[{"data":1,"prerenderedAt":758},["ShallowReactive",2],{"/en-us/blog/gitlab-uses-anthropic-for-smart-safe-ai-assisted-code-generation":3,"navigation-en-us":38,"banner-en-us":464,"footer-en-us":481,"Kevin Chu":724,"next-steps-en-us":737,"footer-source-/en-us/blog/gitlab-uses-anthropic-for-smart-safe-ai-assisted-code-generation/":752},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"seo":8,"content":16,"config":27,"_id":31,"_type":32,"title":33,"_source":34,"_file":35,"_stem":36,"_extension":37},"/en-us/blog/gitlab-uses-anthropic-for-smart-safe-ai-assisted-code-generation","blog",false,"",{"title":9,"description":10,"ogTitle":9,"ogDescription":10,"noIndex":6,"ogImage":11,"ogUrl":12,"ogSiteName":13,"ogType":14,"canonicalUrls":12,"schema":15},"GitLab uses Anthropic for smart, safe AI-assisted code generation","Anthropic’s Claude AI model supports the delivery of helpful, trusted code in GitLab Duo Code Suggestions.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749669095/Blog/Hero%20Images/gitlabduo.png","https://about.gitlab.com/blog/gitlab-uses-anthropic-for-smart-safe-ai-assisted-code-generation","https://about.gitlab.com","article","\n                        {\n        \"@context\": \"https://schema.org\",\n        \"@type\": \"Article\",\n        \"headline\": \"GitLab uses Anthropic for smart, safe AI-assisted code generation\",\n        \"author\": [{\"@type\":\"Person\",\"name\":\"Kevin Chu\"}],\n        \"datePublished\": \"2024-01-16\",\n      }",{"title":9,"description":10,"authors":17,"heroImage":11,"date":19,"body":20,"category":21,"tags":22},[18],"Kevin Chu","2024-01-16","GitLab recently launched GitLab Duo Code Suggestions into general availability. Code Suggestions includes the ability to generate algorithms or code blocks directly within the developer's IDE, a capability that uses [Anthropic's](https://www.anthropic.com/) generative AI model, [Claude](https://www.anthropic.com/index/claude-2-1). Integrated into the GitLab Duo portfolio of AI-assisted features, Claude is compatible with GitLab’s principles of [transparency and privacy](https://about.gitlab.com/the-source/ai/building-a-transparency-first-ai-strategy-7-questions-to-ask-your-devops/) by design and provides a high-integrity foundation for code generation.\n\nIn this post, you'll learn the advantages of code generation and how GitLab, together with Anthropic, is leveraging AI to responsibly boost developer productivity.\n\n## How AI-assisted code generation works\n\nCode Suggestions is incredibly useful as a coding companion that shows the suggestions as a developer types. It helps save developer time and keystrokes, reducing the effort for rote tasks and giving developers time back in their day. But what if a developer wants to do even more with generative AI?\n\nEnter code generation.\n\nImagine needing to write a new complex function based on an unfamiliar algorithm, or write a large amount of boilerplate code. Instead of struggling through these tasks with gritted teeth, code generation allows developers to simply define what they want to do in comments or multi-line comment blocks, and then Code Suggestions generates the code from there.\n\nHere is an example of Code Suggestions generating a JavaScript function that calculates the Levenshtein distance, a string metric useful for comparing the difference between two sequences:\n\n\u003Cimg src=\"https://res.cloudinary.com/about-gitlab-com/image/upload/v1752175962/Blog/lkrk16unp4dcy3c4zwvw.gif\" alt=\"Code Suggestions generating JavaScript function\" width=\"100%\" height=\"auto\">\n\nHere is another example showing a multi-line comment in Python. We want Code Suggestions to generate a Tornado Web Server that does three things: log in, run a scan, and review the results. By providing the specific instructions, including details such as the framework and the components to use,, Code Suggestions was able to generate a Tornado App, despite this author being unfamiliar with Tornado.\n\n\u003Cimg src=\"https://res.cloudinary.com/about-gitlab-com/image/upload/v1752175967/Blog/pxcdppnpzwfhgopxh999.gif\" alt=\"Code Suggestions generating Tornado app\" width=\"100%\" height=\"auto\">\n\nSafety through focus and trustworthiness\nDevelopers expect AI coding assistants to not only be helpful, but also accurate and safe. The system should generate precisely what is asked for while limiting deviation and [hallucination](https://www.ibm.com/topics/ai-hallucinations). Customers want assurances that AI-generated code can be trusted.\n\nThroughout GitLab's evaluation of certain code generation models, Claude stood out for its ability to mitigate distracting, unsafe, or deceptive behaviors. Claude also demonstrated consistent and accurate code generation throughout our testing.\n\nGitLab's use of Anthropic's Claude enables Code Suggestions to balance automation with trust. Code Suggestions helps users become more efficient without sacrificing reliability — a win for augmented development.\n\n## What’s next\n\nReady to experience the future of code generation? 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