Build a Production-Grade AI Support Agent for ShopStream (Python)
Topics covered
AI Agents Observability: Metrics, Logs & Tracing Resilience: Circuit Breakers & Retries
This course includes
- 7 lessons across 3 modules
- Hands-on coding exercises
- Downloadable resources & code
- Full GitHub repository access
- Certificate of completion
- 12 months of access
Why This Course?
Most AI agent tutorials end at "prompt engineering," ignoring the reality that agents are just distributed state machines prone to hallucination, tool-looping, and cost-runaway. In production, an agent isn't a chatbot; it is a remote procedure call (RPC) system where the "remote" is a non-deterministic black box. You will learn to treat LLM calls like unreliable network requests, implementing the same patterns—retries, circuit breaking, and schema validation—that we use to keep distributed systems alive. You will leave with a hardened, observable agent that interacts safely with ShopStream’s core databases.
What You'll Build
You will build supportdesk, a stateful AI support agent for the ShopStream ecosystem. The system evolves from a simple intent-parser into a tool-calling agent capable of querying SQLite databases and executing transactional logic like refunds. By Day 7, your agent will include a telemetry layer for cost/latency tracking, a "circuit breaker" for tool execution, and an evaluation harness that catches regressions in intent classification. It will be capable of handling complex multi-turn flows while maintaining strict adherence to ShopStream's business logic.
Who Should Take This Course?
Engineers: Learn how to wrap non-deterministic logic in deterministic software patterns (idempotency, circuit breaking).
Architects: Learn the cost/latency trade-offs of using LLMs as control-plane components.
SREs: Learn how to instrument and monitor "intelligence" as if it were a standard service.
PMs: Understand the technical limits of "agentic" systems to set realistic expectations for feature delivery.
What Makes This Course Different?
This course rejects the "magic" of framework abstraction. You will write your own tool-calling logic and state machine from scratch in Python, using only the standard library. Every day ends with a "Chaos Check" or a "Regression Test" ensuring your code does exactly what you expect. You aren't building a demo; you are building a system that treats LLM outputs as untrusted input, subjecting them to the same validation rigors as a public-facing API.
What's Included
Repository
Run it on your machine (Linux, macOS or WSL; needs Python 3.10+ and Redis):
git clone https://github.com/sysdr/shopstream-ai-support-agent.git
cd shopstream-ai-support-agent
bash test_all.sh # runs all lessons, or: cd lessons/lesson-1 && bash start.shIn the sandbox, run: cd lessons/lesson-1 && bash start.sh
Prerequisites
Comfort with Python (loops, functions, classes). No prior ML or AI experience is required. You do not need an API key; all lessons function with the built-in deterministic offline engine.