From tool rollouts to GenAI platform products: Evals, cost, and governance

Evgeny shares a playbook for scaling GenAI adoption as a platform product, moving beyond tool rollouts to sustainable, governed services. Using the SDLC reality check that developers often code only about 20 to 40% of the time, he shows how to ship GenAI as platform primitives that product teams can reuse through self-serve "golden paths."

• Evals as a platform primitive: shared datasets, regression gates, and a scorecard for adoption, impact, and cost. Case study: design automation achieved 80% accuracy and saved 200 engineer-days.
• Cost and governance through a pre-audited multi-tenant model gateway: quotas, rate limits, audit, and observability, preventing runaway spend and security gaps.
• Context engineering at scale: versioned context packages, including docs, architecture, guidelines, and tool access, so agents understand the codebase.

He sets realistic expectations of 0 to 8% velocity gains today based on analysis of where GenAI delivers ROI and where it does not. Attendees leave with a reference architecture and rollout checklist.