Will AI lead the charge and leave engineering managers behind?
A look into Tech’s next revolution and what it might mean for engineering managers
Artificial Intelligence (AI) is becoming increasingly prevalent in the workplace and has the potential to disrupt many roles, including engineering management. Over the past decade, we had seen AI replacing repetitive tasks in all industries. For examples, self-serve checkouts replace human cashiers in the retail industry. In the tech industry, AI is increasingly being used to automate data entry tasks, such as scanning documents, extracting data, and entering it into a database. For many industries, chatbots and virtual assistants are now used to provide customer service support, including answering customer inquiries, processing orders, and resolving common issues.
Therefore, the question that many people are asking now in 2023 with tech layoffs and big tech companies like Facebook and Salesforce announcing the reduction of their front-line engineering managers is that would AI eventually replace engineering managers entirely. In this article, I will explore the potential for AI to replace engineering managers.
The measures of success for engineering managers
“What Do Engineering Managers Do?”, is a very popular question for software engineers and even for engineering managers themselves. You will see thousands of articles, videos and blog posts on this topic, mine included. This goes to show that engineering manager role is complex, diverse and involves a range of responsibilities.
To know what engineering managers are expected to do, it’s important to understand how the success of an engineering manager is measured.
The success of an engineering manager is measured across three dimensions:
- Value shipped to customers. Usually in the form of features that customers can use to help them achieve their goals such as an ability to search for a particular product at an e-commerce store or an ability to track your personal expenses.
- Reliability of the underlying services. Platform reliability is often neglected because the work done on reliability is not easily visible like…