CF

faster. | Learn AI-Assisted Development

0h 0m 0s
English
Paid

faster.dev is a hands-on course that shows you how to use AI in real development work. You learn how to speed up tasks while keeping clean design, clear code, and long-term stability. The goal is to help you ship features fast without turning your codebase into a mess.

What You Learn

You focus on simple, repeatable steps instead of one-off demos. You build a workflow you can trust. You set rules, pick tools, and use AI to support each part of your project.

Course Content

Video Lessons

You start with core ideas and move toward advanced ways to work with AI assistants. Each lesson shows you how to apply the idea in your own code.

Project Logs

You look at real products with real users. You see how choices made during development shape the final system.

Ready Tools

  • slash commands for common tasks
  • init scripts for new projects
  • skills and rules you can add to your workflow

Main Topics

  • setting up AI assistants from scratch
  • creating guardrails for stable and safe code output
  • auditing a codebase and spotting design issues
  • building command chains and simple automation
  • using context and clear prompts
  • connecting AI tools to databases, APIs, and services

Why This Helps

faster.dev shifts you from random AI use to a steady engineering practice. You speed up your work, keep quality steady, and stay in control of your codebase as it grows.

About the Author: Aaron Francis

Aaron Francis thumbnail

Aaron Francis is a Texas-based developer and educator who runs Try Hard Studios and is best known in the PHP / Laravel community for his deep production-database content. His videos and courses focus on the parts of working software that don't get attention from the framework documentation: SQL performance, database internals, and the realities of running databases at scale.

His CourseFlix listing reflects that focus — three database courses (High Performance SQLite, Mastering Postgres, MySQL for Developers) plus two on screencasting craft (Screencasting.com and Screenflow for Screencasters) covering the workflow he uses to produce the database material itself. The database courses are unusually rigorous for the YouTube-tutorial market: each one runs many hours and treats the database as a first-class object of study, not a black box behind an ORM.

Related courses

  • AI Voice Agents with AWS thumbnailNew

    AI Voice Agents with AWS

    By: Zero To Mastery
    Study the creation of voice AI agents using AWS and Python. Develop an assistant with real functionalities and a deep understanding of the architecture.
    3h 1m5/5
  • Vibe Code a Generative AI Finance App with Python and LangChain thumbnailNew

    Vibe Code a Generative AI Finance App with Python and LangChain

    By: Zero To Mastery
    Master the creation of AI applications for investments using Python and LangChain. Practice developing a fintech application and understanding financial metrics
    7h 36m5/5
  • Agentic AI Engineering Course thumbnailNew

    Agentic AI Engineering Course

    By: Paul Iusztin, Towards AI, Louis-François Bouchard
    Become an expert in creating AI agent systems for production. Learn how to develop scalable AI agents and make them work in real-world conditions.
    7h 33m5/5

Frequently asked questions

What prerequisites are needed before taking this course?
While specific prerequisites are not listed, a basic understanding of software development concepts and familiarity with coding practices would be beneficial. The course focuses on using AI to enhance development workflows, so prior programming experience will help you better grasp the concepts and tools discussed.
What will I be able to build by the end of the course?
By the end of the course, you will be able to set up AI assistants from scratch and create workflows that incorporate AI for tasks like auditing codebases, building command chains, and connecting to databases, APIs, and services. The course emphasizes creating stable and safe code outputs and leveraging AI tools to enhance productivity.
Who is the target audience for this course?
The course is aimed at developers looking to integrate AI into their development workflows to increase efficiency. It's suitable for those interested in learning how to use AI tools to maintain clean code and long-term stability while speeding up feature delivery.
How does this course compare to other AI courses?
Unlike many AI courses that offer general AI concepts or one-off demos, this course focuses on practical application in real development work. It provides simple, repeatable steps to integrate AI into your workflow and emphasizes engineering practices over random AI use, ensuring you maintain control over your codebase.
What specific tools or platforms are covered in the course?
The course covers using slash commands for common tasks, init scripts for starting new projects, and creating command chains and simple automation. It also includes connecting AI tools to databases, APIs, and services, and setting up AI assistants from scratch with guardrails for stable and safe code output.
What topics are not covered in this course?
The course does not cover basic AI theory or machine learning algorithms. Instead, it focuses on applying AI in a development context, emphasizing workflow integration and practical use cases rather than theoretical foundations.
How much time will I need to commit to this course?
The course runtime and the number of lessons are not specified, so it's difficult to estimate the exact time commitment. However, given the course's focus on practical, hands-on learning, expect to spend time not only watching lessons but also applying what you learn to your own projects.