PP&A designed two structured interview guides, one for each perspective, and led in-depth interviews with senior AI and engineering leaders building production generative AI systems in banking, healthcare, insurance and technology, alongside practitioners with experience inside model-provider organizations. The developer guide walked through the sophistication of current deployments, selection criteria such as performance, latency, cost and licensing, the additional engineering needed to work around model limitations, and the total cost of self-hosting open models versus managed APIs. The provider guide probed prioritization frameworks, community engagement channels, benchmark strategy and the reasons capability launches fail to land.

The findings were synthesized into a report structured around four questions: what developers are building and how, where open and closed models stand today, how models are evaluated and selected, and what this implies for a provider's capability roadmap. Each theme paired interview evidence with a specific recommendation for the client.

The client received a report built around its four questions. It described what enterprises are building with generative AI and where adoption is concentrating, how organizations divide work between open and closed models, and where each falls short. It showed how developers evaluate, select and switch between models, and how model providers prioritize capabilities, gather feedback and communicate launches. Each theme closed with a recommendation for the client, covering capability priorities, the positioning of its model family, developer feedback and launch practice.

The study gave the client an outside-in view of what developers value and how model providers plan, as input to deciding which capabilities to build next.