Hands-on Tutorial: Build an Observable Job Search Agent with LangGraph
dl_weekly · x · 2026-08-01
This article is Part 1 of The Observable Job Agent series, providing a step-by-step guide to building an AI job search assistant named Job Scout based on LangGraph.
Core Features & Highlights:
- After a user uploads a CV, the agent automatically finds real job openings, ranks them from 0 to 100 for fit, and honestly identifies skill gaps.
- The running cost is extremely low (under $0.50), and it supports free tiers from major model providers.
Technical Practices:
- Deep dive into what makes an agent versus a workflow (state, tools, and conditional loops).
- Integrates Opik for LLMOps observability, automatically generating span trees, cost statistics, and versioned prompts.
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