As technology catapults us into a reality where GenAI's role in information retrieval, conversation, and task automation sets unprecedented standards, software development is undergoing a phenomenal transformation.
Yet, amidst the buzz and promise a crucial question arises: how do we ensure that GenAI operates at its zenith and delivers on its transformative potential?
With GenAI benchmarking.
As software development transcends syntax to embrace intent, GenAI benchmarking can become the North Star navigating us towards a future where innovation thrives, and human ingenuity reigns supreme.
In this point of view, we share valuable information from Xoriant’s benchmarking analysis where we measured the impact of GenAI across the software development lifecycle improving functionality readiness, code quality, and overall team productivity.
Key takeaways from the point of view
Methodology used for analysis
Comparing efficiency and productivity of software engineering groups using GenAI tools vs. traditional methods
Benchmarking execution and evaluation
Ensuring meticulous execution with daily monitoring, interventions, and detailed evaluations across different engineering tasks
Specific observations for code generation
Revealing how GenAI may address challenges inherent to various stages of the software development lifecycle
Quantified impact of GenAI on SDLC
Realizing three impactful metrics on GenAI usage: functionality readiness, software quality improvement, and productivity
