Building Full Stack Apps With Cursor

Mike covers building full stack applications using Cursor, including topics like model selection, using MCPs, grounding context, planning, and the importance of rules and memories.

Cursor is a tool used for building and automating full stack applications. It helps with model selection, planning prompts, grounding context, and managing rules and memories to reduce hallucinations and improve functionality.

Cursor automates the development process, provides tools for model selection, helps in grounding context, supports using MCPs, and offers features like auto-run mode and indexing to improve efficiency and reduce hallucinations.

Model selection in Cursor is important because it affects the performance and efficiency of the application. Different models like OpenAI's 4.1, Cloud 4, and Gemini offer various benefits like speed and accuracy, and selecting the right model can optimize development.

Cursor can index entire documentation websites, create a rag for prompts, and build a custom index of project files to provide relevant information, helping reduce hallucinations and improve the accuracy of the AI's responses.

Key features of Cursor highlighted by Mike include model selection, creating and using MCPs, grounding context, planning prompts, managing rules, and using memories for continuous learning and improvement.

In his example project, Mike uses tools and technologies like Next.js, TypeScript, Tailwind CSS, Prisma, Postgres, and PNPM for building a consultancy webpage with a lead generation form.

Mike Mikula learns new technologies by deep diving into tools like Cursor, spending thousands of hours understanding its functionalities, and transitioning from traditional programming to using AI-assisted development methods.

Mike Mikula is a software engineer with 13 years of experience, primarily in the Salesforce domain, and has been working with AI and Cursor for the last two years.

Mike ensures quality by conducting thorough planning, using checklists, cross-referencing with multiple models, correcting hallucinations, and continuously monitoring and guiding the AI to follow best practices and standards.