3 Best AI Coding Assistant Tools in 2023 | KodeKloud

KodeKloud
15 Nov 202309:45

TLDRJeremy Morgan, a training architect, introduces three generative AI tools that enhance software development: GitHub Copilot, Blackbox AI, and TabNine. These tools assist in coding, error detection, code simplification, and documentation. GitHub Copilot excels in language support and cloud operation without slowing down the machine. Blackbox AI offers detailed documentation and integrated code search at a cost-effective price. TabNine stands out for self-hosting capabilities and strong IP protection, as it does not send code over the internet. Morgan highlights the unique features of each tool, helping developers choose the one that best fits their needs.

Takeaways

  • 🤖 GitHub Copilot is an AI programming assistant that can simplify and optimize code, as well as help with error detection and fixing.
  • 📝 The 'Simplify' feature of GitHub Copilot can make code more concise without changing its functionality.
  • 🔍 GitHub Copilot can find and fix errors in code, including more complex ones, improving the development process.
  • 💬 The chat feature of GitHub Copilot can explain code, which is helpful for understanding code written by others or auto-generated code.
  • 🖋️ Blackbox is another generative AI tool for programmers that can improve script efficiency and readability.
  • 📚 Blackbox excels in generating code comments and documentation, and has integrated code search for easier navigation.
  • 💡 TabNine is a generative AI product for Visual Studio Code that offers smart code completion and is considered the fastest among the three tools discussed.
  • 📈 TabNine can suggest improvements to existing scripts, such as using list comprehensions or regular expressions for better efficiency.
  • 📝 TabNine's 'Generate Tests' feature can create test scripts, aiding in the development of robust and reliable code.
  • 🌐 Each tool has its unique advantages: GitHub Copilot for language support and cloud operation, Blackbox for documentation and cost-effectiveness, and TabNine for self-hosting and IP safety.
  • 🏆 The speaker personally prefers TabNine due to its speed and comprehensive features, despite the merits of all three tools.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is the introduction and demonstration of three generative AI tools that can transform the way software developers code: GitHub Copilot, Blackbox AI, and Tabnine.

  • How does GitHub Copilot help in coding?

    -GitHub Copilot assists in coding by simplifying code, optimizing it for better performance, identifying and fixing errors, generating unit tests, explaining code, and proposing fixes for bugs.

  • What feature of GitHub Copilot does Jeremy Morgan find particularly useful for simplifying code?

    -Jeremy Morgan finds the 'SLS - Simplify' feature of GitHub Copilot particularly useful for simplifying code, as it attempts to make the code more concise.

  • How does Blackbox AI differ from GitHub Copilot in terms of code improvement suggestions?

    -Blackbox AI provides different solutions from GitHub Copilot for improving code efficiency. It focuses on eliminating unnecessary if statements, enhancing readability, and reducing time complexity. It also adds comments as part of the solution, which can be helpful for understanding the code better.

  • What unique feature does Blackbox AI offer for tracking code changes?

    -Blackbox AI offers a unique 'View Diff History' feature that allows users to track and compare the changes made to the code.

  • How does Tabnine stand out in terms of code completion?

    -Tabnine stands out in code completion by providing the smartest and fastest suggestions among the three tools discussed in the video. It also supports generating tests and offers a chat feature for explaining code and solving coding problems.

  • What are some key considerations when choosing between GitHub Copilot, Blackbox AI, and Tabnine?

    -Key considerations include language support, integration with documentation and code comments, cost, security features like self-hosting and data privacy, and the ability to handle edge cases and non-permissive licenses.

  • Why might an organization prefer Tabnine over GitHub Copilot in terms of security?

    -An organization might prefer Tabnine over GitHub Copilot because Tabnine can be self-hosted, does not send code over the internet to their servers, and does not use user code to train its models, thus providing better control over data privacy and intellectual property.

  • What course is recommended for those interested in mastering generative AI?

    -For those interested in mastering generative AI, the video recommends the course 'Mastering Generative AI with Open AI' available on Code Cloud.

  • What is Jeremy Morgan's personal favorite among the three AI tools discussed?

    -Jeremy Morgan's personal favorite among the three AI tools is Tabnine, due to its smart code completion and other features that enhance the coding experience.

  • How can users access the generative AI tools discussed in the video?

    -Users can access GitHub Copilot from the VS Code extensions marketplace or through the GitHub website, Blackbox AI can be downloaded from the Blackbox website, and Tabnine can be found in the extensions marketplace or downloaded from Tabnine.com.

Outlines

00:00

🤖 Introducing AI Tools for Code Development

Jeremy Morgan, a training architect for Code Cloud, introduces three generative AI tools that have revolutionized the way he codes. These tools are tailored for software developers and utilize AI to enhance coding efficiency, error resolution, and documentation. The first tool discussed is GitHub Copilot, an AI programming companion that simplifies code and identifies errors. Jeremy demonstrates how Copilot can optimize a script meant to extract URLs from a sitemap. He also explores the tool's chat feature, which offers options like generating unit tests, explaining code, and proposing bug fixes. The video highlights how AI tools can sometimes make mistakes, but the benefits generally outweigh the drawbacks.

05:00

🛠️ Improving Code Efficiency with Blackbox AI

The second paragraph focuses on another AI tool for programmers, Blackbox. Jeremy uses the same sitemap script to demonstrate how Blackbox can enhance an inefficient script by identifying and resolving issues like unnecessary if statements and poor readability. Blackbox proposes a different solution from GitHub Copilot, emphasizing code efficiency and readability. It also includes comments as part of the solution, which is beneficial for understanding the code, especially for code written by others. Blackbox's unique feature of a view diff history allows tracking changes and comparing them. Blackbox AI also offers code completion that adapts as you write, saving time and effort.

🚀 Boosting Development Speed with Tab9

In the final paragraph, Jeremy introduces Tab9, a generative AI product for Visual Studio Code. Tab9 excels in smart code completion, making development faster and more efficient. The video shows how Tab9 suggests improvements to the script, such as using list comprehension or regular expressions. It also demonstrates generating tests with Tab9 and its chat feature, which provides solutions in plain English, making it accessible and user-friendly. Jeremy discusses the key features of each tool, highlighting that while they share similarities, each has unique aspects that might appeal to different users. He concludes by sharing his preference for Tab9 and encourages viewers to explore generative AI through a course on Code Cloud.

Mindmap

Keywords

💡Generative AI

Generative AI refers to artificial intelligence systems that are capable of creating or generating new content, such as code, based on patterns and data they have learned. In the context of the video, generative AI tools are used to assist software developers in writing more efficient and optimized code by providing suggestions, optimizations, and error corrections.

💡GitHub Copilot

GitHub Copilot is an AI-powered programming assistant that integrates with popular code editors to help developers write code more efficiently. It offers features like code simplification, error detection, and even generating unit tests. The tool learns from vast amounts of code to provide relevant suggestions, making the coding process faster and more streamlined.

💡Code Optimization

Code optimization is the process of modifying existing code to improve its performance, efficiency, or maintainability. This can involve reducing the complexity of the code, improving its readability, or eliminating unnecessary elements. In the context of the video, generative AI tools assist in code optimization by analyzing and suggesting improvements to the developer's code.

💡Error Detection

Error detection in programming refers to the identification of mistakes or bugs in the code that may cause a program to behave unexpectedly or fail. AI tools, as discussed in the video, can assist developers in finding and fixing errors by analyzing the code and providing corrections or suggestions.

💡Code Comments

Code comments are annotations added to the source code to explain specific parts of the code, making it easier for developers or other readers to understand the purpose and functionality of the code snippets. They are ignored during the execution of the program but are crucial for maintaining and updating the code.

💡Code Completion

Code completion is a feature in many modern integrated development environments (IDEs) that suggests possible completions for the code a developer is writing. This can include functions, variables, or entire lines of code, and it helps to increase the speed and efficiency of coding by reducing the amount of typing required.

💡Unit Tests

Unit tests are a type of software testing that involves testing individual units or components of a software application to determine if they are functioning correctly. These tests are usually automated and help developers ensure that changes made to the code do not introduce new bugs or errors.

💡Code Efficiency

Code efficiency refers to how well a piece of code performs its intended task with minimal use of resources such as processing time and memory. Efficient code runs faster, uses less memory, and is generally easier to maintain. The video emphasizes the importance of writing efficient code and how AI tools can help achieve this by suggesting improvements.

💡Self-Hosted

Self-hosted refers to the practice of running software, servers, or services on one's own infrastructure rather than relying on a third-party provider. This approach offers more control over the environment and can be crucial for applications with high security or privacy requirements.

💡Open Source Libraries

Open source libraries are collections of code that are freely available for use, modification, and distribution by the public. These libraries often provide common functionality that can be leveraged by developers to build applications more quickly and efficiently.

💡IP and Security

Intellectual property (IP) and security are critical concerns for organizations and individuals when using software tools, especially those that handle sensitive data or are integrated into the development process. Tools that transmit code snippets or data to external servers may raise IP and security concerns, so it's important to choose tools that align with an organization's policies and priorities.

Highlights

Jeremy Morgan shares his top three generative AI tools for coding.

GitHub Copilot is an AI programming buddy that can simplify and optimize code.

The 'Simplify' feature of GitHub Copilot reduces code complexity and improves readability.

GitHub Copilot can detect and fix errors in code, enhancing development efficiency.

The chat feature of GitHub Copilot allows generating unit tests and explaining code.

Blackbox AI is another generative AI tool that can improve script efficiency and readability.

Blackbox AI provides solutions for handling edge cases and includes detailed comments.

The 'View Diff History' feature in Blackbox AI helps track changes and compare code versions.

TabNine is a generative AI product for Visual Studio Code, excelling in smart code completion.

TabNine can suggest improvements using list comprehension, regular expressions, or XML e-tree.

TabNine's code suggestions include a visual diff of changes for better understanding.

The generative AI tools occasionally produce incorrect results, highlighting the need for human oversight.

GitHub Copilot offers great language support and runs in the cloud, not slowing down the machine.

Blackbox AI excels in documentation, generating code comments and integrated code search.

TabNine can be self-hosted, which is beneficial for high-security applications and customization.

TabNine does not send code over the internet and does not use it to train its models, ensuring IP safety.

Jeremy Morgan's favorite tool is TabNine due to its efficiency and comprehensive features.

For those interested in generative AI, there is a course on mastering generative AI with Open AI on Code Cloud.

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