The Agentic Control Loop
Master ReAct, Plan-and-Solve, and self-reflecting architectures. Part of the free AI Agents Academy — every lesson below is open to everyone, no signup required.
// LESSONS IN THIS MODULE
- 01ReAct: Reason + Act8 min · 60 XP
The ReAct Pattern ReAct (Reasoning + Acting) is the foundational pattern for modern AI agents. Instead of just answering a question, the model emits a...
- 02Plan-and-Solve8 min · 60 XP
Hierarchical Planning While ReAct is great for short tasks, it fails on long horizons because the agent loses track of the overarching goal. Enter Pla...
- 03Reflection & Self-Correction10 min · 70 XP
The Inner Critic Agents that act without checking their work make catastrophic mistakes. Adding a Reflection step improves reliability by 30-40%. A Se...
- 04State Machines & Graph Agents10 min · 70 XP
Modeling Agents as Graphs The most reliable production agents are not free-form loops - they are state machines modeled as directed graphs. This is th...
- 05Inner Monologue & Scratchpads9 min · 70 XP
Giving Agents a Private Thinking Space Humans don't jump straight to answers - we mutter to ourselves, scribble notes, and reason through problems. Th...