Developing High-performance Engineering Teams: a Practical Framework for Mentorship and Technical Growth
Type: article
Abstract: This study analyzes mechanisms for forming high-performing teams based on a synthesis of empirical data from DORA 2024 reports, Gartner and McKinsey analytics, as well as a corpus of IEEE/ACM academic works. The purpose of the study is to formulate the Integrated Technical Growth Framework (ITGF), which conceptually and practically links operational DevOps metrics with institutionalized mentoring practices and hiring for growth strategies. The working hypothesis posits that, under conditions of automation of routine programming, the critical predictor of organizational resilience is not the nominal speed of code production, but the effectiveness of tacit knowledge transfer through formalized mentoring mechanisms and internal developer platforms (IDP). Analytical data processing demonstrates that companies that build hiring practices on candidate potential and reinforce them with structured mentoring achieve 1.9 times higher aggregate productivity and increase key employee retention metrics by approximately 50%. The study proposes an applied model for retuning onboarding processes and the architecture of technical leadership aimed at reducing the risks of the AI productivity paradox and ensuring the continuity of expert knowledge under conditions of transformation of the role of Junior developers.
Source: CyberLeninK (CyberLeninka)
Author: Lvov Evgenii
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7165242372