Genai feature launch
Genai Feature Launch
tasks: 42 constraints: 9 team: 17 timesteps: 28
Workflow Goal
Objective
Objective: Launch a user-facing GenAI feature with built-in safety gates to deliver useful assistance (e.g., drafting/search/summarization) while meeting privacy, security, and transparency expectations, and establishing governance evidence suitable for internal and external scrutiny.
Primary deliverables
- Product definition pack: intended use and misuse, task boundaries, user journeys, success metrics, and out-of-scope behaviors (what the feature must refuse or route).
- Data protection & DPIA bundle: data-flow maps, lawful basis/consent model, retention/minimization rules, DSR handling paths, third-party/model disclosures, and residual-risk register.
- Threat model & control plan: risks across prompt injection, data exfiltration via tools, unsafe function calling, secrets exposure, rate/credit abuse; mapped controls incl. sandboxing, least privilege, filters.
- Safety evaluation suite: red-team scenarios and abuse tests, hallucination/jailbreak metrics, benchmark results with failure analysis and a remediation log to "fix or fence" issues before launch.
- Transparency & provenance assets: user-facing AI disclosures and capability limits, content labeling/ watermarking or provenance where feasible, model/system cards, and policy copy for Help/ToS/Privacy.
- Observability & guardrails: runtime moderation checks, PII/unsafe-content filters, event logging, alerting thresholds, and dashboards for safety/quality/cost; rollback and kill-switch procedures.
- Pilot & rollout plan: design-partner cohort, A/B experiment design, acceptance gates, rollback criteria, staged exposure (internal → limited external → GA) with entry/exit criteria.
- Governance package: decision logs, launch-gate materials, approvals (Product, Security, Privacy/Compliance, Legal), and audit-ready links to evidence and artifacts.
Acceptance criteria (high-level)
- Red-team coverage demonstrated across injection/exfiltration/unsafe tool use; all critical issues remediated or explicitly risk-accepted by the accountable owner with compensating controls.
- DPIA completed with privacy controls validated in staging and production paths; residual risks documented and accepted; no unresolved high-risk privacy issues at launch gate.
- Clear, testable transparency: disclosures present; labeling/provenance applied where applicable; telemetry shows safety checks executed in ≥99% of eligible events with alerting for misses.
- Formal sign-offs captured for Security, Privacy/Compliance, Legal, and Product; launch-gate minutes and evidence stored and linkable for audit.
Team Structure
| Agent ID | Type | Name / Role | Capabilities |
|---|---|---|---|
| ai_safety_engineer | ai | Designs and runs automated red‑team campaigns Detects prompt‑injection and data‑exfiltration attempts Builds refusal/containment guardrails and tests kill‑switches Summarizes risks with reproducible evidence and metrics |
|
| red_team_specialist | ai | Designs diverse attack scenarios and playbooks Executes prompt‑injection and tool‑abuse tests Measures exploit success rates and coverage Produces prioritized remediation guidance |
|
| ml_safety_researcher | ai | Builds hallucination/factuality benchmarks Implements bias/fairness metrics and cohort tests Calibrates thresholds and acceptance gates Publishes replicable evaluation suites |
|
| privacy_engineer | ai | Designs privacy‑by‑design architectures Implements PII detection and minimization Sets consent/retention policies and audits Prepares DPIA inputs and evidence bundles |
|
| compliance_analyst | ai | Drafts and reviews DPIA/TRA artifacts Maps cross‑jurisdictional obligations Prepares AI transparency disclosures Tracks gaps and remediation owners/ETAs |
|
| security_architect | ai | Authoring system threat models Designing sandboxing and isolation controls Integrating secrets/leak detection Standing up runtime monitoring and alerts |
|
| devops_engineer | ai | Implements CI/CD and staged rollouts Configures SLOs, dashboards, and alerts Builds kill‑switches and circuit breakers Automates incident response runbooks |
|
| product_manager | ai | Writes crisp PRDs and success metrics Defines safe/unsafe feature boundaries Facilitates cross‑functional decision forums Plans staged launch and comms |
|
| documentation_specialist | ai | Authors model/system cards and user guides Maintains traceability and evidence links Curates API and operations references Prepares audit‑ready documentation bundles |
|
| chief_ai_officer | human_mock | Chief AI Officer (AI Strategy & Ethics) | Defines governance and approval gates Balances safety, compliance, and speed Chairs cross‑functional reviews Owns final go/no‑go for AI launches |
| chief_security_officer | human_mock | Chief Security Officer (Security Leadership) | Approves security architectures and controls Validates threat models and mitigations Oversees incident response preparedness Signs off on launch security gates |
| data_protection_officer | human_mock | Data Protection Officer (Privacy & Data Protection) | Reviews DPIA/consent/retention models Assesses cross‑border transfer posture Approves privacy disclosures and UX Tracks remediation on privacy risks |
| legal_counsel | human_mock | Legal Counsel (Legal & Regulatory) | Drafts/approves regulatory disclosures Assesses liability and risk trade‑offs Coordinates with regulators when needed Ensures documentation defensibility |
| product_executive | human_mock | Product Executive (Product Leadership) | Owns launch criteria and exceptions Balances scope, schedule, and risk Communicates plan and status to leadership Allocates resources to unblock delivery |
| external_ai_auditor | human_mock | External AI Auditor (Independent Audit) | Runs impartial conformance checks Validates evidence and metrics Issues findings and certification Recommends remediations and retests |
| ai_ethics_board | human_mock | AI Ethics Board (Ethics & Governance) | Reviews ethical risks and mitigations Interrogates bias and cohort impacts Sets responsible use guardrails Grants or withholds ethical approval |
| chief_product_officer | stakeholder | Chief Product Officer (Executive Stakeholder) | Prioritizes roadmap vs risk posture Arbitrates cross‑functional trade‑offs Approves staged rollout plans Holds teams to evidence‑based gates |
Join/Leave Schedule
| Timestep | Agents / Notes |
|---|---|
| 0 | ai_safety_engineer — AI safety framework and testing infrastructure product_manager — Product definition and requirements security_architect — Threat modeling and security architecture privacy_engineer — Privacy by design and data protection |
| 5 | red_team_specialist — Adversarial testing and attack scenarios ml_safety_researcher — Hallucination detection and bias evaluation compliance_analyst — DPIA and regulatory compliance mapping |
| 12 | devops_engineer — Monitoring infrastructure and observability documentation_specialist — Model cards and audit documentation |
| 18 | chief_ai_officer — AI governance and ethics oversight data_protection_officer — Privacy impact assessment approval chief_security_officer — Security controls validation |
| 25 | legal_counsel — Legal compliance and transparency review product_executive — Launch decision and business approval external_ai_auditor — Independent safety audit and certification |
| 28 | ai_ethics_board — Final ethics and responsible AI approval |
Workflow Diagram
Preferences & Rubrics
Defined: Yes.
Sources
- Workflow:
/Users/charliemasters/Desktop/deepflow/manager_agent_gym/examples/end_to_end_examples/genai_feature_launch/workflow.py - Team:
/Users/charliemasters/Desktop/deepflow/manager_agent_gym/examples/end_to_end_examples/genai_feature_launch/team.py - Preferences:
/Users/charliemasters/Desktop/deepflow/manager_agent_gym/examples/end_to_end_examples/genai_feature_launch/preferences.py