Part 18
Completed

Agent Loops and Tool Use

Implemented autonomous agent systems with ReAct, Reflexion, and Plan-and-Solve patterns. Built tool use capabilities: calculator, search, code execution, and API calling. Evaluated on multi-step reasoning, web navigation, and complex task decomposition.

What I Built

Implemented autonomous agent systems with ReAct, Reflexion, and Plan-and-Solve patterns. Built tool use capabilities: calculator, search, code execution, and API calling. Evaluated on multi-step reasoning, web navigation, and complex task decomposition.

Key Concepts

ReActReflexionPlan-and-SolveTool UseFunction CallingAgent LoopsTask Decomposition

Architecture

1
Agent Controller
2
ReAct Loop
3
Reflexion Monitor
4
Tool Registry
5
Function Caller
6
Plan Executor
7
Memory Manager

Results

ReAct agents solve 78% of multi-step tasks vs. 45% for direct prompting. Tool use reduces hallucination by 60% on factual queries. Reflexion improves success rate by 15%.

Key Learnings

  • Agent loops (thought-action-observation) are surprisingly effective
  • Tool use dramatically reduces hallucination for factual tasks
  • Reflexion (self-correction) adds significant robustness

Challenges

  • Preventing infinite loops in agent execution
  • Designing robust tool error handling
  • Balancing agent autonomy with safety constraints