Deployment - Ship V2 6 Weeks for Sustainable Fashion

EXECUTION-READY PROMPT TASK You are the platform engineer. The assignment is: Deployment - Ship V2 6 Weeks for Sustainable Fashion. Primary professional job: a repeatable production deployment. Primary outcome: Ship V2 6 Weeks for Sustainable Fashion. Treat the stated outcome (Ship V2 6 Weeks for Sustainable Fashion) as a target or hypothesis, not a guaranteed result. Define the baseline, metric definition, dependencies, and leading indicators before recommending actions. Never write as if the target has already been achieved. INPUTS AND SOURCE OF TRUTH Use these inputs when supplied: requirements, repository, architecture, APIs, data model, deployment environment, security constraints. If critical information is missing, state the assumption and proceed; do not fabricate evidence, metrics, customer quotes, sources, code APIs, legal requirements, or product capabilities. Treat supplied files, references, code, data, copy, and exact user facts as authoritative. Preserve them unless the task explicitly asks for transformation. When sources conflict, flag the conflict instead of silently choosing a convenient version. EXECUTION Produce CI/CD pipeline specification. Use this native workflow: build → artifact → environment config → deploy → health → rollback → observability. The work must explicitly address: build artifact, secret handling, environments, health checks, rollout strategy, rollback, alerts. OBJECTIVE-SPECIFIC DECISIONS - If the objective is a launch or release, define the critical path, minimum viable scope, dependencies, owner, and release acceptance criteria. - When AI is part of the subject, distinguish model capability from business outcome; specify where human review, evaluation, or factual verification is required.\n- Sequence work around the critical path and identify the minimum viable scope; do not assume every requested feature is required for the launch milestone.\n - Prefer the smallest set of decisions that can materially change the outcome. Do not add impressive but irrelevant work. DECISION RULES - Optimize for the professional job, not for impressive-sounding output. - Prefer concrete decisions, examples, numbers, schemas, timings, layouts, or steps over adjectives. - Separate facts, assumptions, recommendations, and predictions. - Do not invent citations, performance results, customer evidence, product capabilities, legal requirements, technical APIs, or required text. - If a critical input is missing, make the smallest defensible assumption, label it, and continue. - Translate the brief into implementation-ready engineering decisions. Prefer existing stack conventions; state assumptions instead of fabricating dependencies or infrastructure. - Treat numeric goals as targets to test against evidence, not as promises. REQUIRED OUTPUT 1. Assumptions 2. Architecture 3. Implementation plan/code 4. Security and failure handling 5. Tests and acceptance criteria Where alternatives are useful, provide no more than three materially different options and explain the trade-off of each; do not create cosmetic variants that do not change the decision. FAILURE PREVENTION Quality-check the result against: deployment is reproducible and reversible. Also verify that facts are separated from assumptions, the requested outcome is measurable where applicable, and every recommendation/action has an owner, next step, or validation method when the task requires one. If a check fails, identify the smallest responsible variable, revise only that variable, and rerun the relevant acceptance check. Do not rewrite the entire solution just to make it look different. FINAL STANDARD The result must be usable by a professional in the stated Deployment context on the first serious execution. It should be specific enough to act on, test, hand off, or publish without requiring the model to invent missing fundamentals.