Accelerate your coding progress with our 3 Day AI Coding Accelerator. This course is designed to help engineers release production code 10 times faster by harnessing real AI workflows used by leading engineers in practice.

Course Overview

In this intensive program, you will observe and replicate the real software development process, using the tools and approaches we employ in our consulting work. As engineers first, we've integrated AI tools into feature development, reducing implementation time from weeks to days. Originally shared with senior engineers, these practices have been scaled into this course for hundreds of developers.

Master Key Workflows

Throughout the course, you will master two key classes of workflows:

Synchronous Workflows: Live coding with AI, managing state and context, and obtaining clean and correct code from models.
Asynchronous Workflows: Background tasks, automated agents, Slack triggers, and multi-step processes that operate in parallel with your ongoing work.

Complete Engineering Cycle

This course covers the entire engineering cycle, beyond just coding:

Generating design documents from meeting notes
Debugging with AI assistance
Code review and pull request workflows
Implementing custom commands, sub-agents, and rules

By course end, you'll possess a reproducible engineering system that can be applied across any codebase, stack, and development environment. You'll not only understand these approaches but also release a real production feature using learned methods.

The course is already trusted by over 200 developers, emphasizing its practical impact.

What You Will Learn

Automate entire stages of development and eliminate routine tasks with custom commands.
Connect existing tools via MCP servers for seamless work with tickets, APIs, and processes without constant context switching.
Develop an AI-first workflow, from planning to context loading, to prevent model errors at the infrastructure level.
Enhance efficiency from individual to team level by delegating tasks to autonomous agents and setting unified engineering standards.

Who This Course Is For

Developers seeking a clear, practical AI tool system amidst overwhelming options.
Team leads and technical leaders evaluating AI tools and needing strategies for informed decision-making.
Engineers tired of the hype, looking for honest, practice-proven AI experience.

About the Authors

Jason Liu

Jason Liu is an experienced AI engineer with over six years of experience developing search and recommendation systems in both academic and commercial environments. His portfolio includes developing computer vision models at the University of Waterloo, shaping content policy at Facebook, and building recommendation engines at Stitch Fix, which brought the company an additional $50 million in revenue. Over the past year, he has consulted for dozens of startups, helping take their RAG solutions from prototypes to systems ready for industrial deployment. Jason is also the author of the open-source Instructor Python library, designed for building advanced RAG workflows.

Vignesh Mohankumar

Vignesh is an independent consultant in the field of applied artificial intelligence. He helps companies bring AI solutions to production within 30 days and trains engineering teams in the efficient and practical use of AI in development.

Previously, Vignesh was one of the first engineers at Drift, an early startup in the conversational AI space, which was later acquired for $1.2 billion. He later led the growth engineering team as a staff engineer, responsible for scaling the product and engineering processes.

Lesson Title

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Day 1.1 Fundamentals Demo