How AI-assisted code suggestions will advance DevSecOps

Mar 23, 2023 · 5 min read
Neha Khalwadekar GitLab profile

This blog post is part of an ongoing series about GitLab's journey to build and integrate AI/ML into our DevSecOps platform. The series starts here: What the ML is up with DevSecOps and AI?. Throughout the series, we'll feature blogs from our product, engineering, and UX teams to showcase how we're infusing AI/ML into GitLab.

Artificial intelligence (AI) and machine learning (ML) have made incredible technological strides and are now poised to impact the software development process. As we can see, AI code suggestion proposals have already had a tremendous influence in helping programmers reduce repetitive tasks. AI-assisted code suggestions will enable developers to speed up coding, debugging, refactoring, documentation, and many more tasks, greatly enhancing the software development lifecycle (SDLC).

Trends adopting AI/ML from GitLab's DevSecOps Survey

What are suggestions for AI-assisted code?

ML techniques are used in AI-assisted code suggestions to assess code and recommend improvements. These recommendations involve modifying the syntax, streamlining the organization of the code, or suggesting more effective methods. By lowering errors, increasing effectiveness, and providing optimization advice, the aim is to assist developers in writing better code faster.

Animated gif image of code suggestions

How can AI-assisted code suggestions help?

AI-assisted code suggestions can substantially improve the programming experience by reducing errors and helping programmers write code faster, which will help reproduce the much higher production code quality.

Here are some of those SDLC improvements:

GitLab’s competitive advantages

GitLab’s unified DevSecOps platform enables businesses to deliver software more quickly and efficiently while enhancing security and compliance and maximizing the total return of investment on software development. We anticipate GitLab AI Assisted Code Suggestions will extend and amplify these benefits to improve developer productivity, focus, and innovation without context switching and within a single DevSecOps platform using the GitLab Workflow VS Code extension to get code suggestions as they type. Depending on the user prompts, the extension provides entire code snippets like generating functions or completing the current line. Simply pressing the tab key enables you to accept the suggestions.

As AI technologies advance in sophistication, they will provide more individualized and nuanced ideas, increasing their value to programmers.

The low-code/no-code development sectors are where AI-assisted code suggestions are anticipated to have substantial impact. As these development platforms spread, we envision bringing AI-powered tools that can offer recommendations and optimizations to simplify the software creation and deployment process for non-technical users on

The following are some of the critical jobs we intend to address for our customers with AI Assisted Code Suggestions in the DevSecOps Platform:

GitLab’s AI Assisted Code Suggestions are available to select Ultimate customers in a closed beta. For early access consideration, Ultimate customers can submit this form. We’re working towards a wider open beta of this capability in the next few months.

Continue reading our ongoing series, "AI/ML in DevSecOps".

Disclaimer: This blog contains information related to upcoming products, features, and functionality. It is important to note that the information in this blog post is for informational purposes only. Please do not rely on this information for purchasing or planning purposes. As with all projects, the items mentioned in this blog and linked pages are subject to change or delay. The development, release, and timing of any products, features, or functionality remain at the sole discretion of GitLab.

“AI-assisted code suggestions will improve the software development lifecycle. Find out how in part two of our ongoing series about the future of AI/ML in DevSecOps.” – Neha Khalwadekar

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