Learn 9router from the basics to production-grade: pre-requisites & environment setup, history & background, core concepts & main architecture, architecture overview, routing engine, model selector, policy engine, observability layer, credentials management, OpenAI provider, Azure OpenAI provider, Anthropic provider, custom providers, fallback strategies, rate limiting, load balancing, middleware, caching, authentication & API keys, performance tuning, deployment options, monitoring & alerting, modern features & roadmap, and the alternative ecosystem & final reflection, with a total of 23 episodes.
Before touching your first configuration, you need to prepare the foundational skills of AI routing, HTTP/REST, JSON/YAML, and observability, while making sure tools like Node.js, Git, Docker, and your LLM provider credentials are ready in your environment.

This episode traces the evolution of gateways from simple load balancers to AI routing gateways, compares traditional API gateways with service mesh, and explores real-world use cases such as prompt routing, multi-model orchestration, and policy-based model selection.

This episode dissects 9router's internal architecture: the route engine, model selector, policy engine, and observability layer, then traces the complete flow of intent extraction, the routing decision pipeline, and tool invocation, as well as the gateway's position between clients, LLM providers, and downstream tools.

This episode guides you through setting up a 9router workspace, configuring the first route rules and model endpoints, running a local server, then verifying that request and response routing works as expected with a real example.

This episode discusses how 9router decides a route: routing based on intent, task type, user identity, and metadata; the basics of rule matching with keyword, semantic classification, and fallback; as well as route priority and route chaining with real configuration examples.

This episode discusses choosing the target model based on performance, cost, and accuracy, building a multi-model stack for conversational, embeddings, code, and vision, and integrating external tools and API services into the agentic routing flow.

Applying policy-driven routing in 9router: the policy engine for compliance, privacy, and access control, rate limiting and quota enforcement, request filtering, up to safe fallback routes and safe handling of blocked intents.

Building observability for an AI routing gateway: latency metrics, request volume, and success rate; logging request context along with route decisions and provider diagnostics; and end-to-end tracing of AI request flows from client to provider.

Mastering advanced routing patterns in 9router: traffic splitting between models or tool pipelines, canary routes, shadowing, and A/B testing on route policies, as well as dynamic routing based on runtime signals such as cost, latency, and load.

Applying multi-tenant routing in 9router: tenant-aware route rules, per-customer model preferences, isolation of sensitive workloads, SLAs that differ between customers, as well as custom routing based on user profiles and domains.
