CF

3 Day AI Coding Accelerator

15h 31m 6s
English
Paid

3 Day AI Coding Accelerator is a 6-lesson 15 hours 31 minutes self-paced course by Jason Liu, Vignesh Mohankumar. Accelerate your coding progress with our 3 Day AI Coding Accelerator .

Course facts

Lessons
6
Duration
15 hours 31 minutes
Level
All levels
Language
English
Updated
Instructor
Jason Liu, Vignesh Mohankumar
Price
Premium

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.

Who teaches 3 Day AI Coding Accelerator?

Jason Liu

Jason Liu thumbnail

Jason Liu is a US ML engineer and the creator of Instructor (the most-used Python library for getting structured outputs from LLMs) and a long-running independent voice on the production-engineering side of LLM applications. He consults with companies on RAG implementations and is widely cited for the rigour of his approach to systematic RAG improvement.

His CourseFlix listing carries three Jason Liu courses: Systematically Improving RAG Applications, the accompanying Bonus Content module, and 3 Day AI Coding Accelerator. The RAG material is unusual for the depth it goes into the eval and feedback-loop side of production RAG systems — the parts of RAG work that separate a working RAG pipeline from one that hallucinates.

Material is paid and aimed at engineers running RAG in production who want to make the system measurably better rather than relying on prompt-engineering by intuition. For broader content, see CourseFlix's RAG category page.

Vignesh Mohankumar

Vignesh Mohankumar thumbnail

Vignesh Mohankumar is a software engineer and educator focused on the AI-coding workflow as a deliberate productivity discipline — particularly the short-format intensives that get experienced engineers comfortable with AI-coding tools quickly.

His CourseFlix listing carries the 3 Day AI Coding Accelerator — a focused intensive on integrating AI-coding tools (Cursor, Claude Code, Aider) into a real engineering workflow.

Material is paid and aimed at developers ready to make AI-coding tools a deliberate part of their workflow rather than a side experiment. For broader content, see CourseFlix's AI-Assisted Coding category page.

What lessons are included in 3 Day AI Coding Accelerator?

This is a demo lesson (10:00 remaining)

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#1: Day 1.1 Fundamentals
All Course Lessons (6)
#Lesson TitleDurationAccess
1
Day 1.1 Fundamentals Demo
01:55:55
2
Day 1.2 Sync 101
02:35:00
3
Day 2.1 Sync 101
02:34:18
4
Day 2.2 Async 102
02:26:44
5
Day 3.1 Optional: Hackathon Session 1
03:00:22
6
Day 3.2 Optional: Hackathon Session 2
02:58:47
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Books

Read Book 3 Day AI Coding Accelerator

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1AI Coding Accelerator PDF
2coding-async-101 PDF
3coding-sync-102 PDF

What courses are similar to 3 Day AI Coding Accelerator?

Frequently asked questions

What prerequisites are needed before enrolling in this course?
The course is aimed at engineers who want to accelerate their coding process with AI. While specific prerequisites are not mentioned, a background in software development and familiarity with coding practices will be beneficial. The course involves replicating real software development processes, which suggests that prior experience in coding and understanding engineering cycles is important.
What will I be able to build by the end of the course?
By the end of the course, you'll have developed a reproducible engineering system applicable across any codebase, stack, and development environment. The course covers generating design documents, debugging with AI, and implementing custom commands. You will also complete a real production feature during the course, enhancing your ability to integrate AI tools into your development workflow.
Who is the target audience for this course?
This course is designed for engineers looking to significantly reduce their coding and implementation time using AI workflows. It is particularly beneficial for those who are already familiar with software development processes and want to learn how to integrate AI into feature development to release production code more efficiently.
How does this course compare in depth and scope to other AI coding courses?
Unlike many courses that focus solely on AI theory or isolated coding exercises, this course offers a comprehensive view of the engineering cycle. It includes synchronous and asynchronous workflows, debugging, code review processes, and practical applications such as generating design documents and implementing custom commands, providing a holistic approach to AI-assisted development.
What specific AI tools or platforms are covered in the course?
The course teaches integrating AI tools into the development process, focusing on synchronous and asynchronous workflows. Synchronous workflows involve live coding with AI, while asynchronous workflows cover automated agents and Slack triggers. Specific AI tools are not named, but the focus is on real AI workflows used by leading engineers in practice.
What topics are explicitly not covered in this course?
The course does not delve into the theoretical aspects of AI or machine learning algorithms. Instead, it focuses on practical applications of AI in the software development process, specifically covering workflows, debugging, and code review practices. If you're looking for foundational AI or machine learning theory, this course may not meet those needs.
How much time should I expect to commit to this course?
The course is structured over three days, with intensive sessions designed to replicate real software development processes. While the exact runtime for each lesson is not specified, you should be prepared for a full-time commitment over these three days to fully engage with the material and complete the optional hackathon sessions if desired.