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#ai-platform-engineering

9 notes

# Production Agent Systems

All Production Agent Systems notes →

1. Designing Internal AI Platforms

Covers the reference architecture for an internal AI platform team - shared inference layer, tool/agent registry, and paved-road SDKs - so product teams build agents without re-solving auth, observability, and deployment each time.

production-agent-systems ai-platform-engineering book

2. Agent SDKs

Compares the design trade-offs of building a first-party agent SDK (LangGraph, custom Python/TypeScript wrappers) against adopting a vendor SDK, focused on API stability, versioning, and abstraction leakage at scale.

production-agent-systems ai-platform-engineering book

3. Agent APIs

Defines the contract layer for exposing agents as internal APIs - request/response schemas, streaming vs synchronous invocation, idempotency keys, and versioning strategy for breaking prompt or tool changes.

production-agent-systems ai-platform-engineering book

4. Plugin Ecosystems

Examines how to design a plugin/extension model for agents (tool manifests, capability declarations, sandboxed execution) so third-party or team-owned tools can be registered without a platform team code change.

production-agent-systems ai-platform-engineering book

5. Agent Registries

Covers building a central registry of agents and tools with ownership metadata, capability tags, and discovery APIs, mirroring a service catalog but for autonomous and semi-autonomous agents.

production-agent-systems ai-platform-engineering book

6. AI Gateways

Explains the AI gateway pattern - a single ingress for model routing, rate limiting, cost attribution, and prompt/response logging across multiple LLM providers - and how it differs from a traditional API gateway.

production-agent-systems ai-platform-engineering book

7. Multi-Model Infrastructure

Covers routing and fallback strategy across multiple foundation models (cost tier, latency tier, capability tier), including circuit breakers when a provider degrades and shadow-testing a model swap before cutover.

production-agent-systems ai-platform-engineering book

8. Deployment Strategies

Applies canary, blue-green, and shadow-deployment patterns specifically to agent releases, where a bad deploy can mean bad tool calls or unsafe actions rather than just bad HTTP responses.

production-agent-systems ai-platform-engineering book

9. Platform Operations

Covers the day-2 operating model for an AI platform - on-call ownership boundaries between platform and product teams, cost governance, and the SLOs that keep a shared agent platform reliable.

production-agent-systems ai-platform-engineering book