Game soft launch review

Game Soft Launch Review

Produce a Game Soft-Launch Program that converts bounded real-player exposure into causal evidence and automated release decisions without reducing the declared final game to a conventional MVP.

Atomic boundary

Own cohort/market design, exposure stages, hypotheses, telemetry, economy/live ops test schedule, acquisition/creative cells, pass/watch/fail predicates, decision authority, and scale/hold/pause/withdraw evidence. Do not own the game design, channel submission, full marketing operating system, or provider payment system.

Use a draft artifact ID and explicit inputs from Game Design, Economy, Distribution, Marketing, Analytics, Payment, Refund, and Support owners. A deterministic delivery process may seal serialized versions and digests later; never invent a digest or treat a draft as proof.

Agent-first invariant

Soft launch is an exposure and proof system, not permission to omit production architecture. Build the complete declared target, automation, migrations, observability, support, low-end, accessibility, localization framework, content pipeline, and shutdown controls before exposure. Construct all test cells and decision automation now; activate spend, regions, features, and concurrency through bounded gates. Unknown data never authorizes unbounded scale.

Workflow

1. Define traceable game, build, content, economy, and policy identities—draft IDs during design and observed exact values only during exposure—plus genre/audience/age modes, target global promise, regions/platforms, acquisition sources, monetization, cohort horizon, budget/spend caps, and irrecoverable harm boundaries.
2. Read references/game-soft-launch-patterns.md. Write falsifiable hypotheses for comprehension, delight/mastery, FTUE, core/meta loops, progression, social/liquidity, content, economy, IAP/IAA, performance, support, and market transferability.
3. Build a cohort cell matrix across install date, version/content/economy policy, region/locale, platform/device tier, acquisition source/creative, age mode, payer state, and experiment exposure. Prevent cross-cell leakage.
4. Set event/identity/consent contracts and pass/watch/fail bands for cold start, activation, D1/D7/D30 retention, session quality, progression, economy, IAP/IAA, crashes/ANRs, latency, battery/thermal, store conversion, support, safety, accessibility, localization, and trust.
5. Sequence deterministic simulation, agent QA, internal playtest, low-risk cohorts, market cells, spend cells, and scale steps. Synthetic agents expand coverage but never prove human comprehension, culture, usefulness, trust, or delight.
6. Separate product defects, cohort mix, acquisition quality, creative/listing, novelty, live-ops cadence, economy tuning, price/offer, and regional effects. Use holdouts and immutable version/policy identities.
7. Define daily automated readback, anomaly/fraud detection, support/community evidence, content/economy calendar, migration/compensation, and exact scale/hold/pause/withdraw/rollback/forward-fix actions.
8. Produce a decision record that states evidence, uncertainty, countermetrics, global-transfer limits, next bounded exposure, and authority.

Source verification

Retrieve current store/test-track, regional availability, ads/IAP, child/age, privacy/consent, reviews/community, refund, promotion, and acquisition-platform authority for every active cell. A test market or platform permission is not a global compliance or product-fit verdict.

When not to use

• Use game-design-blueprint when the primary job is designing or repairing core play, progression, content, social, feel, retention, or monetization.
• Use software-distribution-readiness for submission assets, certification, reviewer access, staged release mechanics, and exact live-channel evidence.
• Use marketing-automation-blueprint for the complete multi-channel creative, organic, lifecycle, paid-spend, attribution, and shutdown operating system.
• Use launch-readiness-review for a cross-domain final admission verdict when the soft-launch learning program is already complete.

Guardrails

• Never scale blended metrics that hide version, market, device, source, creative, age, payer, or experiment cohorts.
• Do not over-monetize early cells and then treat damaged retention as product truth; preserve baseline/no-paid-acceleration reachability.
• Purchases, durable progress, social relationships, and creations survive normal experiment/season/region changes; resets require explicit migration, compensation, support, and authority.
• One market is evidence for its cell, not global proof. Cultural/locale and channel differences remain hypotheses until tested.
• No autonomous system may raise spend/exposure caps or weaken quality, safety, consent, payment, economy, or rollback gates to chase growth.

Output contract

Return one typed Game Soft-Launch Program with:

1. exact artifact identities, hypotheses, cells, budgets, authorities, and ruin boundaries;
2. exposure DAG from simulation/playtest through regions, spend, and scale;
3. cohort/identity/consent/event contract and immutable experiment policy;
4. pass/watch/fail gate matrix with confidence/uncertainty and machine actions;
5. FTUE, loop, progression, economy, IAP/IAA, live-ops, performance, support, community, safety, accessibility, localization, and store evidence plan;
6. anomaly/fraud, pause/withdraw, rollback/forward-fix, migration, compensation, and live-readback controls;
7. scale/hold/pause/withdraw decision record and next bounded exposure.

Complete only when every cell and metric maps to an action, unbounded spend is impossible, exact versions are traceable, and global transfer claims remain bounded by evidence.