Orchestration

Why It Matters

Real AI applications rarely involve a single LLM call. A customer support system might retrieve context, classify intent, route to the right handler, generate a response, and log the interaction. Orchestration is how you wire these pieces together reliably.

Without proper orchestration, you get spaghetti code, LLM calls scattered everywhere, state passed through global variables, errors that crash silently. With orchestration, you have clear flow control, centralized error handling, and observable pipelines you can debug and improve.

For AI engineers, orchestration skills separate production systems from prototypes. Frameworks like LangChain, LlamaIndex, and Semantic Kernel exist primarily to solve orchestration problems. Understanding when to use them (and when plain Python is better) is a critical architectural decision.

Implementation Basics

Orchestration patterns range from simple to complex:

1. Sequential Chains The simplest pattern: output of one LLM call becomes input to the next. Summarize a document, then translate the summary, then extract key points. Each step is predictable and debuggable.

2. Parallel Execution When steps are independent, run them concurrently. Generate three different response variants simultaneously, or call multiple APIs at once. Python’s asyncio or framework-specific parallel primitives handle this.

3. Conditional Routing Branch based on LLM output or intermediate results. Route customer requests to different specialized handlers. Use a classifier to decide which tool to invoke. This is where orchestration gets interesting, and complex.

4. State Management Complex workflows need to track state across steps. What documents were retrieved? What tools were called? What was the user’s original intent? Good orchestration provides clean state abstractions rather than ad-hoc dictionaries.

5. Error Handling LLM calls fail. APIs timeout. Outputs don’t parse. Orchestration layers need retry logic, fallback paths, and graceful degradation. This is often the most important (and most neglected) part of orchestration design.

Choose the simplest approach that works. Many “orchestration frameworks” add complexity without proportional benefit. A well-structured Python function with clear control flow often beats a framework-heavy solution.