AI Tools Engineers Need To Stop Fearing (And Start Using!)
Put artificial intelligence in the copilot seat and try these five options to understand this work revolution, and perhaps increase your production levels or even decrease the hours you need to crunch:
The world is changing for code engineers and natural language prompts are growing fast. They are also transforming job descriptions. Natural language will soon suffice to carry out tasks thanks to AI. Engineers need to start experimenting with AI tools. Here are some of the best tools to code without coding,
- Copilot and Codex: the ones that have everyone talking
Surely you have heard about these two projects, since they were the most talked and written about, and they share the same basis.
One of them, GitHub Copilot, is the power of training IAs with the common and shared knowledge of a coder community. It was trained on billions of lines of code and it can turn natural language prompts into coding suggestions across dozens of languages. Copilot will share its recommendations based on your project’s context and style conventions. And then it’s up to you to accept, reject or edit.
The other one is the heart of it all: Codex. Launched by Open AI, one of the most famous AI companies right now, it is the engine that powers GitHub Copilot, and is proficient in more than a dozen programming languages.
Advice: If you still want to sit in the driver’s seat, Copilot might be the way to go.
2. Code T5: a powerful and versatile OpenSource option
With powerful options like translating from one language to another, correcting errors, and -of course- prompting in natural language, Code T5 is one of the best and more capable OpenSource choices.
This transformer-based model for code generation is based on T5 architecture. As a code-awre, encoder-decoder-based pre-trained programming language model, it enables a wide range of code intelligence applications.
Advice: If you consider yourself an expert, try this one, some say it could be trained to be the most powerful. For more, you can read the original paper.
3. PolyCoder: the one dethroning the kings
The developers of PolyCoder claim that their OpenSource code generator can beat Codex and Copilot. It sure is an option that no one can miss when exploring this fast-changing landscape.
This AI code generator can write source code in different programming languages. Developers swear that it will reduce software development costs at the same time it allows developers to focus on creative and less repetitive tasks. PolyCoder was trained with data from various GitHub repositories that include these languages: C, C#, C++, Go, Java, JavaScript, PHP, Python, Ruby, Rust, Scala y TypeScript.
Advice: If you already use Codex, definitely try it and see for yourself.
4. PyCharm: a Python companion
For Python developers, the Czech company JetBrains has developed an AI solution that says it can solve most of the problems and expand the coder power: PyCharm.
It is an integrated development environment used for programming in Python that provides code analysis, a graphical debugger, an integrated unit tester, integration with version control systems and support web development with Django.
Advice: This is the best option for beginners.
5. Autocompletion: the option with more human control
If you still like to have total control over your code, or use a unique method you think AI could interrupt, there are some powerful autocompletion tools for you to try. You can think about this as a little nitro that would accelerate your step.
TabNine and Jedi are two of the best ones out there to try. TabNine uses generative AI technology to predict and suggest the next code line based on context, syntax, whole line compositions, full-function code completions and, of course, natural language to code. Completion can be run on a developer’s laptop, on a server inside a firewall or in the cloud.
On the other hand, Jedi is a static analysis tool for Python that can be used in IDEs/editors. It has support for two different goto functions and uses a very simple API to connect with IDE’s.
Advice: If you have doubts about AI or don’t feel comfortable yet, go with these.
You are all set: now you can test for yourself how to code with an artificial copilot. Evaluate for yourself the future of your work. What do you feel about using them?
Do you know any other tools worth mentioning?
Let’s build on this debate!
