The original title is "Inside An AI Agent: Planning, Tool Use, Memory, Constraints, And Verification"

Short summary

Production agents aren't magic — they're software workflows where LLMs pick the next step and call tools. Success depends on five core pillars: planning (thinking before acting), tool use (safe orchestration), memory (state tracking), constraints (budget and iteration limits), and verification (output checking). The post breaks down each pillar with TypeScript/Python examples and compares plan-then-execute vs. ReAct approaches.

• •Agents are workflows around planning, tool use, memory, constraints, and verification — not magic
• •Plan-then-execute vs. ReAct represent different tradeoffs between cost/latency and adaptability
• •Production agents need auditable plans, constraint guards, and output verification before shipping

Generated with AI, which can make mistakes.