I Tried Every AI Coding Assistant

Conner Ardman
22 Nov 202324:50

TLDRThe video compares various AI coding assistants, evaluating their performance in autocompleting code, providing accurate information, and generating test cases. Tools like TabNine, GitHub Copilot, and Codium AI stand out for their efficiency and accuracy. The video also critiques Bard and Amazon CodeWhisperer for their shortcomings. Sourcegraph Cody's repository understanding feature is noted but found lacking. The host assembles an AI developer suite with Chat GPT, GitHub Copilot, and Codium AI for optimal coding assistance.

Takeaways

  • 😀 TabNine offers autocomplete and AI chat features within IDEs like VS Code, but its explanation of time complexity can be inconsistent.
  • 🔍 The video tests TabNine's ability to fix code issues, finding that while it can identify some errors, it doesn't always explain them well.
  • 📝 GitHub Copilot provides a more accurate and efficient coding assistance compared to TabNine, including better handling of edge cases and time complexity.
  • 💡 Sourcegraph Cody claims to understand entire code repositories for making suggestions, but it struggles with identifying specific logic within a large codebase.
  • 🤖 Bard, similar to ChatGPT, provides sourced information but is slightly less accurate in coding tasks, such as generating a working tic-tac-toe game in React.
  • 📈 Amazon CodeWhisper is comparable to GitHub Copilot but lacks a chat feature and doesn't perform as well in autocompletion and test case generation.
  • 🛠️ Codium AI specializes in testing and improving code rather than general code completion, offering detailed test suites and code analysis.
  • 🔧 The video demonstrates how AI coding assistants can generate test cases and improve code quality, but their effectiveness varies.
  • 📚 The reviewer plans to use a combination of ChatGPT, GitHub Copilot, and Codium AI for their development work due to their complementary strengths.
  • 🔑 The takeaways highlight the importance of choosing the right AI tool for different aspects of coding, from learning to efficient code writing and testing.

Q & A

  • What is the core idea of TabNine?

    -TabNine is an AI coding assistant that provides autocomplete code suggestions as you type within an IDE like VS Code. It also includes an AI chat feature for asking questions about the code.

  • What is the time complexity of a factorial function according to TabNine?

    -TabNine initially provides the correct time complexity of a factorial function as O(n), where n is the number of iterations. However, it incorrectly states it as O(n^2) later on.

  • How does TabNine respond to incorrect code?

    -When presented with incorrect code, TabNine identifies the issue with the base case of a factorial function but does not effectively explain why it is wrong.

  • What command options does TabNine offer?

    -TabNine offers command options such as explaining code, writing comments, and generating test cases.

  • How accurate are the test cases generated by TabNine?

    -The test cases generated by TabNine are correct but lack variety, often using sequential or repeated values rather than random numbers.

  • What is the author's opinion on Chat GPT as a coding tool?

    -The author finds Chat GPT to be an amazing tool, particularly for learning due to the context it provides. However, it is not considered the best option for most coding tasks due to the context switching it requires.

  • How does GitHub Copilot handle negative numbers in a factorial function?

    -GitHub Copilot suggests returning 'Not a Number' for negative inputs in a factorial function, which is a reasonable approach according to the author.

  • What does GitHub Copilot provide that sets it apart from other AI coding assistants?

    -GitHub Copilot stands out for its ability to create comprehensive test suites using actual testing frameworks, which is more than just console log statements.

  • What is Bard's main advantage over Chat GPT according to the video?

    -Bard's main advantage is that it cites sources, providing further reading and ensuring the correctness of the information it provides.

  • How does Amazon CodeWhisperer compare to GitHub Copilot?

    -Amazon CodeWhisperer is similar to GitHub Copilot in terms of autocompletion but lacks a chat feature. It also provides a reference log showing where the code suggestions originated from.

  • What feature does Sourcegraph Cody claim to do that is different from other AI coding assistants?

    -Sourcegraph Cody claims to understand the entire code repository and make suggestions based on the entire repository, which is intended to assist in larger projects with extensive codebases.

  • What is Codium AI's primary focus according to the video?

    -Codium AI focuses on testing code and helping improve it, rather than attempting to be an all-in-one code completion tool.

Outlines

00:00

🤖 AI Coding Tools: TabNine and GitHub Copilot

The speaker evaluates AI coding tools, starting with TabNine, which offers autocomplete and chat features within IDEs like VS Code. They test TabNine's ability to write and correct code, generate comments, and produce test cases for a factorial function. TabNine performs well but has minor inaccuracies. The speaker then compares it to GitHub Copilot, noting Copilot's superior performance in coding tasks and its ability to handle more complex functions like merge sort with greater accuracy. They categorize TabNine as 'decent' and Copilot as a '10x developer tool'.

05:00

💬 ChatGPT and Bard: Conversational Coding Assistance

The video script discusses the use of ChatGPT and Bard as conversational AI tools for coding assistance. ChatGPT, while amazing, may not be the best for direct coding tasks due to the context switching it requires. Despite this, it's still considered 'actually useful.' Bard, on the other hand, provides sourced information which is a pro, but it's slightly less accurate than ChatGPT, as seen in a tic-tac-toe game example. The speaker ranks Bard as 'actually useful' but prefers ChatGPT for more accurate and confident responses.

10:01

🔍 Amazon CodeWhisper and Sourcegraph Cody: Autocompletion and Code Understanding

The speaker tests Amazon CodeWhisper, which is similar to GitHub Copilot but lacks a chat feature. CodeWhisper shows promise in autocompleting code and generating test cases, although it sometimes adds unnecessary blank lines. Sourcegraph Cody is highlighted for its potential to understand entire code repositories and make suggestions based on them. However, the speaker finds Cody's integration with the repository to be lacking, as it struggles to find specific logic within a large codebase, despite its decent code autocompletion and AI chatbot features.

15:01

📈 Code Quality Improvement with Codium AI

Codium AI is presented as a tool focused on testing and improving code quality rather than general code autocompletion. The speaker赞赏Codium AI在生成测试套件和提供代码分析方面的能力，指出它能发现并建议修复代码中未处理的边缘情况。尽管Codium AI在某些建议上不是完美的，比如对非数字输入返回1而不是抛出错误，但它提供了专业的代码解释和文档。此外，Codium AI还建议对大于170的数字返回Infinity，因为JavaScript无法准确表示更大的数字。总的来说，Codium AI因其专注于提高代码质量和生成优秀的测试用例而被归类为'10x开发者工具'。

20:01

🛠️ Assembling the AI Developer Suite

In the final paragraph, the speaker reflects on their personal AI developer suite, which includes ChatGPT, GitHub Copilot, and Codium AI. They discuss how these tools cater to different aspects of development: ChatGPT for learning, Copilot for efficient coding, and Codium AI for code improvement and testing. The speaker expresses hope that using these tools will enhance their development skills and encourages viewers to find their own suite of tools to become better developers. They also humorously mention the YouTube algorithm's suggestion for the next video to watch.

Mindmap

Keywords

💡AI Coding Assistant

An AI Coding Assistant is a tool that uses artificial intelligence to assist in the process of writing computer code. These assistants can offer functionalities such as autocompletion, error detection, and even suggesting improvements or alternative methods of coding. In the context of the video, the assistant is being tested for its ability to autocomplete code, provide correct information about code complexity, and generate test cases.

💡Autocomplete

Autocomplete, in the realm of coding, refers to the feature where a tool predicts and completes the code for the user as they type. This can significantly speed up the coding process and reduce errors. The video assesses how well different AI assistants can autocomplete a factorial function, which calculates the product of all positive integers up to a given number.

💡Time Complexity

Time complexity is a computational complexity that describes the amount of time taken by an algorithm to run as a function of the length of the input. It is usually expressed using Big O notation. In the video, the assistant incorrectly identifies the time complexity of a factorial function, which should be O(n), not O(n^2).

💡Factorial Function

A factorial function is a common coding example used to illustrate recursion and is defined as the product of an integer and all those less than it. For instance, the factorial of 5 (denoted as 5!) is 5*4*3*2*1 = 120. The video script uses this function to test the AI assistants' ability to write correct code and identify errors.

💡Chat Feature

The chat feature in AI coding assistants allows users to interact with the tool through natural language queries or commands. In the script, the user tests this feature by asking questions about code complexity and requesting fixes for broken code segments.

💡Test Cases

Test cases are sets of conditions or variables used to determine whether a piece of software behaves as expected under certain circumstances. The video script describes how the AI assistants generate test cases for functions like the factorial and merge sort, which is a sorting algorithm.

💡Merge Sort

Merge Sort is a divide-and-conquer algorithm used for sorting lists. It has been used in the video to test the AI assistants' ability to not only autocomplete the function but also to generate test cases that validate the correctness of the merge sort implementation.

💡Code Complexity

Code complexity refers to how complex a piece of code is to understand and maintain. It is often associated with the efficiency of an algorithm. In the video, the assistants are evaluated on their ability to correctly identify the time complexity of the code they generate or are asked about.

💡GitHub Copilot

GitHub Copilot is an AI pair programmer developed by GitHub and OpenAI. It offers autocomplete suggestions for code directly in the developer's editor. The video discusses its performance in terms of code generation, handling edge cases, and providing test cases.

💡Bard

Bard, mentioned in the video, is a search engine developed by Google that incorporates AI to provide conversational answers to user queries. It is compared with other AI assistants in terms of its accuracy and utility in coding tasks.

💡Amazon CodeWhisper

Amazon CodeWhisper is an AI coding assistant developed by Amazon. The video evaluates its performance in autocompleting code and generating test cases, comparing it with other AI assistants.

Highlights

TabNine offers autocomplete and AI chat features within IDEs like VS Code.

TabNine can create a factorial function with a single command.

The AI chat feature incorrectly states the time complexity of a factorial function as O(N^2).

TabNine can identify and suggest fixes for incorrect code conditions.

TabNine provides partial credit for identifying the base case error in a factorial function.

TabNine can explain code and generate test cases.

GitHub Copilot provides similar autocomplete and AI chat features.

GitHub Copilot can handle negative numbers in factorial functions.

GitHub Copilot correctly identifies the time complexity of a factorial function as O(n).

GitHub Copilot can generate JSDoc comments.

GitHub Copilot creates comprehensive test cases using a testing framework.

ChatGPT is great for learning but may cause context switching during coding.

Bard provides sourced information but may be slightly less accurate than ChatGPT.

Amazon CodeWhisperer lacks a chat feature but offers autocomplete suggestions.

Sourcegraph Cody claims to understand entire code repositories for suggestions.

Codium AI focuses on testing and improving code quality.

Codium AI generates test suites and provides code analysis and suggestions.

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