GitHub Copilot is presented as an AI pair programmer, that plugs into the user's editor. It then turns natural language prompts into code, offers multi-line function suggestions, speeds up test generation, filters out common vulnerable coding patterns, and blocks suggestions matching public code.
$10
per month
Codex
Score 8.7 out of 10
N/A
Codex is a specialized, agentic desktop application developed by OpenAI designed to serve as a command center for software engineering and autonomous coding tasks. Distinct from the general-purpose ChatGPT application, Codex is optimized for project-level repository management, allowing developers to orchestrate multiple AI agents that can research, implement, and verify code changes across a local or cloud-based codebase.
Copilit is fantastic at the following: 1. Solving simple, well-defined problems, such as implementing an algorithm, manipulating a data structure, or string manipulation and regex. 2. Implementing simple APIs that are mainly CRUD in nature, with moderate business logic inside them, which may involve some processing or passing the data through an algorithm. 3. Implementation of well-defined activities, such as implementing a connection to an Oracle DB using Hibernate or JDBC, or implementing boilerplate code for a backend service to listen to Kafka events. It is not that great when it comes to understanding and implementing code in a proprietary DSL. It struggles when implementing a major feature across a complex codebase. I believe developers should also adopt the trust-but-verify paradigm when expecting highly secure or regulated code from GitHub Copilot.
Codex is great for coding, but also really good for knowledge work. when used properly, codex can take over executing actions correctly and precisely over multiple software products, enabling more focus and less context switching.
I feel that GitHub Copilot's overall usability is good due to its tight integration with Visual Studio and the workspace. However, developers expect greater ease of use, as there is a learning curve to realize productivity gains with the tool fully. I think there is room for improvement in GitHub Copilot's UI integration within Visual Studio.
I am using OpenAI Codex to help me to write complete automation framework. Like previously I am manually written the test scripts but after using it it enhance me the speed of writing scripts as well as with more efficient manner and just give some images and videos to help to understand the AI agents what are you want ? So its convert into your accordingly demand coding
It is useful that copilot integrates so well with vscode, which is a very common IDE. I used Tabnine for a little while but it was not that intuitive, and did not seem as helpful as GitHub copilot was. I have enjoyed GitHub copilot a lot, especially the ease of hitting the tab key and seeing quick progress in my tasks.
I use Codex, Claude Code and Cursor daily, but focused on different tasks. Codex as an app is the best overall and has the most reliable models. Would like to see better and easier ways to spin up cloud agents, like Cursor does.
