AI Engineering in Practice8 min read
Docker Compose for the full AI agent stack
How to run your entire agent stack locally with Docker Compose. Postgres, Redis, the agent service, Langfuse, and the network rules that just work.
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136 posts in total
AI Engineering in Practice8 min read
Docker secrets management for agentic AI services
How to inject API keys and secrets into agent containers without baking them into the image. BuildKit secrets, runtime injection, and the 3 bad patterns.
AI Engineering in Practice8 min read
Docker build errors: troubleshooting AI service Dockerfiles
How to fix the 5 common Docker build errors in AI service Dockerfiles. apt-get failures, wheel builds, layer cache misses, and the silent bugs.
AI Engineering in Practice7 min read
FastAPI CORS for production agentic APIs
How to configure CORS for a production agentic API without wildcard origins. The allowlist, the credentials flag, and the preflight that breaks SSE.
AI Engineering in Practice8 min read
FastAPI lifespan for agentic services: startup and shutdown
Why FastAPI lifespan is the only right place for agent startup code. Per-worker initialization, ordered teardown, and the bugs it kills.
AI Engineering in Practice9 min read
Async context management in Python AI services
How async context managers prevent connection leaks in Python AI services. The lifespan, contextvars, and middleware patterns that survive load.
AI Engineering in Practice8 min read
FastAPI + LangGraph: production chatbot API pattern
How to wire LangGraph into a FastAPI chatbot API with streaming, persistence, and per-user threads. The production pattern that scales past demos.
AI Engineering in Practice9 min read
FastAPI dependency injection for agentic API auth
How FastAPI Depends makes agent auth testable and composable. The pattern, the chain, and why module-level globals break at scale.
AI Engineering in Practice9 min read
Postgres state persistence for agentic systems
How to persist agent state in Postgres so conversations survive restarts. The schema, the session writer, and the idempotency rule that prevents loss.
AI Engineering in Practice9 min read
Service layer for AI agents: decoupling logic from routes
How a service layer in an AI agent codebase decouples business logic from HTTP routes. The pattern, the tests, and the refactor from a fat route.
AI Engineering in Practice9 min read
Dockerizing AI systems: a layered image approach
How to Dockerize a production AI service with multi-stage builds, layer caching, and a 150 MB runtime image. The pattern that survives real deploys.
AI Engineering in Practice9 min read
Production env variable parsing in Python AI services
How to parse environment variables in Python AI services without os.environ.get footguns. Pydantic Settings, type coercion, and the validation layer.
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Built by Param Harrison
Cofounder of AEOsome.com and Chief Mentor at learnwithparam.com with 14+ years building production systems. I've trained 50+ engineers on AI engineering - these programs distill what actually works into structured paths you can follow at your own pace.
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