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Here’s a checklist of important considerations that will help you identify the right tool for your stack and workflow.
Outline what you want for your team
Let’s start at the beginning – what does your team need help with? There are AI coding assistant tools that can help autocomplete and generate code, detect errors, assist with documentation, and provide more contextual help.
While some tools provide general support, others specialize in specific use cases and provide deep coverage over a specific area. Understanding where these tools can help your team will help you identify the right tool for the job.
Evaluate how it will connect to your stack for your team
Does your team want a tool that connects directly with their code environment? IDE-integrated assistants like Copilot offer real-time coding support within the development environment, while chatbot-based assistants like ChatGPT provide more versatile interaction options but may lack seamless integration with coding workflows. The choice between the two depends on the preferences, requirements, and workflow of individual developers and teams.
Review the quality of information the tool will provide your team
First, you want to be sure the tool in question is proficient in the language(s) and framework(s) your team uses. Not all tools provide support for all languages.
Next, get a sense of the quality of information the tool will provide you. How well does it provide suggestions? Does it understand the context of your code? Is it actually providing helpful knowledge in the areas where you need coverage? If possible, allow your team to demo or trial the product so they can weigh in on how helpful the tool will be for them.
Finally, it’s important you understand how you may use the information the AI coding assistant may provide you. Check with your legal team to confirm you won’t have copyright ownership issues.
Security and compliance checks
Whenever bringing any new tool into your stack, it’s important to understand how it prioritizes the protection of user data, mitigates security risks, and complies with industry standards and regulations. This is especially true of AI coding assistants where there is opportunity to not only expose user data, but also your organization’s IP.
It’s critical you work with your security team to understand how data will be stored and shared, who has access controls and permissions, and how communication channels are encrypted, among other standard security and vulnerability assessments.
Try them out
Let your team see how well these tools actually work for them by taking them for a test run. Remember, AI coding assistants are an aide. They’re here to help your team work more efficiently. Perhaps you’ll choose a tool that serves many needs, or maybe you’ll be open to choosing a couple of specialized tools that answer special use case needs.
Ultimately, it’s important to find a tool that integrates into your stack, provides useful information, and enhances your workflows.
