchronous artefact handoff in the shared ticketing tool. The two-page decision log the engineering lead can read in five minutes. The escalation rule that brings in the Deputy GC without burning political capital. Built so the review process is the rhythm, not an interrupt.

Module 12. Post-launch monitoring and incident playbook

The post-launch slice: monitoring metrics the counsel team actually receives, incident triage when a deceptive-design complaint or a regulator inquiry lands, and the document retention map for the launch packet. Templates for the post-launch monitoring memo, the regulator first-response packet, and the lessons-learned write-up the next launch reuses. Closes the loop so the next launch starts from a known shape.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

Product brief lands and the launch ticket gets opened on the legal Jira board: modules 1 and 11.

Modelling team requests provenance memo sign-off before training pipeline run: modules 2 and 3.

Launch review committee scheduled and the multi-jurisdiction matrix is due: modules 5, 6, 7, 8, 9.

Feature ships and the post-launch monitoring window opens: modules 4, 10, 12.

What you get with this course

12 written modules in the Art of Service learning environment with worked examples drawn from consumer AI feature launches.
Downloadable templates for each of the seven launch packet artefacts: model card scrutiny checklist, provenance memo, deceptive-design register, jurisdiction matrix, minors-impact memo, privileged pre-launch counsel memo, post-launch monitoring memo.
A hand-built implementation playbook tuned to the Associate GC role, covering the standing review packet, the engineering pod rhythm, and the post-launch loop.
A 30-day money-back commitment and no automatic renewal.

What you will have in hand by Day 1, Week 1, Month 1

Within 24 hours: account in the Art of Service learning environment is provisioned and the hand-built implementation playbook is delivered alongside it.

Week one: model card scrutiny checklist and provenance memo template installed and rehearsed on a current feature.

Week two: jurisdiction matrix populated for the next launch, deceptive-design register stood up with product owners.

Week three: engineering pod working rhythm established, privileged pre-launch counsel memo template adopted.

Week four: post-launch monitoring loop closed, lessons-learned template adopted for the next launch.

Before and after

Before

Every launch becomes a renegotiation of what 'legal review' consists of. Provenance memos arrive in five different shapes. The deceptive-design register is two product cycles out of date. The jurisdiction matrix is rebuilt from scratch for each feature. The engineering lead reads the legal review as a black box and works around it where possible.

After

The launch packet has a known shape. Reviewers complete the model card checklist and the provenance memo in one sitting. The deceptive-design register is live because product managers update it weekly. The jurisdiction matrix is a single page that updates when the underlying rules update. The engineering pod treats the legal review as part of the rhythm, not an interrupt.

What happens if you do not address this

Without a standing review packet, every launch costs the Associate GC a week of renegotiation, and the launch review committee eventually flags the legal review process as the slow path. That changes the political position of the in-house legal team relative to engineering, and the next reorg moves the review function closer to engineering rather than closer to the GC.

Who it is for

An Associate General Counsel inside a platform-scale technology company, working on product-counsel coverage for consumer-facing AI features. Reports into a Deputy GC or GC for a product area. Partners daily with privacy, policy, content, and engineering counsel. Owns the legal sign-off artefacts that go into the launch review committee, not the policy white papers that go to regulators.

Who this is NOT for. Not for outside counsel selling AI advisory hours. Not for policy-team lawyers writing position papers to regulators. Not for compliance generalists with no product-launch exposure. The artefacts assume the reader is the named lawyer on a launch ticket.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access.

Time investment. About four hours per week for four weeks for the core artefacts. The playbook is consulted as a reference for the next several launch cycles.

Why $199 is the right number

The closest alternative is a Big Law AI launch advisory retainer at five-figure monthly rates that produces memos rather than working templates the product-counsel team can run. The next alternative is internal sprint workshops, which produce alignment but no installed artefacts. This course installs the artefacts and the rhythm, at a price that does not need expense approval.

FAQ

Is this jurisdiction-specific?

The launch readiness matrix covers EU, UK, California, Texas, Colorado, and Brazil. The implementation playbook is tuned to the rollout footprint the Associate GC names at purchase.

Is this a CLE course?

No. It is an operational playbook. CLE credit varies by jurisdiction and is not certified here.

Does this replace privacy counsel?

No. The provenance memo template is built to be co-signed with privacy counsel and the model card scrutiny checklist is built to be co-signed with policy counsel. The course gives the artefact shape, not the substantive review by other in-house counsel.

What if my product is not consumer-facing?

The templates were built around consumer AI features. Adapting them to enterprise B2B AI features is straightforward and noted in each module, but the worked examples assume a consumer launch.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.