I Tried Every AI Coding Assistant
TLDRThe video script offers a detailed review of various AI coding tools, comparing their capabilities in code autocompletion, generating test cases, and understanding code repositories. It evaluates tools like TabNine, Chat GPT, GitHub Copilot, Bard, Amazon CodeWhisperer, Sourcegraph Cody, and Codiuum AI, placing them in different tiers based on their performance. The reviewer finds GitHub Copilot and Codiuum AI particularly useful for their specific strengths in coding efficiency and test case generation, respectively.
Takeaways
- 🔍 TabNine offers AI-powered code completion and a chat feature similar to GitHub Copilot.
- 🤖 The AI chat feature in TabNine provides correct information about the time complexity of factorial but made an error regarding the complexity being of N squared.
- 🔧 TabNine can identify and suggest fixes for code issues, such as correcting the base case condition in a factorial function.
- 📝 TabNine can generate test cases for code, but the user noted a desire for more varied and random test cases.
- 📈 Chat GPT is considered a useful tool for learning but may not be the best for coding tasks due to potential context switching.
- 💬 GitHub Copilot provides a more accurate and efficient code completion experience compared to TabNine, with better test case generation.
- 🔗 Bard, while similar to Chat GPT, cites sources for information, which can be helpful for verification but may be slightly less accurate.
- 🔍 Amazon CodeWhisper, Amazon's AI coding tool, has a reference log feature that shows the source of the code suggestions.
- 📊 Sourcegraph Cody claims to understand entire code repositories but did not perform well in the user's test with a real codebase.
- 🧠 Codium AI focuses on testing and improving code, providing detailed test cases and code analysis, and is considered a top-tier tool for developers.
- 🛠️ The user plans to continue using Chat GPT, GitHub Copilot, and Codium AI as part of their AI developer suite.
Q & A
What is the core functionality of Tab N as described in the video?
-Tab N functions similarly to GitHub Copilot, offering code autocompletion and an AI chat feature within an IDE, allowing for easy generation and explanation of code, such as autocompleting a factorial function.
How did Tab N handle the correction of a factorial function with incorrect base case condition?
-Tab N correctly identified that the base case condition for the factorial function was incorrect when changed to equal to 1 instead of less than or equal to 1, providing a correct suggestion on fixing it.
What was the issue with the time complexity explanation provided by Tab N for the factorial function?
-Tab N correctly stated the time complexity of factorial as O(n), but incorrectly concluded it as O(n^2), which was a mistake.
What limitations did the video highlight about using Chat GPT as a coding tool?
-While Chat GPT is praised for providing context and aiding in learning, it was noted for potentially adding unnecessary context switching when coding and occasionally providing confidently incorrect information without citing sources.
How did GitHub Copilot's functionality compare to Tab N in the video?
-GitHub Copilot was shown to have similar autocompletion capabilities, but it also included an AI chat feature and was able to handle more sophisticated tasks like fixing code for handling negative numbers in a factorial function and generating comprehensive test cases.
Why was Codium AI placed in the 10x developer category?
-Codium AI specialized in testing code and improving code quality, providing detailed test suites, code analysis, and suggestions for improvement that were accurate and highly useful, making it stand out for its specific functionality.
What was the perceived weakness of Amazon CodeWhisperer as mentioned in the video?
-Amazon CodeWhisperer was noted for mainly providing a feature similar to one aspect of GitHub Copilot's functionality but doing it less effectively, though it could potentially excel in AWS-specific features.
How did the video describe Sourcegraph Cody's attempt at understanding code repositories?
-Sourcegraph Cody aimed to understand and make suggestions based on the entire code repository but was criticized for its slow performance and inability to effectively parse and understand the repository, often failing to find relevant code logic.
What unique feature of Bard was highlighted in comparison to Chat GPT?
-Bard was noted for citing some sources, providing a way to verify information and gain further reading, despite being considered slightly less accurate than Chat GPT.
What was the final assessment of the AI coding tools presented in the video?
-The video concluded with a preference for using Chat GPT for learning and context, GitHub Copilot for efficient coding without context switching, and Codium AI for testing and improving code, each serving a unique purpose in the developer's toolkit.
Outlines
📝 Exploring AI Coding Tools: TabNine and GitHub Copilot
The video script discusses the use of AI coding tools like TabNine and GitHub Copilot. TabNine is compared to GitHub Copilot, with a demonstration of its code autocompletion and chat feature. The script highlights the tool's ability to autocomplete a factorial function and its mixed performance in providing correct information regarding time complexity. It also showcases the tool's capacity to fix code issues and generate test cases, although it notes some inaccuracies and limitations in its responses.
🤖 ChatGPT as a Coding Tool: Pros and Cons
The script evaluates ChatGPT as a coding tool, acknowledging its usefulness for learning but noting its drawbacks for practical coding tasks. It criticizes the lack of source citation and the potential for providing incorrect information confidently. Despite these issues, ChatGPT is placed in the 'actually useful' tier, with the video creator expressing a preference for other tools like GitHub Copilot for more efficient coding.
🔍 Comparing Bard and Amazon CodeWhisper
The video script compares Bard and Amazon CodeWhisper, two AI coding tools. Bard is noted for citing sources, which adds credibility, but it is also observed to be less accurate than ChatGPT. Amazon CodeWhisper, Amazon's version of GitHub Copilot, is tested for its autocompletion capabilities and its ability to generate test cases. The script finds CodeWhisper's performance to be inferior to GitHub Copilot, suggesting it might be more useful for AWS-specific features.
🔎 Sourcegraph Code Review and Repository Understanding
The script explores Sourcegraph's ability to understand an entire code repository and make suggestions based on it. It tests the tool's performance with a factorial function and its capacity to generate test cases. The video creator is disappointed with Sourcegraph's slow performance and its inability to integrate effectively with the repository, despite its promising feature set. The tool is placed in the 'acceptable' category due to its potential but current limitations.
🧠 Codium AI: Specialized Testing and Code Improvement
The script highlights Codium AI's unique approach as a specialized tool for testing and improving code. It demonstrates the tool's ability to generate comprehensive test suites, provide detailed code explanations, and offer suggestions for code improvements. The video creator praises Codium AI for its focus on code quality and test case generation, placing it in the '10x developer' category for its effectiveness in these areas.
Mindmap
Keywords
💡GitHub Copilot
💡Time Complexity
💡Chat GPT
💡Code Autocompletion
💡Test Cases
💡Code Comments
💡Merge Sort
💡AI Coding Tools
💡Code Whisper
💡Sourcegraph Cody
💡Codium AI
Highlights
TabNine is an AI tool similar to GitHub Copilot that auto-completes code within IDEs like VS Code.
TabNine provides an AI chat feature to discuss code-related queries, such as time complexity.
TabNine correctly identifies the base case condition for a factorial function but fails to explain why it's wrong.
The AI chat feature struggles with providing accurate information, as it incorrectly states the time complexity of factorial as O(N^2).
Chat GPT is praised as an amazing tool for learning but may not be the best for coding tasks due to context switching issues.
GitHub Copilot offers an AI chat similar to Chat GPT and can also auto-complete code with inline commands.
Copilot provides a more exhaustive test suite for code, using a testing framework, compared to TabNine.
Bard, another AI tool, cites sources for information, which can be helpful for verifying accuracy.
Amazon CodeWhisper, Amazon's version of Copilot, lacks a chat feature but attempts to auto-complete code.
Sourcegraph Cody claims to understand entire code repositories and make suggestions, but its performance is mixed.
Codium AI specializes in testing code and improving it with test cases and code suggestions.
Codium AI generates test cases that can find errors in the user's code, which is a valuable feature.
Codium AI provides professional-looking code documentation and explanations.
The user plans to continue using Chat GPT, Codium AI, and GitHub Copilot as their AI developer suite.
The video includes a tier list of AI coding tools, ranking them from 10x developer tools to artificially unintelligent.
The user's experience with Bard shows it to be less accurate than Chat GPT, particularly in generating a Tic Tac Toe game in React.
Amazon CodeWhisper's reference log feature provides insights into the source of the code, which can be useful for licensing and compatibility checks.
Sourcegraph Cody's ability to understand the entire codebase is not as effective as claimed, as it struggles to find specific logic within a codebase.
Codium AI's focus on code improvement and test case generation makes it a top-tier tool for developers, despite not being a full-fledged code auto-complete tool.
