Description

Most AI courses teach you to use AI tools. This one teaches you to build AI agents that do engineering work autonomously — running in your CI pipelines, reacting to events, and fixing problems without waiting for you.This is a hands-on course for freshers-mid-to-senior software engineers ready to move from AI user to AI agent builder.You won’t be building toy demos. Every agent in this course solves a real problem: automated PR reviews, slow query detection, with human approval gates, and more. Each build introduces a distinct architectural pattern you can adapt to your own stack.What you’ll learnHow LLMs actually work: context windows, hallucinations, token limits, and why it matters when you’re building agents, not just chattingPrompt engineering that holds up in production agent contextsClaude Code: terminal-native agentic coding with filesystem ownership and MCP integrationGitHub Copilot: IDE-native and GitHub Actions agentic workflowsOpenAI Codex: async task delegation with PR-based outputGoogle Antigravity / Google Gemini: multimodal terminal input for Google ecosystem teamsMCP servers: extending your agents with custom tools and external integrationsn8n: event-driven orchestration that connects your agents to the rest of your workflowJetBrains AI: Run all AI tools inside IntelliJ IDEAWho this is forSoftware engineers or Freshers who want to build and deploy real AI agentsJava and Spring Boot developers integrating AI into existing backend systemsDevOps and cloud engineers looking to automate repetitive operational workAny developer tired of demos and ready to run agents in actual CI/CD pipelinesRequirementsComfortable with at least one backend language (Java or Spring Boot experience is a plus)No prior AI or machine learning experience needed