Architecting Enterprise AI Workflows
Master the agentic patterns (Routing, Tool Use, Orchestration) defining enterprise AI in late 2025.
Course Modules
The Shift to Agents
The era of "chatting with a bot" is ending. The future of enterprise AI isn't about better prompts—it's about agentic workflows.
The Core Shift
Zero-Shot (Old Way): You give an LLM a task, and it tries to solve it in one continuous stream of tokens. It can't backspace, it can't check its work, and if it hallucinates, it keeps going.
Agentic Loop (New Way): The system is designed to "think, act, observe." It breaks a task down, uses tools, checks the output, and iterates. It's software that can reason.
Why "Loops" Beat "Chains"
In 2023, we built "chains"—linear sequences of steps (A -> B -> C). If step B failed, the whole chain broke.
Today, we build "loops" (or agents). An agent is given a goal ("Update the CRM with this email info") and a set of tools. It decides which steps to take. If step B fails (e.g., the API times out), the agent sees the error and tries again or chooses a different path.
Linear Chain
Agentic Loop
Andrew Ng has famously stated that "agentic workflows" will drive more AI progress this year than the next generation of models. For enterprises, this means we can build reliable systems using cheaper, faster models (like GPT-4o-mini) simply by wrapping them in a smart loop.
verify your understanding
What is the fundamental difference between a 'Chain' and an 'Agentic Loop'?