In the video, host Carl compares four AI coding tools—GitHub Copilot, Cursor, Codeium, and JetBrains’ PyCharm—by challenging them to build a simplified HTTP server in Python using a standardized task from CodeCrafters. Ultimately, Cursor performs the best, followed by Codeium, while Copilot is deemed the least effective, highlighting the limitations of AI in programming and the need for further improvement.
In the video, the host, Carl, conducts a thorough comparison of four AI coding tools—GitHub Copilot, Cursor, Codeium, and JetBrains’ PyCharm—by challenging them to build a simplified HTTP server in Python. Unlike typical AI demos that often showcase cherry-picked problems, Carl uses a standardized challenge from CodeCrafters, which provides clear instructions and grading, ensuring an impartial evaluation of each AI’s performance. He emphasizes the importance of transparency in AI demos and expresses a desire for companies to adopt a similar approach.
The challenge begins with the task of returning a “200 OK” response to a client. All four AIs initially fail this step, but PyCharm shows the most promise by recognizing the need to send the response to the client socket. However, it still fails to set up the client socket correctly. After receiving error feedback, all AIs manage to complete this step, but Carl notes that PyCharm’s code tends to be more complex, which often leads to more bugs. This complexity becomes a recurring theme as the challenge progresses.
As the challenge continues, the AIs are tasked with checking the requested path and returning appropriate responses. Cursor and Codeium successfully complete this step, while Copilot struggles significantly, introducing incorrect logic that leads to failure. Carl expresses frustration with Copilot’s inability to correct its mistakes, ultimately deciding to abandon it by the end of the challenge. Meanwhile, PyCharm attempts to implement error handling but complicates the code unnecessarily, leading to further issues.
In subsequent steps, the AIs are asked to handle client headers and manage multiple requests. Cursor and Codeium perform well, while Copilot continues to falter, prompting Carl to give up on it entirely. PyCharm’s approach to handling headers is overly complicated, resulting in a lengthy debugging process. Despite some successes, the AIs struggle with maintaining previously working features when new ones are added, highlighting a common issue in AI code generation.
By the end of the challenge, Carl ranks the AIs based on their performance: Cursor emerges as the best, followed closely by Codeium, while PyCharm takes third place and Copilot is deemed the worst. He reflects on the limitations of AI in programming, noting that none of the AIs completed all tasks successfully, which raises concerns about their potential to replace human programmers. Carl concludes that while AI tools can assist in coding, they still require significant improvement, and he plans to continue using Cursor and Codeium while discontinuing Copilot and PyCharm for practical work.