Browse categories
AI coding: a guide for small business
AI has revolutionized coding. ChatGPT, Amazon CodeWhisperer, Microsoft IntelliCode, GitHub Copilot, and other tools are changing the way programmers create code.
Several AI tools help review code, reducing the time programmers spend in meetings, while chat-based AI tools can even help you develop a web app from scratch.
So how can businesses best leverage AI coding? Let’s dive in.
How does AI in coding work?
AI in coding leverages Natural Language Processing (NLP) technology and deep learning to help programmers write or review code. AI coding models have been trained on massive, programming-specific datasets and some of the things AI coding assistants can help with are:
● Converting code from one programming language to another
● Generating code from comments
● Generating code from the context of previous code lines
● Generating code from user prompts
● Debugging code
● Suggesting code improvements
● Analyzing code for security errors
● Code refactoring
Each AI coding tool has its unique characteristics. Many integrate directly into your IDE (Integrated Development Environment), making the AI coding experience seamless.
What are some popular AI coding tools?
Some of the most popular AI coding tools on the market include:
● IntelliCode by Microsoft: Included in Visual Studio.
● GitHub CoPilot: Monthly subscription. It's based on OpenAI's Codex.
● Tabnine: Need to use the paid version to obtain real value. They have extensive support for many IDEs and languages.
● Cody by Sourcegraph: Free. Excellent integration with your IDE. It provides both contextual and chat-based AI coding help.
Common AI coding mistakes
With so many AI tools available, it’s easy to make mistakes. Here are common ones to avoid:
Over-reliance
Generative AI's proclivity for hallucination when generating text applies equally when it generates code. You must thoroughly test the code an AI tool provides and verify that the code implements best practices.
AI coding tools aren't a replacement for human programmers but they can help beginner and advanced programmers alike.
If you're an intermediate programmer, you can use AI to create the basic structure of an app for you and then hire a programmer to review the final code, just to be sure it's secure.
These challenges can be overcome with a forward-thinking business strategy. Be proactive in implementing ethical frameworks, monitoring regulations, and checking guidelines for AI development and deployment. Interdisciplinary collaboration is likely going to be needed to adequately address these concerns.
Lack of context
Another common mistake is not providing enough context to the AI coding tool. It's easier for an AI coding assistant to suggest accurate code if you've provided extensive context compared to just a single code comment.
Licensing issues
Many AI coding tools were trained on vast datasets of public open-source code. If you intend to create a closed-source app, you need to know whether or not the AI-generated code came from an overly restrictive license that would force you to release your project's entire source code under the same license.
Consider to avoid using public repositories as sources for generated code. Failing to do so can involve you in problematic legal issues.
Integrated versus chat-based tools
Integrated tools work within your development workflow as part of your IDE. Chat-based tools such as ChatGPT and Google's Bard mean you have to step out of the confines of your IDE. That's fine for the occasional code lookup or debug, but it gets unwieldy when you need it often.
Chat-based tools are helpful for quick code snippets, debugging a specific error, or converting code from one language to another. You don't need to set anything up to use these tools.
These tools are also excellent during the brainstorming and design phases. You can ask ChatGPT questions about your app's recommended tech stack or infrastructure and receive surprisingly accurate answers.
Important: Always fact-check ChatGPT's output. Want to save time? Hire an AI fact-checker to help you with this.
Integrated tools are better for day-to-day coding but require more setup time.
Will AI coding replace programmers?
In its current form, AI coding is excellent for mundane and repetitive coding tasks, but tends to produce errors for more advanced tasks.
AI works best when coupled with human skill. If you're working on an app to offer to consumers and are mostly writing it using AI coding tools, you should definitely consult with a web programmer to review the app's code before launching it, to give your code a human touch.
