Welcome to the ever-evolving and incredibly fast-paced landscape of software development, where developers are on a constant quest for tools that enable them to supercharge their ability to deliver applications quickly and with utmost precision.
Throughout the years, nothing has revolutionized the way developers approach their work more than the recent arrival of the developer's holy grail: AI.
At Yeti, we've been experimenting with an abundance of tools powered by AI - and have found that this groundbreaking technology has enabled us to streamline our processes, boost productivity, and unlock new levels of innovation - completely transforming the the way we build exceptional products.
With AI as a trusted coding companion, our developers have begun to bid farewell to the mundane and repetitive tasks that often hinder the development process, and instead focus their energy on innovation and building next level applications - in a fraction of the time.
One prominent AI use case is code generation and autocompletion. AI-powered code editor tools, such as Tabnine, and Github CoPilot have improved the coding experience by using advanced machine learning algorithms to suggest code snippets, provide autocompletion, and assist developers in writing code. These tools analyze code patterns, understand context, and offer intelligent recommendations that significantly enhance productivity and reduce coding errors.
By harnessing the power of AI as their coding companion, developers can focus on solving complex problems and building innovative solutions with greater speed and accuracy. With its ability to code so intelligently and so quickly, AI tools remove much of the redundant work developers face day to day.
Detecting and fixing bugs is an essential part of the software development process, and AI-driven platforms have emerged to provide valuable support in this area. One such platform is DeepCode , which utilizes advanced algorithms to analyze codebases and detect potential bugs. By leveraging the power of AI, DeepCode goes beyond traditional static analysis and provides developers with actionable recommendations for improvement. The platform uses machine learning techniques to identify patterns, compare code with known bug patterns, and highlight potential vulnerabilities that might otherwise go unnoticed. With the help of DeepCode, developers can proactively identify and address bugs, leading to enhanced code quality and more reliable applications.
AI platforms like DeepCode not only help you locate bugs while you're writing code - it also has the ability to write tests that run every time a pull request is made - and will alert you if the test fails - ensuring that critical parts of the code are covered by tests. This allows devs to stay focused on building all the cool features clients love, while AI quickly creates tests for ensuring that code continues to work in perpetuity.
In addition to bug detection, AI-driven platforms like DeepCode continuously learn from user feedback and code patterns to improve their detection accuracy over time. As developers interact with the platform and provide feedback on the identified issues, DeepCode's AI algorithms adapt and refine their analysis, becoming more effective at identifying bugs specific to the project's context. This iterative learning process enhances the platform's ability to provide relevant and actionable recommendations, enabling developers to make informed decisions and produce higher-quality code.
Keeping up with multiple projects and understanding complex codebases can be a daunting task for developers. Luckily, AI-driven code explanation tools like Cody AI are revolutionizing the way developers understand and navigate complex codebases, with their ability to analyze and interpret code snippets or entire files, offering high-level explanations of their function.
When using Cody AI, developers can simply highlight a piece of code or a file and prompt the assistant to explain what is occurring within it. Leveraging its vast knowledge base, Cody meticulously searches through the code and relevant files to gather contextual information.
Once the analysis is complete, it generates a comprehensive answer that elucidates the code's overall purpose and functionality. This capability proves particularly beneficial for developers transitioning between different projects, as it helps them quickly grasp the inner workings of unfamiliar codebases, minimizing the learning curve and enabling smoother onboarding experiences.
Previously, developers would have to invest considerable time and effort in manually studying complex codebases, deciphering intricate algorithms, and understanding the underlying logic. With AI, these challenges are significantly mitigated, as it efficiently summarizes the code's essence, allowing developers to rapidly familiarize themselves with its key components. As a result, developers can seamlessly transition between projects, accelerating the development cycle and reducing time wasted on unnecessary trial and error.
One of the ways the Yeti developers have leveraged ChatGPT is by using it as a development mentor. It serves as a virtual guide that can answer questions about various tech stacks, programming languages, and computer science concepts. When faced with a technical hurdle or a lack of clarity, developers can turn to ChatGPT to gain insights and receive explanations that help them move forward with confidence.
Developers can use ChatGpt for code review by running their code through the platform and prompting it to provide feedback and suggestions for improvement. Though completing manual reviews is still necessary, developers are saved the trouble of code reviewers pointing out minor flaws or obvious mistakes, by allowing AI to review their code first, saving significant time and effort.
The feedback received from ChatGPT can help identify potential issues and improve code readability, leading to more robust and maintainable software.
ChatGPT's capabilities extend beyond general development knowledge and code reviews. It can act as a highly personalized search engine, tailored to the specific needs of developers. Instead of resorting to generalized online searches, developers can directly ask ChatGPT for assistance in summarizing documentation and other online resources to answer their questions quickly.
By providing ChatGPT with detailed information about the project, desired functionality, and tech stack, developers can receive code snippets or guidance that precisely address their needs. This personalized approach saves time and delivers solutions that are customized to the project at hand, ensuring greater accuracy and efficiency.
ChatGPT is also very effective at helping debug issues in code. By prompting ChatGPT with sufficient context - including the code/error message - the tool will often be able to correctly identify the potential problem. Below is a step by step guide for using ChatGPT for debugging code issues:
Create a Prompt that includes:
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The recent wave of AI technology has had the Yeti team itching to experiment with the countless possibilities it presents - so we organized an AI hackathon that tasked teams with conceiving, designing, and developing an AI powered application… all within a single day. Take a look at what we built!
At Yeti, we’ve been experimenting with AI tools since they first landed on the tech scene, and have seen firsthand just how much productivity levels soar when AI is utilized throughout our processes. Join us as we explore how AI is reshaping project management practices in the tech industry!