We’ve talked about the growing importance of AI in the past. Their benefits, the opportunities present in implementing them in the software development process were just some of the topics we touched upon. Everywhere you look, most businesses are looking to implement and optimize AI into their products and business processes.
Software development isn’t exempt from this trend. With agility as the main focus of most software development companies, AI in software development is being used to increase productivity and bring about better final products through refined processes. Here, we’ll be giving a list of AI tools companies can begin implementing if they’re looking to implement AI for product design or development as a whole.
This list consists of AI tools specially thought of for software development as a process. AI development tools such as these help developers become more agile in their deliveries, reducing the number of errors that need revision, and optimizing development pipelines for better, agile software development. These AI tools for software development are:
AI tool that provides developers with autocompletion functions in real time. It’s compatible with a number of programing languages, including Python, JavaScript, and TypeScript. It’s also compatible with many integrated development environments (IDEs) like JetBrains and Neovim. If that wasn’t enough, it uses open-source libraries to improve it’s autocompletion capabilities, as well as the activity of its users. Meaning, the more the AI tool is used, the more it updates and improves.
Tabnine is an AI tool for software development that’s based on code completion for over 20 programming languages. The difference between Tabnine and something like Copilot is that Tabnine functions within it’s own programming, compared to the former, which operates using the OpenAI Codex. This gives Tabnine a better security for code being developed with it compared to other technologies. The accuracy of these code predictions is also something to take note about.
DeepCodes main offer in the AI tool sphere is its static code analysis capabilities. Unlike the previous AI tools we’ve talked about before, DeepCode is used as a code auditor in a sense, analyzing software for any bugs vulnerabilities and security flaws that could have gone through the cracks. Though it is limited to a few programming languages, like Python and TypeScript, the results in its analysis and recommendations are extremely effective, making it a perfect AI tool for software development that has QA within its scope of work.
AWS brings its own code completion tool to the table of AI tools for software development. This tool was specially made thinking about cloud developers and their needs. Even more specific, the benefits are geared more towards cloud developers working in the context of AWS, making this tool a bit narrower in scope compared to other tools we’ve listed before. This doesn’t mean that it isn’t compatible with other IDEs however, though results will be better suited for AWS Cloud9 over others. IT also has built in vulnerability scouts, giving it the best of both worlds.
Kite is perhaps the most restricted AI tool for software development on this list, though that doesn’t make it any less useful than the others. Kite is another code completion tool, though it specializes in Python and JavaScript, while offering limited support for other programming languages. This specialization makes it so that the autocompletion function understand the specific quirks of these programming languages more than others.
Replit Ghostwriter combines the benefits of other AI tools for software development we’ve mentioned here, and adding a team element to the mix. Though other code completions tools work in a vacuum, the distinguishing benefit of this tool is that it allows for code reviews and autocompletion within a team setting, allowing for active feedback and editing capabilities. The downside here is that, unlike other tools, this one is only compatible with a single IDE, and it’s the Replit IDE. Meaning, features that are found in other IDEs except for Replit will be out of a user’s reach.
One of the most versatile security testing ai tools for software development there are. Not only is compatible with most of the IDEs and CI/CD tools, but it implements continuous security checks alongside integrations along the whole development process, allowing for the security features to be in their best form.
This ai tool for software development uses a different approach to recommending code. While most analyze context and tool quirks for their code recommendations, Visual Studio takes the collective behavioral data from teams working on a specific project and recommends different lines of code based on the way teams carry themselves throughout the project. Intellicode is tailored to Microsoft’s specific tech stack, making it ideal for MS oriented development. The downside is that it truly only works with Microsoft environments, making it even more restricted than even the AWS alternative we mentioned in previous entries.
Mendable contribution to ai for software development is different from any other tool we’ve mentioned before. This ai tool works more like a search engine instead of a autocomplete software. It focuses on searching for snippets of code and corresponding documentation for projects. The efficient use of this tool allows for projects to find useful materials faster than just searching for them on your own. Projects that need constant documentation, naturally, are a prime fit for an ai tool like Mendable.
Possibly one of the most prevalent branches of business where AI has been implemented. AI and business go hand in hand, as it represents the ultimate form of productivity and efficiency. As there’re so many tools to document, we’ll be focusing on the areas of general improvement that these tools can provide, alongside a few examples. This way, you’ll have a better idea regarding how are businesses using ai.
AI in project management was one of the first ways of implementing AI beyond the introduction of Chat GPT. Using it for organizing your tasks and prioritizing them using historical data can allow your business to properly set better goals throughout the year. These tools don’t just offer AI as the one trick pony, but use it as a compliment for their real offerings.
Tools like Asana use AI to analyze historical data to help set better goals throughout the year, identify workflow risks and blockers and answers questions about your specific project like a curated chatbot. Others like BeeDone keeps track of your habits and assistance when needed, all while gamifying tasks to help team members achieve their goals. No matter the tool you pick, Ai in project management can help keep your day-to-day more organized and productive.
A central hub where all the functionalities of AI tools for business can offer a fully automated experience. Automated workflows, ai-powered chatbots to building your own ai virtual assistant. These a some of the things you could hope to accomplish through an automated interface.
ChatBots like the original GPT and any ChatGPT alternative where the main reason why AI became such a mainstream hit with users and businesses alike. They constitute the base for most innovations within the field, creating language models that are capable of answering questions of any kind, using advance reasoning and logic.
Most of these offer benefits for the administrative side of the business, like ChatGPT, the current market leader for these kinds of products. Others like Claude extend their reach to other activities, such as coding based off of specific prompts, writing documents, among others. These tools are the most advanced right now, and they’ll continue leading the charge in the innovations around ai tools for business.
AI tools for business can even make it easier to organize and access knowledge that you need for any given moment. Similar to some of the tools that assist with sifting through documentation we spoke of before, these tools can help organize notes and information in a way that is easier to find and get access to compared to sifting through them yourself.
Tools like Mem let you store your data on their platform while their AI does the rest in sorting and organizing that data properly. Others like Notion offer AI capabilities so precise that it can help you find past notes and data that otherwise would have been lost.
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