A comprehensive learning initiative featuring curated resources, hands-on milestones, and live mentorship sessions to help you master AI engineering skills.
Follow our structured learning path to master AI engineering concepts and tools through hands-on practice and expert guidance.
Get hands-on experience with the most powerful AI-powered development tools available today.
Watch or read "An Opinionated Guide on the Best AI Coding Tools in 2025"
Learn about the current landscape of AI coding tools and their capabilities.
Build a prototype with Bolt
Read the blog post about Bolt.new and create your own prototype. Reply to the original post with your prototype link.
Create a full stack app with Replit
Watch the developer experience video and build your own full-stack application.
Install Cursor on your machine
Watch the tutorial and implement the Momentum Chrome extension following the blog post guide.
Install WindSurf Editor on your machine
Watch the demonstration video and implement the bike shop app on your local machine.
Wednesday, June 4, 2025 at 9:30 am PST
Bring your questions, discuss progress, and connect with peers.
Master the fundamentals of prompt engineering, retrieval-augmented generation, and evaluation methodologies.
Prompt Engineering
Read and/or watch the videos on "The Prompt Report Parts 1 and 2" from Oxen.ai and read OpenAI's guidelines for text generation and prompting.
Retrieval Augmented Generation (RAG)
Read LangChain's overview on RAG, implement their tutorial on building a search engine over a PDF document, and read Cameron Wolfe's practitioner's guide.
Evaluation
Read about RAG evaluation metrics and learn about RAGAS framework for automated evaluation of RAG systems.
Wednesday, July 16, 2025 at 9:30 am PST
Please reply below or DM me to get the Zoom link to the live AMA session. Bring your questions, discuss progress and connect with peers.
Learn the complete process of building modern chatbots like ChatGPT, from understanding transformer architecture to training with human feedback.
Overview
Watch Andrej Karpathy's video, "Deep Dive into LLMs like ChatGPT", which covers all the steps that go into making a modern chatbot like ChatGPT.
Understand the Transformer Network Architecture
Read Jay Alammar's "The Illustrated Transformer" blog post that visually explains the Transformer neural network architecture.
Pre-train to get a base model, Post-train via Supervised Fine Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) to get a chatbot aligned with human preferences
Read Sebastian Raschka's "LLM Training: RLHF and its Alternatives" blog post. Read and watch the video on Oxen.ai's "Training Language Models to Follow Instructions (InstructGPT)" blog post.
Wednesday, October 15, 2025 at 9:30 am PST
Please reply below to get the Zoom link to the live AMA session. Bring your questions, discuss progress and connect with peers.
Learn how to build autonomous AI agents that can use tools, plan, reflect, and collaborate with other agents.
Foundation — What Are Agents and Why Do They Matter?
Take Dr. Andrew Ng's "Agentic AI" short course on DeepLearning.AI. Learn agentic design patterns — reflection, tool use, planning, and multi-agent collaboration.
Building and Engineering Agents
Read Anthropic's "Building Effective Agents" guide and their follow-up article "Effective Context Engineering for AI Agents". Build AI agents and feed them the right context (prompts, memory, tool outputs, etc.).
Evaluating Agents
Read Anthropic's "Demystifying Evals for AI Agents". Build evaluation frameworks to measure and improve agent reliability.
Multi-Agent Systems in Practice
Read Anthropic's case study on building their multi-agent research system. Learn how multiple specialized agents can coordinate on a complex task.
Agent Protocols — Connecting Agents to Tools and Each Other
Read the intro to the Model Context Protocol (MCP) and take DeepLearning.AI's course on the Agent2Agent (A2A) protocol. MCP connects agents to tools; A2A connects agents to agents.
Wednesday, April 8, 2026 at 9:30 am PST
Please reply below to get the Zoom link to the live AMA session. Bring your questions, discuss progress and connect with peers.
Learn how to build the harness (prompts, tools, memory, and control logic) and the agentic loop that drives agents over long horizons.
Foundation: What Is a Harness and Why Long-Running Agents Need One
Read Anthropic's "Effective Harnesses for Long Running Agents" and its companion "Harness Design for Long Running Apps." They explain why agents that run for minutes or hours, not seconds, need deliberate engineering for context compaction, error recovery, and state management.
Harness Design in Practice
Read OpenAI's "Harness Engineering: Leveraging Codex in an Agent-First World" for a practical look at building harnesses around coding agents in a real agent-first workflow.
Agentic Loops: Reliable Workflows That Learn Over Time
Every agent runs on a loop: observe, decide, act, repeat. "How to Solve Problems of Autonomous Agentic AI Workflows" covers common failure modes (drift, runaway loops, lost context) and how to keep a loop on track. LangChain's "Continual Learning for AI Agents" shows how the best loops learn from each iteration and improve with every run.
Putting It Together: An Always-On Agent You Can Message
Study the "Hermes Agent Masterclass" (architecture similar to OpenClaw): the harness and loop working together as an always-on agent that lives on a server, runs continuously, and reaches you over Telegram or Slack. Send it a task from your phone, and it works on its own and messages you back.
Wednesday, July 1, 2026 at 9:30 am PST
Comment below for the Zoom link and bring your questions.
A structured learning initiative designed to bridge the gap between traditional software engineering and AI engineering through practical, hands-on experience.
Each milestone contains carefully selected resources including blog posts, videos, tutorials, and research papers to ensure comprehensive learning.
Build real projects and prototypes using cutting-edge AI tools like Bolt, Cursor, Replit, and more to gain practical experience.
Join live AMA sessions to discuss progress, ask questions, and connect with fellow engineers on the same learning journey.