AI efficiency at Devōt: Different perspectives on using AI for work productivity
We keep seeing how jobs adapt and change. In the technological world, where adaptability is the only constant, artificial intelligence (AI), mainly machine learning models, plays a major role in changing business.
And no, this isn't another bombastic article about AI replacing human labor. Instead, we'll see how, through the application of generative AI, we can work on our version of "Subtractive Productivity." In our company, the use of AI varies depending on the role, but most of us started to use AI after the boom of ChatGPT.
Developer perspective - AI enables a smooth transition between learning new technologies
Our Tech Lead, Marko Meić Sidić, regularly uses AI tools like Copilot in his IDE. Copilot significantly speeds up writing boilerplate code and offers suggestions for refactoring and generating unit tests. Marko particularly highlights that AI saves him time with education or when transitioning from one programming language to another. After more than five years of working in Ruby on Rails, last year, he started programming in Java and the Spring framework, where AI significantly accelerated his adaptation and enabled a smooth transition to another language.
While AI helps speed up the process, Marko emphasizes that his approach to problem-solving remains similar because AI still requires human input. He highlights the importance of properly formulating queries in AI tools: better context and higher-quality data result in better responses. If adequate context is missing, AI can actually make the process worse, as you spend more time arguing with it than solving the problem.
Marko also adds: "I always try to come up with solutions myself, but that certainly includes a combination of official documentation and then AI. AI can definitely speed up the process, but it's always necessary to verify the solution AI proposes. Regardless of the speed of progress of AI technologies, they must continuously align with rapidly developing technological standards."
Despite AI's help, Marko emphasizes that Code Reviews by other developers and work by QA engineers are still essential. AI cannot fully replace thorough quality checks and manual testing, which are crucial for maintaining high software development standards.
QA perspective - Artificial intelligence cannot replace critical thinking
QA Leo Cvijanović uses AI in his job, especially for writing automated tests. In addition to ChatGPT, he also uses GitHub Copilot, which he finds extremely useful due to its integration into the code editor. Copilot has the ability to use existing code within the project or repository to help create new code.
Copilot allows him to simply describe what he wants to achieve, enter the necessary variables and parameters, and then the tool takes care of the syntax of the code. This automation allows him to focus more on the more complex aspects of the QA process.
Despite the advantages that AI systems offer, he believes that the QA position is still just as necessary. Regardless of the advancement of AI technologies, the code must undergo a detailed code review before reaching the QA phase, where human intervention is necessary for the final check. Leo believes that AI, no matter how advanced, will never be perfect and cannot completely replace the critical review and analysis provided by the human factor. Therefore, while AI can significantly improve the efficiency of processes, it is important to remain cautious and not rely solely on technology.
Designer perspective - AI is never the ultimate solution, but a help on the way to the solution
Our designer, Tisa Bastijanić, uses AI technologies to expand and generate images in Photoshop, while in her role as Product Owner of Devōt's website, she most often uses AI for writing User stories. Tisa points out that although AI significantly helps in the efficiency of her work, she never uses it as the final solution. For her, AI is a tool for support and quick access to information, serving as a help on the way to the solution, but not as a replacement for the creative process.
Tisa also emphasizes the importance of recognizing moments when it is better not to use AI. Due to various shortcomings, such as "hallucinating" answers or misunderstanding queries, using AI can result in spending more time than necessary, sometimes making manual work faster and more efficient.
In the world of design, AI-generated images, from portraits of human faces to scenic elements, often contain illogical things or photos look just "too perfect." So far, Tisa has not used any images or graphics created by AI in her projects. Often, illustrations are easier and faster to find via the internet than to correct AI-generated illustrations. However, she believes that the quality of AI tools will greatly improve in the future.
The perspective of a Talent Acquisition Specialist - Today, there is even greater emphasis on technical interviews
Lina Višić, a Talent Acquisition Specialist at Devōt, uses AI most to enhance the recruitment process. AI helps her in various aspects, including writing procedures, defining job descriptions, generating interview questions, and structuring meetings. She particularly highlights the usefulness of AI when she lacks ideas for new content.
Lina believes that the quality of job applications has always varied; there have always been poor and good resumes. Previously, candidates often used the first available templates from the internet, while today standards are becoming somewhat higher. However, it is easy to notice which resumes are generated without additional processing and adaptation.
A major change in the hiring process for technical staff is extra emphasis on verifying technical knowledge. Given AI's capabilities, such as ChatGPT, there is a risk that candidates will submit codes generated using AI without a deeper understanding. At Devōt, we solve this problem by conducting thorough technical interviews that test not only the accuracy of the code but also the candidate's understanding of the methods of using AI for professional purposes.
Although Lina acknowledges that AI can sometimes slow down the process due to the time required to formulate effective queries, she believes that AI has significantly helped increase the efficiency of performing business tasks that are otherwise not her favorite (and yes, we are talking about writing down some boring procedures).
So, how does AI increase efficiency in operational work?
Read more about it on our blog
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