Alexey Grigorev – AI Engineering Buildcamp: From RAG to Agents
AI Engineering Buildcamp: From RAG to Agents by Alexey Grigorev is a comprehensive hands-on AI engineering program designed for developers, software engineers, data scientists, and technical professionals who want to build real-world AI applications using modern large language model (LLM) technologies.
Rather than focusing solely on theory, this buildcamp emphasizes practical implementation through real projects. Students learn how to design, build, evaluate, deploy, and monitor production-ready AI systems using Retrieval-Augmented Generation (RAG), AI agents, tool calling, workflow automation, and modern AI engineering frameworks.
By the end of the program, participants will have developed multiple portfolio-worthy AI applications and gained the skills needed to build intelligent systems that retrieve information, reason through complex tasks, and take actions autonomously.
What’s Included
Inside AI Engineering Buildcamp – From RAG to Agents, you’ll get access to:
- 8+ Hands-On AI Engineering Projects
- Step-by-Step Implementation Workshops
- RAG System Development Training
- Agent-Based AI Architecture Frameworks
- Live Sessions and Recordings
- Community Collaboration & Support
- AI Evaluation Methodologies
- Production Monitoring Systems
- AI Safety & Guardrails Training
- Portfolio Development Projects
- Capstone Project
- Modern AI Tools & Frameworks
- Real-World Use Cases and Deployments
Course Curriculum
Module 1 – LLMs & RAG Foundations
Build a strong foundation in modern AI application development.
Topics include:
- Large Language Models (LLMs)
- Prompt engineering fundamentals
- Retrieval-Augmented Generation (RAG)
- Knowledge retrieval systems
- Context management
- Structured AI outputs
- API integrations
You’ll learn how to build intelligent applications capable of retrieving and utilizing real-world information effectively.
Module 2 – Agentic Systems & Tool Calling
Move beyond simple chatbots and create AI systems capable of taking actions.
Covered topics:
- AI agents
- Function calling
- Tool integration
- Agent workflows
- Multi-step reasoning
- Agent orchestration
- Task automation
Frameworks include:
- PydanticAI
- Agents SDK
- Modern agent architectures
Module 3 – Testing & Evaluation
Learn how professional AI teams evaluate model quality and reliability.
Topics include:
- AI performance measurement
- Prompt evaluation
- Output scoring
- Automated testing
- Benchmarking systems
- LLM-as-a-Judge frameworks
- Continuous improvement methodologies
Module 4 – Monitoring & Guardrails
Build AI systems that are safe, observable, and production-ready.
You’ll learn:
- Logging systems
- Performance monitoring
- Cost tracking
- AI observability
- Debugging workflows
- Reliability engineering
- Safety guardrails
- Hallucination mitigation
Module 5 – Real-World AI Applications
Apply your knowledge to practical business use cases.
Projects include:
FAQ Assistants
Build intelligent customer support systems capable of retrieving accurate information from knowledge bases.
Research Agents
Create AI systems capable of collecting, organizing, and summarizing information from multiple sources.
AI Coding Assistants
Develop programming assistants that can analyze code, suggest improvements, and automate development workflows.
Documentation Systems
Generate intelligent documentation retrieval and management platforms.
Multi-Agent Workflows
Build advanced systems where multiple agents collaborate to solve complex tasks.
Capstone Project & Hackathon
The buildcamp culminates in a complete end-to-end AI engineering project.
Students will:
- Design a production-ready AI application
- Work with real-world datasets
- Build scalable architectures
- Implement deployment workflows
- Receive project feedback
- Create portfolio-ready systems
The capstone serves as practical proof of your AI engineering skills and can be showcased to employers or clients.
What You’ll Learn
By completing AI Engineering Buildcamp – From RAG to Agents, you’ll learn how to:
- Build production-ready AI applications
- Create Retrieval-Augmented Generation systems
- Develop AI agents with tool-calling capabilities
- Design multi-agent workflows
- Evaluate AI performance professionally
- Monitor and optimize AI systems
- Implement AI safety mechanisms
- Build scalable AI architectures
- Deploy real-world AI products
- Create portfolio-quality AI projects
Why This Course Stands Out
Many AI courses focus on prompts and simple chatbot examples.
This buildcamp focuses on:
- Real AI engineering
- Production-level workflows
- Practical implementation
- Portfolio development
- Agent-based architectures
- Modern AI frameworks
- End-to-end system design
Students learn how to move from prototypes to deployable AI products used in real business environments.
Who This Course Is For
This program is ideal for:
- Software Engineers
- AI Engineers
- Machine Learning Engineers
- Data Scientists
- Backend Developers
- Full-Stack Developers
- Technical Founders
- AI Product Builders
- Developers Transitioning Into AI
- Professionals Building AI Applications
Prerequisites
To get the most from the course, students should have:
- Basic Python knowledge
- Familiarity with Git
- Programming experience
- Basic API understanding
- Access to AI APIs (OpenAI or alternatives)
Previous machine learning experience is helpful but not required.
About Alexey Grigorev
Alexey Grigorev is widely recognized for his practical approach to AI education and engineering. He specializes in teaching developers how to build scalable AI applications using modern tools, production-ready architectures, and hands-on project-based learning.
His training emphasizes implementation over theory, helping students develop real-world AI engineering skills that can be applied immediately in professional environments.
Why You’ll Love AI Engineering Buildcamp
- Build real AI products
- Learn modern RAG architectures
- Create advanced AI agents
- Develop production-ready systems
- Master AI evaluation techniques
- Build portfolio projects
- Learn industry-standard workflows
- Understand deployment and monitoring
- Gain practical AI engineering experience
- Stay current with modern AI tools
Final Thoughts
AI Engineering Buildcamp – From RAG to Agents by Alexey Grigorev is one of the most practical AI engineering programs available for developers who want to move beyond basic prompts and build real-world AI systems.
Through hands-on projects, production-focused training, agent frameworks, RAG architectures, evaluation systems, and deployment workflows, students gain the skills needed to design, build, and maintain modern AI applications at scale.
If you want to become an AI engineer capable of building intelligent applications that retrieve information, reason through tasks, and take actions autonomously, this buildcamp provides a complete roadmap from foundations to production-ready AI systems.
Get Alexey Grigorev – AI Engineering Buildcamp: From RAG to Agents today.
