The top AI tools transforming software development


The top AI tools transforming software development


Since launch about a year ago, it’s safe to say that Open AI’s natural language tool – ChatGPT – has well and truly brought artificial intelligence into the spotlight. Capable of doing anything from writing poems and explaining complex concepts to debugging code and passing major tests like the bar exam, ChatGPT marks a tipping point in our understanding and use of this technology. And the use cases for these models are endless.


Within the software development space, artificial intelligence is already changing the way developers work. Able to generate complex and accurate code, AI tools promise to transform software development as we know it; ramping up the pace of modern software development by taking over many of the more mundane, time-consuming tasks. On the ground, it just makes coding faster, empowering developers to get through more work in less time. But this doesn’t mean that AI will replace developers. Rather, it will have a multiplier effect – dramatically increasing developer productivity by taking care of repetitive programming jobs so that they can focus on unique problems and more complex reasoning.


So, what AI tools are having the most impact across Bluegrass’s dev teams? Here are a few of our favourites.



1. ChatGPT Plus


Perhaps the most obvious tool, ChatGPT Plus – the premium version of regular ChatGPT – offers improved accuracy, performance and speed. Simply put, GPT Plus is very good at code, particularly refactoring code and looking for issues. We use it as part of our code review processes and when we’re doing technical audits. It’s particularly useful with boilerplate code because these sections of code are repeated in multiple places with little to no variation.


As such, GPT Plus can work on this type of code a lot faster than a human could. This being said, it’s important to understand that any of these tools have limitations and can, sometimes, produce complete rubbish. The risk of errors creeping in makes it incredibly important to do internal training to make sure that your development teams understand the shortcomings of these tools and knows what to look out for when reviewing code generated by these and other AI models.



2. GitHub Copilot

GitHub Copilot is a cloud-based artificial intelligence tool developed by GitHub (owned by Microsoft) and OpenAI. Integrated within your development environment, GitHub Copilot essentially offers developers autocomplete on steroids, turning natural language prompts into coding suggestions in an instant. The tool has evolved massively since it was first launched back in 2021. And it was pretty useful already back then. What makes Github Copilot so great is the fact that it knows your open codebase files relatively well, which means that it has the context needed to make the best suggestions. This is one area where it has an edge over ChatGPT. Should Copilot get off track, you can write comments in the code to guide it down the right path and, obviously, it learns from this additional context.



3. Slack bots


This example isn’t entirely around development, but it is a good example of how we’re using AI to improve our processes and make our development teams more efficient. We have a Slack bot called Claude, which is basically a free Slack extension that is really good at summarising text. Essentially, Claude is a large language model that we use to summarise Slack conversations and package then in a way that is easy to follow and understand.



While all these tools are useful, it’s important to remember that when using any of these AI tools, you still must follow your regular code review processes. Dev teams must double check all output to ensure that there are no hallucinations, which occur when AI generates a response that contains false or misleading information presented as fact. Potential mistakes shouldn’t deter people from trying these tools out. You must remember that this is as bad as they’re ever going to be. They’ll be better tomorrow, and they’ll be better the next day and the next.


But it is still very early days and the potential for AI is endless. There are those who are already using AI models, while in some environments people are effectively banned from using these tools. But at the end of the day, those holding out will pretty much have no option but to get on board. If your competitors are using AI, and they’re innovating 10 times as fast as you, it’s inevitable that you’re going to fall behind from a real-world business perspective. You’re certainly not going to be able to beat them, so, at some point, you’re going to have to join them.


At Bluegrass, we combine AI efficiency with our expertise to deliver the best digital solutions. To find out more about us, click here.


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