Ai Engineer 2026

Ai-Engineer
Published 8/2026
Created by Cleuton Sampaio
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 76 Lectures ( 11h 57m ) | Size: 13.6 GB
Generate, review, and build production-ready software using advanced AI APIs, RAG, and Multi-Agent systems.
What you'll learn
Implement AI-enabled engineering workflows to accelerate system architecture, automate code generation, and optimize complex software delivery pipelines.
Integrate state-of-the-art LLM APIs into existing applications to add advanced semantic search, automated reasoning, and intelligent data processing.
Architect multi-agent engineering solutions that collaborate to solve real-world development problems, perform technical audits, and enforce best practices.
Master AI-driven engineering tools to streamline code analysis, identify architectural bottlenecks, and accelerate system refactoring tasks safely.
Requirements
Experience in software development, solid understanding of programming logic, basic architecture concepts, and familiarity with APIs and command-line tools.
Description
This course contains the use of artificial intelligence.
Note: This version of the course uses Node.js / Typescript / React.
Transform your development workflow and master the next frontier of software engineering. This practical, hands-on course bridges the gap between traditional software development and AI-enabled engineering. Using a modern stack of Node.js, TypeScript, and React, you will move past basic prompting to build production-ready AI utilities, cognitive architectures, and autonomous workflows.
Throughout the course, you will engineer a complete portfolio of real-world applications from scratch
Foundations & API Mechanics: Master raw fetch requests, official SDKs, token counting, and prompt caching to maximize performance while minimizing API costs.
AI-Powered Programming Utilities: Build CLI tools and server-side APIs that perform autonomous code generation, automated code reviews, intelligent refactoring, and security scanning directly inside your CI/CD pipelines.
Advanced Tool Use & RAG: Implement function calling using JSON schemas to connect LLMs to web search, filesystems, and databases. Build a complete Retrieval-Augmented Generation system with semantic search using pgvector.
Agents & Multi-Agent Systems: Progress from basic chatbots to autonomous ReAct agents. Orchestrate a collaborative multi-agent development team featuring specialized Architect, Developer, QA, and Writer agents working in parallel to deliver full features autonomously.
Learn also about Spec-driven Development (SDD) and how to integrate it into your development workflow!
By the end, you will architect robust, cost-controlled AI systems, and master the AI-based workflow.
Who this course is for
Software developers, Software architects, Software Engineers, Data Engineers, QA professionals
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