Introduction: Tool use transforms LLMs from text generators into capable agents that can search the web, query databases, execute code, and interact with APIs. But implementing tool use well is tricky—models hallucinate tool calls, pass invalid arguments, and struggle with multi-step tool chains. The difference between a demo and production system lies in robust tool […]
Read more →Tag: AI Agents
Multi-Agent Coordination: Building Systems Where AI Agents Collaborate
Introduction: Single agents hit limits—they can’t be experts at everything, they struggle with complex multi-step tasks, and they lack the ability to parallelize work. Multi-agent systems solve these problems by coordinating multiple specialized agents, each with distinct capabilities and roles. This guide covers practical multi-agent patterns: orchestrator agents that delegate and coordinate, specialist agents with […]
Read more →Agentic Workflow Patterns: Building Autonomous AI Systems That Plan, Act, and Learn
Introduction: Agentic workflows represent a paradigm shift from simple prompt-response patterns to autonomous, goal-directed AI systems. Unlike traditional LLM applications where the model responds once and stops, agentic systems can plan multi-step solutions, execute actions, observe results, and iterate until the goal is achieved. This guide covers the core patterns that make agentic systems work: […]
Read more →Building AI Agents: A Complete Code Review Assistant from Scratch
Hands-on tutorial building a production-ready AI agent. Create a code review assistant with tool use, error handling, caching, and GitHub integration.
Read more →Agentic AI Explained: Building Autonomous Systems That Plan, Act, and Learn
Move beyond simple chat to autonomous AI agents. Understand ReAct, multi-agent architectures, memory systems, and what actually works in production today.
Read more →Building Multi-Agent Workflows: Advanced LangGraph Patterns
Building multi-agent workflows requires careful orchestration. After building 18+ multi-agent systems with LangGraph, I’ve learned what works. Here’s the complete guide to advanced LangGraph patterns for multi-agent workflows. Figure 1: Multi-Agent Architecture with LangGraph Why Multi-Agent Workflows Multi-agent systems offer significant advantages: Specialization: Each agent handles specific tasks Parallelism: Agents can work simultaneously Scalability: Add […]
Read more →