Invite-only community
A community for action-oriented builders interested in AI engineering and AI tools. Get the structure, focus, and accountability you need to ship practical AI products.
Build
Practical AI projects
Ship
With structure & accountability
Grow
Through peer collaboration
Philosophy
Designed for motivated learners who prefer learning by doing. Get clear frameworks, direction, and community support to make consistent progress on your projects.
No passive consumption. Every activity is designed around building, shipping, and getting feedback on real work.
Focus on what actually works in production. Move from prototypes to reliable systems with battle-tested patterns.
Work alongside other practitioners. Hackathons, projects, and group problem-solving instead of isolated learning.
Develop better instincts through peer feedback, expert guidance, and exposure to real-world decision-making patterns.
Membership
Each tier is designed for a different type of builder. More investment means more structure, accountability, and support to help you ship your AI projects consistently.
Content only
Educational content without community access.
Access curated educational content, tutorials, and research. Perfect for self-directed builders who learn at their own pace.
Best for independent builders who prefer self-paced learning. Upgrade to Main for structure, accountability, and community support.
Choose BasicLive learning + community
Build with the community and get the accountability and direction you need to make progress.
Everything in Basic, plus the structure, accountability, and peer support to ship your AI projects consistently.
Best for builders who need structure and accountability to turn project ideas into reality alongside motivated peers.
Get StartedCourses + personalized feedback
Accelerate your growth with structured courses and personalized feedback.
Everything in Main, plus structured learning paths through mini-courses and personalized career guidance to accelerate your growth.
Best for builders seeking structured learning paths to complement hands-on projects, plus personalized career guidance.
Choose PremiumWhat learners say
AI Shipping Labs community is new, but here's what practitioners say about the courses that inspired it.
"This course helped me understand how to implement a RAG system in Python. From basic system-design of a RAG, to evaluating responses and implementing guardrails, the course gave me a great overview of the necessary skills for implementing and managing my own agent."
Rolando
AI Data Scientist · AeroMexico
"I highly recommend the AI Engineering Buildcamp. I learned a tremendous amount. The material is abundant, very well organized, and progresses in a logical and progressive manner. This made complex topics much easier to follow and digest. The instructor Alexey Grigorev is clearly very knowledgeable in the field, and also super helpful and responsive to questions."
John
AI Tutor · Meta
"Excellent, comprehensive, and modern course that elevated my knowledge of generative AI from RAG applications to well-evaluated, fully functioning agentic systems. Alexey Grigorev incorporated essential software engineering practices, especially unit testing and evaluation, teaching us how to systematically improve our agents."
Yan
Senior Data Scientist · Virtualitics
"I really enjoyed this course! It made the process of building AI agents both accessible and exciting. The progression from RAG to agents, multi-agent systems, monitoring, and guardrails was clear and practical. I'm walking away inspired and full of new ideas to build on."
Scott
Principal Data Scientist, Applied AI · interos.ai
"The course provides an excellent introduction to the core tooling needed to develop an agentic tool. Worth the effort especially given the comprehensiveness of the options and solutions available in the course."
Naveen
Software Engineer
"Excellent course, it gets you practicing the concepts you need to know to work on agentic AI. The instructor is accessible, clear, and flexible."
Nelson
Practitioner
Event Recordings
Workshop recordings with embedded content, timestamps, descriptions, and materials. Learn from hands-on sessions on building AI agents and practical systems.
Extend a basic coding agent into a general-purpose agent with modular skills and explicit commands. Learn how Claude Code-style skills and commands work internally.
Build safe AI agents with input and output guardrails. Learn how to prevent inappropriate responses, enforce policies, and maintain academic integrity.
Build a durable data ingestion pipeline, handle IP blocking with proxies, index transcripts into ElasticSearch, and design a multi-stage research agent with Temporal orchestration.
From the blog
Long-form notes, walkthroughs, and experiments. Stay close to how we build and reason.
See how CRISP-DM still guides AI engineers in 2026, translating each phase into practical workflows for LLM apps, RAG pipelines, and production AI systems.
An incident story: how I accidentally wiped our AWS RDS production database and deleted snapshots by letting Claude Code touch production infrastructure.
Learn what an AI engineer is in 2026: responsibilities, skills, tools, and real-world use cases based on analysis of 1,000+ AI engineer job descriptions.
Project Ideas
Project ideas and real projects from people who've taken courses. End-to-end AI applications and agentic workflows you can learn from and build on.
Carlos Pumar-Frohberg's agent analyzes client satisfaction using Stack Exchange data, focusing on UI discussions to find frustration patterns. An orchestrator agent routes questions to a MongoDB agent for 'what'/'how' queries or a Cipher agent that translates natural language into Neo4j graph queries, often calling both for safety.
A reference project from the AI Engineering Buildcamp: an agent that interacts with a simple to-do list application. Built with Lovable for the frontend and FastAPI (Python) for the backend. Uses the backend's OpenAPI spec so the model can create tools to get tasks or mark them complete, with Logfire for monitoring and pytest for testing.
A small, self-contained project idea: take a photo of an everyday object and turn it into a short story with AI. Expand gradually with illustration, audio, a small website, and a podcast feed. Great for experimenting with multimodal pipelines (vision, text, speech) and sharing with kids, family, or friends.
Curated Links
Curated GitHub repos, model hubs, and learning resources. Dev tools, local LLMs, and courses to level up.
AI copilot for data science. One prompt runs the full workflow: EDA, cleaning, feature engineering, model selection and fitting, evaluation, and feature importance—in about 5 minutes. Free to get started.
sphinx.ai
AI-powered app builder. Design in the browser, export to GitHub.
lovable.dev
AI-first code editor. Built on VS Code, with Copilot-style assistance.
cursor.com
Command-line coding agent. Scaffold and edit projects from natural language.
claude.com
Large language model course. From basics to RAG, agents, and fine-tuning.
GitHub
Curated list of ML resources. Frameworks, papers, and tools.
GitHub
FAQ