Days 1 and 2 combine live coding demos with guest speakers from leading AI companies (OpenAI, Cursor, Sourcegraph, Linear). Day 3 is a hands-on hackathon with real-time support to work on projects at work.

Students get access to a private Discord community with instructors and AI-forward engineers and LIFETIME ACCESS to all materials and recordings.

Do these questions sound familiar?

- How can I manage context windows effectively when building complex features?

- What’s the real difference between coding with AI and just using autocomplete?

- How do senior engineers actually use AI in production environments?

- How can I maintain quality with AI-generated code?

- How do I turn meeting notes into working code without losing context?

If you or your team aren’t getting the most out of AI in your development workflow, this course is for you. It’s a hands-on program built for software engineers who want to level up—without wasting hours chasing scattered tips online.

Day 1 — Fundamentals of AI Software Engineering

The day begins with Vignesh introducing a practical framework for building software with AI: Explore → Plan → Build.

Participants will learn how to turn raw meeting notes into working code without losing context, manage context windows effectively, and apply the workflow in real scenarios.

The day concludes with a live coding session where Vignesh builds a complete production feature, giving attendees a clear, practical path to using these tools.

Day 2 — Advanced Workflows & Guest Speakers

The focus shifts to advanced workflows, rules, and features—including the Model Context Protocol (MCP).

Guest talks will feature leaders from top AI coding companies, along with respected engineers sharing their unique workflows. Attendees will gain actionable insights they can adopt without needing to sift through hours of YouTube or X content.

The day ends with an integration workshop to bring these tools together into a cohesive workflow.

Day 3 — Hackathon & Implementation

The final day is dedicated to applied learning. Participants will work on real features from their production codebases—or side projects if preferred—using credits provided as part of the course.

Throughout the day, Jason and Vignesh will host office hours to pair on workflow tips and provide hands-on support. The hackathon wraps with project showcases, structured debriefs, and key takeaways attendees can immediately bring back to their teams.

By the end of this course, you'll be shipping features in hours that previously took days, with the confidence to incorporate new AI coding tools as they come out.

Trusted by Industry Leaders



Jason has taught over 570 professionals through his course Systematically Improving RAG Applications, earning a 4.8-star rating and recognition as one of Maven’s top AI instructors. His teaching is trusted by engineers and leaders from top companies and research institutions including Anthropic, OpenAI, Google, Netflix, and Stanford, where alumni are actively applying his frameworks in production today.

The results speak for themselves:

"I took Jason's RAG course in Cohort 3 and found it to be an information-dense, practically useful LLM course. It skips the hype and focuses on real tools and patterns you can apply. Jason’s cross-industry experience brings valuable perspective on how retrieval systems are being used in production to drive real outcomes. Solid course if you're looking to learn how to build a RAG system with a systems mindset - something that evolves over time rather than a one-off implementation." - Nishant, Staff Analytics Engineer, Netflix