Blueprint · intermediate · 10 steps

Build a LangGraph Agent Team

Build a job application assistant where four AI agents collaborate via LangGraph — analyze postings, tailor resumes, write cover letters, and review everything.

← All blueprints
STEP 01Step 1: What We're BuildingA multi-agent job application assistant powered by LangGraph where four specialized AI agents collaborate — analyzing job postings, tailoring resumes, writing cover letters, and reviewing the final package.4 minSTEP 02Step 2: Project SetupCreate the Python project, install LangGraph and LangChain, configure your OpenAI API key, and scaffold the project directories.3 minSTEP 03Step 3: LangGraph FundamentalsLearn the four building blocks of every LangGraph application — State, Nodes, Edges, and Conditional Edges — by building a minimal graph before tackling the full agent system.4 minSTEP 04Step 4: The Job AnalyzerBuild the first agent node — the Job Analyzer — that takes a raw job posting and extracts structured requirements, skills, and company information.5 minSTEP 05Step 5: The Resume TailorBuild the Resume Tailor agent that rewrites a user's resume to match the specific job requirements, skills, and keywords identified by the Job Analyzer.4 minSTEP 06Step 6: The Cover Letter WriterBuild the Cover Letter Writer agent that drafts a targeted, compelling cover letter using the job analysis and original resume.4 minSTEP 07Step 7: The Application ReviewerBuild the Application Reviewer agent that checks the tailored resume and cover letter for quality, consistency, and completeness — then decides if revisions are needed.4 minSTEP 08Step 8: Wire the GraphConnect all four agents into a LangGraph workflow with parallel execution, conditional routing, and a revision loop — the complete pipeline.4 minSTEP 09Step 9: Run LocallyBuild the CLI entry point, run the complete pipeline on a real job posting, and inspect the output.4 minSTEP 10Step 10: What's NextExtend your agent team with different LLMs, human-in-the-loop, persistence, and a web interface — plus a comparison of multi-agent approaches.4 min