What’s Next?
Explore the next steps in agentic development: real-world trade-offs, production pitfalls, and continuous learning.
We'll cover the following...
You’ve learned how to design AI using agentic patterns, like simple chains or complex orchestrators. Think of these as your AI blueprints. But in the real world, these blueprints often blend:
Patterns aren’t always separate: In practice, AI systems are complex, like a mosaic. It’s tough to draw clear lines between patterns.
For instance, when an AI decides to run tests or analyze code, is it just routing a task, or is the orchestrator choosing the right tool?
When a research AI discards a bad source, is it a simple ReAct loop (observe, act, reflect), or a mini evaluator-optimizer cycle? Often, it’s both!
One part of your AI can use ideas from many patterns at once. This isn’t a problem; it shows your system is mature. The patterns simply give us a common language to handle this complexity.
Build the right system, not just the smartest: ...