
Create a simple Go project structure with modules, a cmd folder for maker and server, and an internal agents package, then add a Makefile and run the project.
Build an OpenAI client in Go and generate an entire medium-sized Go project from a first prompt, parsing model responses into files (including a readme) with system and user prompts.
Add command line arguments to configure the Golang agent, including the open api key, output directory, base package, and worker count, with environment variable fallbacks and validation.
Stabilize llm responses by crafting solid system prompts and templates, enabling predictable output for building files and programs such as a to-do app, makefiles, and go code.
Learn to load and manage code templates in Go by loading embedded and user-defined JSON templates, handling directories, JSON validation, and default fallbacks.
Build a code generator in Go by implementing a generate code method with templates. Process templates, set the agent language, create files, and queue tasks for OpenAI prompts.
Polish the golang cli by accepting model and timeout via command line, building the prompt from all args, and wiring the OpenAI model into the http client to generate code.
Set up an HTTP server and WebSocket using Gorilla Toolkit, define project request and progress event types, and implement a JSON writer with a mutex to manage the WebSocket connection.
Implement an http handler that upgrades to a websocket, reads json project request, and sends progress events to front end while driving code generation with an OpenAI client, zipping directory.
Ever wanted to harness the power of AI to write code for you? In this hands-on course, you'll build your very own AI code generation tool using Go! This is the first Golang course on this subject.
I'll guide you step-by-step as we create a powerful application that uses OpenAI's API to generate complete projects in multiple programming languages. You'll learn how to implement concurrent processing, template systems, and even build a sleek web interface.
The course focuses on using prompt engineering to get a consistent response from the LLM, which we, in turn, parse to build out our program. What you will build in this course is fantastic and shows AI's unlimited power.
By the end of this course, you'll have:
A fully functional AI code generator with the ability to generate full project.
Support for Golang, Python, JavaScript, and Java
A professional web UI with real-time progress tracking using WebSocket
Skills to build your own AI-powered development tools
Learn how t build a code generation engine from scratch
Perfect for Go developers curious about AI integration or anyone looking to boost their productivity with custom AI tools.
No AI experience needed - just basic Go knowledge!
Join me and discover how easy it is to build your own AI coding assistant!