API teams lack common tooling and guidance to deliver MCP servers alongside their existing APIs for copilot integration.

Traditional filter-based catalog search doesn't match how developers think about their problems, leading to duplicate API development.

API documentation and metadata quality must improve so that both developers and AI agents can effectively discover and use internal APIs.

Governance rules need to be available directly in developers' coding assistants and AI agents, not just in standalone tools and pipelines.

Enterprise security restrictions prevent using standard distribution mechanisms to deliver governance rules to all API designers.

Riley has an accurate central API inventory but cannot account for APIs on teams' own AWS API Gateways.

Riley has a clean API inventory but needs to understand how APIs map to products and business capabilities.

Riley realizes reuse isn't just about whole APIs—it's about reusing schemas, data elements, headers, and parameters.

Riley was asked by leadership to answer how well they are reusing APIs and how they are incentivizing improvement.

Developers perceive governance as friction and avoid it unless compliance is the easiest path.

Organizations can enforce coding standards and CI gates but cannot enforce equivalent governance for the Markdown files that shape AI agent behavior.

Beyond MCP, protocols like A2A, ACP, AP2, and x402 are proliferating — enterprises need unified governance across all agent communication protocols, not just one.

Agentic browsers and AI-native workspaces are becoming the primary interface for discovering and consuming services — APIs need to be optimized for Generative Engine Optimization (GEO), not just traditional developer portals.

Engineers at closed-off enterprises shipping their first public API now have to ingest OpenAPI, Arazzo, JSON-LD, MCP, agent skills, async patterns, and agent-payment standards in weeks — with no sequenced onramp that says what to learn, when, and why.

Engineering leads see agent-era API strategy as urgent before leadership does. They need a playbook — language, evidence, and risk framing — to convince executives without sounding like AI hype, especially at responsibility-mindset enterprises that won't move fast just because the market is.

Need a productized way to check incoming OpenAPI schemas against an enterprise data model so governance teams know where each new API fits or diverges before it ships.

Need an asset database of APIs that auto-publishes specs and breaking-change changelogs into the systems developers actually use — Confluence, intranet, internal portal — because most enterprises do not yet have a true internal developer portal.

Need every API to carry first-class metadata linking it to the job-to-be-done, the team goal, and the group strategic objective it serves, so anyone working on it knows they are going in the right direction.

Business product managers need to design and stand up the APIs they need without having to develop a backend, because most enterprise APIs are data APIs and the design work is about assembling existing data.

Even with identity and onboarding solved, API providers carry advertising-era baggage — own the user, distrust middlemen — that blocks them from issuing tokens to agents at all.