VIBE CODING FULL COURSE: Gemini 3.1 + Antigravity (6 Hrs)

What Is Vibe Coding and Why It Matters

Vibe coding represents a modern paradigm shift in software development where AI models like Gemini 3.1 Pro become active co-developers rather than passive tools. This approach leverages large language models and AI agents to generate entire applications, manage complex workflows, and handle deployment with minimal manual intervention. The course from Nick Saraev demonstrates that vibe coding is not theoretical—it's a practical methodology for building real, revenue-generating applications in 2026. Unlike traditional programming, which requires deep language expertise, vibe coding allows developers of any skill level to conceptualize an idea and rapidly iterate toward a production-ready product using AI guidance and intelligent prompting.

Setting Up Your Vibe Coding Environment

The foundation of vibe coding begins with properly configuring Antigravity, a specialized interface designed to maximize AI productivity and agent coordination. During setup, learners navigate the core panels of Antigravity, including the agent chat interface where conversation with Gemini 3.1 Pro occurs, customizable workflow triggers, and the integration of MCP servers for extended functionality. The course walks through selecting appropriate AI models for specific tasks, understanding how conversation modes alter AI behavior, and implementing voice dictation features to speed up development cycles. Key configuration decisions at this stage—such as defining custom prompts and establishing clear communication patterns with the AI—significantly impact downstream development efficiency and code quality.

The Vibe Coding Design Loop and Architecture

A critical concept throughout the course is the vibe coding design loop, an iterative process where developers specify intent, receive AI-generated code and designs, review the output, provide feedback, and refine the result until production standards are met. The common vibe coding stack combines Gemini 3.1 Pro for logic generation, Antigravity for workflow orchestration, Next.js or Vite for frontend frameworks, and Supabase or similar services for backend infrastructure. This stack is deliberately chosen for ease of integration and minimal configuration overhead. Learners discover how to leverage agents and agent teams—coordinated AI workflows that handle discrete subtasks in parallel—to dramatically accelerate development. The design loop emphasizes rapid prototyping, continuous deployment feedback, and security-first thinking from the earliest stages.

Building Five Production-Ready Applications

The course structure includes hands-on construction of five complete applications, each introducing progressively complex concepts. The first project is a portfolio website deployed to Netlify, establishing foundational deployment practices and design iteration. The second is a full-stack client dashboard platform that introduces database architecture, authentication, and multi-user workflows. A lead generation application demonstrates API integration, external service coordination, and data capture patterns. A thumbnail generator showcases specialized AI use cases and real-time user feedback loops. The final application, codenamed Splinter, brings together advanced feature integration, pricing strategy implementation, and marketing considerations. Each project reinforces core software engineering principles: version control with GitHub, secure credential management, testing methodologies, and iterative debugging within an AI-driven workflow.

Essential Software Engineering Topics

Beyond coding mechanics, the course covers modern software engineering fundamentals necessary for production systems. Database concepts are explained through the lens of SQL versus NoSQL trade-offs, guiding learners to select appropriate persistence layers for their applications. The role of frameworks—Next.js, Vite, and others—is contextualized within the larger ecosystem of programming languages and their respective strengths. Version control and GitHub workflows receive practical treatment, showing how AI-generated code integrates with collaborative development practices. Security is treated as a primary concern, not an afterthought. The course includes dedicated security audit processes, explanation of authentication and authorization patterns, Stripe payment integration for monetization, and best practices for handling sensitive data in AI-assisted development.

Deployment, Monetization, and Scaling

A distinguishing feature of this course is its emphasis on going from prototype to revenue-generating product. Learners deploy projects to Netlify and other cloud platforms, integrate payment processing through Stripe, and understand the operational considerations of maintaining live applications. The course addresses how to think about pricing strategy, basic marketing approaches for vibe-coded products, and the debugging processes required when applications reach production. Hosting considerations, API wrapping techniques, and the debugging of payment systems receive practical, example-driven instruction. The underlying message is that vibe coding is not just faster development—it fundamentally changes the business model by reducing time-to-market and enabling solo developers to ship products at scale.

Why This Course Stands Apart

Nick Saraev brings credibility through demonstrated success: six years building automated businesses with Make.com, including 1SecondCopy, a content company that achieved seven-figure revenue. This background ensures the course focuses on systems that generate actual revenue, not toy projects. The 6-hour runtime balances depth with accessibility, covering enough detail to implement each concept while maintaining momentum. The curated stack of tools—Gemini 3.1 Pro, Antigravity, Next.js, Supabase, Apify—represents carefully selected choices for 2026 development practices. Rather than abstract theory, every concept is demonstrated through live building, debugging, and deployment. Learners gain not just knowledge of individual tools but understanding of how they orchestrate together to enable one person to build, ship, and scale production applications.

Ideal Audience and Prerequisite Knowledge

This course appeals to entrepreneurs seeking to build software without years of traditional programming education, existing developers who want to accelerate their workflow with AI, and automation specialists transitioning from platforms like Make.com. While the course assumes basic comfort with web concepts, no prior coding experience is strictly required—the AI handles implementation details while the human provides direction and judgment. The real skill being taught is effective communication with AI models, rapid iteration and feedback cycles, and understanding sufficient software engineering principles to avoid critical mistakes in production systems.