01
Boundaries first
Agent autonomy was designed around permissions and execution isolation instead of added after the platform was already risky.
CASE / 01 · Confidential platform · shipped end-to-end
AI Agent
Marketplace
A two-sided platform where creators publish agents, customers discover and run them, and a controlled orchestration layer handles execution across multiple model providers.
Agent marketplaceOrchestrationSandboxingLLM routingMetering
Full platform
Product, design, architecture, delivery
Multi-provider
Model routing without hard coupling
Shipped
End-to-end production delivery
Screens withheld · client request
The challenge
The product needed to serve two very different users at once: creators publishing agents and customers expecting safe, predictable execution. Discovery and presentation mattered, but the harder work lived beneath the interface—versioning agents, isolating runs, managing tool access, routing model requests, measuring usage, and giving operators enough visibility to support the marketplace.
What we built
Windrose owned the product architecture, experience design, and implementation end-to-end. We designed a marketplace shell around a provider-aware runtime, then connected publishing, discovery, sandboxed execution, usage metering, and operator controls into one coherent product. The system was structured so new models and agent capabilities could be introduced without rebuilding the customer experience around every provider change.
MarketplaceAgent publishing, versioned listings, discovery, product detail, and creator-facing management.
RuntimeSandboxed execution with explicit boundaries around tools, inputs, and request lifecycle.
OrchestrationProvider-aware model routing, retries, failure handling, and coordination between specialized agent roles.
OperationsUsage metering, entitlement checks, execution visibility, and the internal controls needed to run the platform.
A coherent product around complex infrastructure.
The result was a production-ready marketplace that made advanced agent infrastructure understandable to creators, customers, and operators. Windrose delivered the system as an owned product rather than a collection of disconnected AI experiments.
/02 — Engineering decisions
The choices beneath the interface.
The strongest AI product decisions are often invisible to the user. These were the boundaries that kept the system coherent, maintainable, and ready for real use.
02
Provider-aware core
The orchestration layer could make model choices without exposing provider complexity throughout the product.
03
Observable runs
Execution state and failure paths were treated as product requirements, not hidden implementation details.
04
Two-sided UX
Creator workflows and customer workflows were designed as one marketplace system with different jobs and levels of control.
Windrose turned the AI agent marketplace into a coherent, production-ready platform. They made complex orchestration and infrastructure decisions understandable, shipped consistently, and approached the product like owners rather than an outsourced development team.
/03 — Continue exploring
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