G2

Md. Azharul I.

Software Engineer

Computer Software

Small-Business (50 or fewer emp.)

11/5/2026

"Unmatched AI Assistance with Intuitive IDE Integration and Massive ROI"

4.5/5

What do you like best about GitHub Copilot?

As a software engineer managing our BIAI-CRM project at Neuroxyte, the AI intelligence of GitHub Copilot is simply unmatched for architectural analysis. The UI and UX are incredibly intuitive, offering seamless integrations directly inside my IDE (VS Code) to analyze our Dockerfiles and Prisma scripts. From day one, the onboarding process was smooth, and their technical support documentation made it easy to set up. Most importantly, it drastically improves our coding performance and execution speed by automating repetitive boilerplate and identifying deployment risks. When calculating the engineering hours saved, the subscription pricing offers a massive ROI (Return on Investment) for our business. Review collected by and hosted on G2.com.

What do you dislike about GitHub Copilot?

While highly capable, GitHub Copilot occasionally struggles with deep context retention across massive multi-file workspaces. For instance, when working on complex Prisma schemas alongside specific Vercel deployment configurations for our CRM, it sometimes suggests deprecated library methods or loses track of custom types defined in adjacent directories. You have to be very precise with your prompts and manually steer the AI to ensure it adheres to the latest framework updates, which can briefly slow down your coding momentum. Review collected by and hosted on G2.com.

What problems is GitHub Copilot solving and how is that benefiting you?

Before adopting GitHub Copilot, our engineering team at Neuroxyte spent significant hours manually auditing pull requests for deployment vulnerabilities and writing repetitive boilerplate code for the BIAI-CRM. Copilot solves the bottleneck of manual code reviews by acting as an automated assistant that instantly flags architectural risks—like our Vercel storage configuration issues—directly inside VS Code. This has drastically accelerated our development velocity. I am saving approximately 10 to 15 hours a week on debugging and boilerplate generation, which directly translates to faster feature rollouts and highly secure, reliable deployments. Review collected by and hosted on G2.com.