Build a Multi-Agent AI System in Python (Agents That Collaborate) | AI Engineering Project

Project: Multi-Agent AI System Idea: Multiple AI agents solving a task together. Example Workflow: 1️⃣ Research Agent collects information 2️⃣ Analyst Agent analyzes data 3️⃣ Writer Agent prepares final report Example Code: from openai import OpenAI client = OpenAI() research_prompt = "You are a research agent. Find trends in AI adoption." analysis_prompt = "You are a data analyst. Explain the impact of these trends." writer_prompt = "You are a technical writer. Summarize this clearly." research = client.chat.completions.create( model="gpt-4.1-mini", messages=[{"role":"user","content":research_prompt}] ) analysis = client.chat.completions.create( model="gpt-4.1-mini", messages=[{"role":"user","content":analysis_prompt + research.choices[0].message.content}] ) report = client.chat.completions.create( model="gpt-4.1-mini", messages=[{"role":"user","content":writer_prompt + analysis.choices[0].message.content}] ) print(report.choices[0].message.content) Multiple agents → Better problem solving. This project demonstrates how to build a Multi-Agent AI System, where multiple specialized AI agents collaborate to complete complex tasks. Instead of one AI doing everything, we divide the work between agents. Each agent has a specific role. Example roles: Research Agent Data Analyst Agent Planner Agent Writer Agent Reviewer Agent This architecture mimics real teams inside companies. Multi-agent systems are one of the most important developments in modern AI. They are used in: Autonomous AI systems Research assistants AI development copilots Business automation platforms AI workflow orchestration Enterprise AI tools Major frameworks built around this concept include: CrewAI LangGraph AutoGen LangChain Agents Understanding multi-agent systems is becoming a key skill for AI engineers. 🧰 TOOLS & TECHNOLOGIES USED Programming Python 3.10+ AI OpenAI API Large Language Models Concepts AI Agents Multi-Agent Systems Ag