New technologies, such as GPT Chat, help optimize processes and increase work efficiency
With the emergence of new technologies, many segments have adopted Artificial Intelligence tools to optimize work processes, improving productivity and efficiency. According to Gartner research, 45% of companies are increasing investments in Generative Artificial Intelligence.
In this survey, software development is the function with the highest rate of technology adoption or investment, followed by marketing and customer service areas.
Given this context, the BossaBoxa startup that assigns and manages technology professionals for enterprises and scale-ups, shows how this type of tool can help team productivity in other industries, as it already helps teams in product and technology projects.
Currently, artificial intelligence is used as an assistant tool in product launch processes, since thanks to its implementation in management, technology managers now have a broader and more diverse view of the team’s performance, but without neglecting the workforce of the teams.
“To use this tool, the most important work is human. If there is no good management of the data and how it is stored, it is difficult to add a level of artificial intelligence and obtain important insights that have a positive impact on the business,” explains Gustavo Bassan, Head of Engineering at BossaBox.
Team management
When it comes to team management, this type of technology can be an ally for product leaders to have a more assertive view of technological capabilities by looking, for example, at Dora Metrics, a set of metrics that aims to measure the performance of the software team. engineering in agile development environments, or for Developer Experience (DX), solutions provided as support to improve the developer’s experience in using development tools.
With search analytics, AI can also automate repetitive and routine tasks in the segment, freeing up more time for managers to focus on more strategic tasks. This can include automating product development workflows, project management and data analytics.
For developers, these tools help in the pull request analysis process, where you can review and discuss the set of proposed changes before integrating them into the main code base. You can also use these AI agents to help with specific tasks via LangChain, which is an open source framework for developing applications using large language models.
“Today in our management dashboard we aim to prioritize issues to have a holistic view of engineering and products. This is possible because we work to impute all data in a centralized and normalized way, after having a layer of analysis and AI agents that constantly verify this information,” highlights Bassan.
With all these changes, product and technology professionals must be prepared to implement AI tools, providing valuable insights, automating processes, personalizing experiences, and improving decision-making at all stages of the product lifecycle, the which will bring benefits to all those involved in the process. processes. However, what cannot be ruled out is the importance of the employees involved in each high-performance team to the final outcome of the project.
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Source: Terra
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