My Top AI tools for Coding

I like to think of myself as a fan of technology first. So, the new shiny and recently released tools are attracting my attention. It’s something new to try so I didn't want to miss out. With all the buzz around ChatGPT, I fell for the trap myself. Tried chatbot for coding, building architecture, and stacks for projects. The results were not bad if you aim for repetitive, usual solutions in programming. So, I thought coding helping tools need to have only one role, not thousands like the OpenAI tool. Here are the code helpers that you can test and bring to your workspace ??

TabNine

Probably the one that’s most useful for Javascript autocomplete functions. TabNine is an AI-powered autocomplete tool for code editors that uses deep learning to suggest code completions. It supports a lot of programming languages, including Python, JavaScript, Typescript, PHP, Rust Go, and Java. The tool is trained on the most popular public repositories like GitHub, so it has many options while you type. They recently acquired Codota so it’s being integrated and can be useful too.?

??Price:?

free Starter version

12$/month per 1 user

Advantages:

? Fast and responsive code completions

? Supports a wide range of programming languages

? Can learn from your own code to improve suggestions

? Trained on different languages separately (not bulk trained like ChatGPT)?

Disadvantages:

? Requires a lot of system resources and may slow down your editor (eating CPU)

? May suggest irrelevant or incorrect code completions (not a lot though, and it learns on mistakes faster than other tools)

GitHub Copilot

GitHub Copilot is similar to TabNine but uses GPT-3 language models to suggest code completions based on your context. It has to be used with VS Code or other code editors. Supports popular languages: JavaScript, TypeScript, Python, Ruby, Go, Rust, PHP, Java, C#, C++, HTML/CSS, and counting.?

??Price:

10$ for individual use

19$ for business?

Advantages:

? Improved code quality: suggests optimization and usually good choices

? If you are an active contributor to Github, it gets cheaper or free

? Offers multiple solutions to one problem and you can choose one you like

Disadvantages:

?Needs to be turned off or is very distractive

? The options it offers aren’t always optimized so you’d still go to StackOverflow

?Could cause many copyright issues in the future

DeepCode

DeepCode is a code-analysis tool that looks for potential issues in your code. Catching bugs before they appear and improving security measures are other tasks it can do. A combination of static analysis and custom machine learning algorithms makes it effective for spotting most of the troubles. They call themselves “Grammarly for coders” and now are part of Snyk.?

??Price:

has a nice free tier

pricey for teams $98 per contributing dev/month

Pros:

?great for big codebases, fast in execution?

?are concentrating on looking for security gaps

? supports Java, Python, JavaScript, TypeScript, C/C++

Cons:

?requires some set-up and config before using?

?not compatible with some languages, frameworks

IntelliCode?

IntelliCode is a set of AI-powered tools for code editors, including code completion, suggestion, and refactoring. It uses machine learning to improve its suggestions based on your context and coding style. It’s a VSCode extension with development features for Python, TypeScript/JavaScript, and Java developers. To be honest, VScode has loads of useful extensions both free and paid, so check them out.?

??Price:

free for VScode users

Pros:

?makes context-aware suggestions?

?great for collaboration as it’s integrated with VScode and Github

Cons:

?doesn’t take your coding style into consideration

?limited list of languages?

? there’s some learning curve?

Which Business Ideas Would Benefit from AI?

Not all software projects could use AI coding tools. Only experienced developers that know how AI works and uses data, can approach it right. With all the AI API integration going on, it’s vital to assess such steps for possible business risks.

As for me, open-source projects can use AI without much hassle. Develop, test, release and gather feedback fast and improve even faster. However, those who have a lot of vulnerable data or security risks should treat AI tools as an instrument that needs evaluation first.

And a final warning: check your project’s or company’s guidelines before using any AI tools. Sometimes speeding up coding isn’t worth lawsuits ??

Happy coding!