AI is shifting games and platforms from static content and manual ops to governed systems of action. The winning pattern: fuse gameplay, economy, social, and platform telemetry; reason with live context and design rules; then execute only typed, policy‑checked actions—matchmaking, offers, events, tuning, moderation—with preview and rollback. Optimize for incremental retention and revenue while enforcing … Read more
Personalized recommendations work best when delivered as a governed system of action: retrieve trustworthy facts about users and items, rank with calibrated models that respect business and safety rules, and execute only typed, policy‑checked actions (set rails, reorder modules, send notifications) with preview and undo. Optimize for incremental engagement and retention, not clicks alone; enforce … Read more
AI is transforming media and entertainment from generic catalogs into governed, context‑aware “systems of action.” Winners combine trustworthy retrieval over catalogs/metadata/rights, fit‑for‑purpose models for search, recommendations, and ads, and typed, policy‑gated actions that personalize rows, rails, notifications, ad decisions, and live‑ops—always with preview, approvals, rollback, and explicit SLOs for latency, quality, safety, and cost. Focus … Read more
Great AI SaaS testing goes beyond unit tests. It continuously validates three things: 1) the product’s facts and payloads are correct (grounding and JSON/action validity), 2) actions are safe and compliant (policy, privacy, fairness), and 3) the system meets performance and cost SLOs in production. Build a layered test strategy: golden evals for content and … Read more