Routing

We’ve explored how to break tasks down into sequential moves using prompt chaining, building structured outputs one clear step at a time. But what happens when a task doesn’t neatly fit into one chain of prompts? Real-world AI problems often resemble a bustling train station: inputs arrive rapidly, and each passenger (or input) needs to board a specific train to reach the right destination efficiently. Routing is how we ensure every input finds its perfect train.

Routing is about classification and delegation. Rather than forcing a single generalist prompt to handle every type of request, we first classify the input and then delegate it to a specialized subtask. By clearly separating concerns, each specialized prompt can become exceptionally good at its one job, without trying to juggle too many different tasks at once. This agentic pattern not only boosts accuracy but also prevents optimizing for one kind of input from hurting performance on another.

When should routing be used?

Imagine coaching a sports team composed of specialists. You wouldn’t expect your best shooter to play as a center; instead, you’d assign each task to the player most suited for it. Similarly, routing in AI directs each task to the best-equipped resource, providing three significant advantages:

• Accuracy: For example, a customer support bot can quickly handle straightforward queries like “What’s your return policy?” with a small, efficient model or a simple database check. Conversely, complex technical issues might be directed to a powerful AI model or a human expert. This targeted approach increases response speed and reduces operational costs.

• Scalability: Routing makes it easy to expand a system’s capabilities without overhauling the existing setup. Introducing new specialists, such as a “refund agent” or “account management tool,” can be seamless, enabling your system to manage an ever-growing range of tasks effortlessly.

• Reliability: In sensitive sectors like healthcare, intelligent routing is crucial. A question about drug dosage can be quickly directed to a reliable database, while a symptom like “unusual chest pain” is immediately escalated to a specialized diagnostic agent or a medical professional. This ensures effective risk and complexity management.

In this lesson, we’ll bring back our familiar weather-checking tool and our JSON-file-based knowledge retriever to show routing in action. You’ll see firsthand how the routing pattern makes our agentic system smarter and more efficient by smoothly directing each input to the right specialized agent. ...