AI Feature Productionization. @ai-productionization

The AI Feature Productionization sprint closes the gap between a proof-of-concept that works in a demo and a feature that works at 2 a.m. under real load. Most GenAI vendors deliver the prototype and leave; the distance from there to production — retries and fallbacks, evaluation gates, security review, cost ceilings, monitoring — is where AI initiatives quietly die. The finish state is your AI feature live for real users: architecture hardened, quality gated by evaluation in CI, security and data handling reviewed, spend capped and attributed, and dashboards watching hallucination signals, latency, and cost.

Production-first GenAI is Scrums.com's stated stance — those three metrics are tracked as first-class delivery metrics from sprint one on every build. This item applies that standard to a POC you already have, whoever built it.

Production Architecture Rebuild

The POC's prompt spaghetti and hardcoded calls rebuilt into a maintainable service: versioned prompts and configs, provider abstraction with failover, timeouts, retries, and graceful degradation when the model misbehaves.

Evaluation & Release Gating

Test sets and automated scoring for the feature's core behaviors, wired into CI as release gates — so prompt and model changes are regression-tested like any other code change.

Security & Data Controls

Prompt-injection defenses, PII handling and redaction, secrets out of prompts, tenant isolation, audit logging, and a data-flow review aligned to your compliance posture.

Monitoring & Cost Governance

Production observability on quality signals, latency, error rates, and token spend — attributed per feature and customer tier — with budget alerts, rate limits, and cost ceilings that prevent bill surprises.

1. Scope — Audit the POC, define the production bar (reliability, quality, security, cost), and fix the gap list.
2. Build — Rebuild the architecture, install evaluation gates and controls, and run a staged rollout behind flags.
3. Handover — Full production traffic, dashboards and runbooks live, and an operating guide for evolving the feature safely.

The AI Feature Productionization is a menu item on the Scrums.com delivery catalog, available at every plan tier. Add it to your plan backlog and your delivery team schedules it like any other item — scoped, tracked, and reported through the SEOP. See Delivery Plan Tiers.

The POC was built by someone else. Is that a problem?

No — it is the common case. The audit step establishes what exists and what it actually does; the rebuild keeps what is sound and replaces what is demo-ware.

Will users notice the transition?

Only if quality improves. The rollout runs behind feature flags with the old path as fallback, and evaluation gates ensure the productionized version meets or beats the POC's behavior before full cutover.

Who operates it afterward?

Your team, with the runbooks and dashboards handed over. Teams that want ongoing model operations — re-benchmarking, evaluation upkeep, incident response — continue with the Model Ops Retainer from the menu.