Learn how to build agent systems that work in real production. This course guides you step by step. You will design, test, and ship real agents that you can add to your portfolio.
What You Will Learn
You will learn when to use an agent and when a simple workflow is enough. You will also learn how to build agents that run well in production, not only on your machine.
When an Agent Helps
- Know when to use an agent. Avoid the three common mistakes developers make when they pick an agent for a task.
- Fix local‑to‑prod issues. Build two full agents with deployment, logs, and clear pipelines.
- Break down complex tasks. Build a research agent and a content system with clear checks and tool use.
- Make good decisions. Choose between rules and agent freedom. Pick points where a human should review work. Create clean prototypes you can scale.
- Learn long‑lasting skills. Focus on system design, not trends. You will finish with two deployed agents and the core skills to build more.
What You Will Build
Research Agent
- Collect and shape data from the web, GitHub, and YouTube.
- Run research in clear cycles.
- Use tools for search, parsing, and analysis.
Content Workflow
- Create text, diagrams, and images.
- Run automated checks for quality.
- Keep style and context stable.
- Ship work through a clean pipeline.
Agent Architecture Skills
- Plan and run stable workflows.
- Build custom checks and monitors.
- Deploy with Docker and cloud tools.
- Work with Cursor, Claude, and other tools.
Course Outcome
- Two production agents in your portfolio.
- A clear view of design ideas that outlast frameworks.
Who This Course Is For
- Python users who know functions, classes, and APIs.
- People who know basic LLM use with OpenAI or Claude.
- People who know Docker and simple deployment ideas.
- Learners who like to build through practice, not long videos.
