What's new?
For Tabnine's private installation release notes, click here.
Dec 17, 2024
Introducing Provenance and Attribution: Minimize IP liability for GenAI output
State-of-the-art LLMs like Claude 3.5 Sonnet and GPT-4o are trained on vast amounts of data, including code that may have restrictions on how it can be used, introducing the risk of IP infringement. Since the copyright law for the use of AI-generated content is still unsettled, engineering teams at enterprises want to strike a balance: leveraging the performance gains that come from these powerful models while minimizing the likelihood of copyleft-licensed code getting in their codebase. To support these goals, Tabnine is thrilled to announce Provenance and Attribution, a new feature that can drastically reduce the risk of IP infringement when using models like Anthropic’s Claude, OpenAI’s GPT-4o, and Cohere’s Command R+ for software development. Tabnine now checks the code generated within our AI chat against the publicly visible code on GitHub, flags any matches it finds, and references the source repository and its license type. This critical information makes it easier to review code suggestions and decide if they meet your specific requirements and policies.
October 29, 2024
Code Review Agent: Improve your code's quality, security and compliance
We’re proud to introduce Tabnine’s Code Review Agent — a first-of-its-kind AI software validation agent that enables organizations to produce higher quality, more secure code by leveraging and enforcing any given team’s unique best practices and standards for software development. The Code Review Agent checks the code in pull requests and IDE against rules that align with your unique standards. If the code doesn’t conform with your rules, then the agent flags the deviations and provides guidance and suggested edits to fix the issues.
September 24, 2024
AI agents to implement and validate Jira issues
Now with just a single click, Tabnine can implement a Jira issue, generating code from the requirements outlined in those issues. In addition to generating code for issues, you can also use Tabnine to validate code and review your implementation. The Jira Validation Agent will verify that your code accurately captures the requirements outlined in the Jira issue, offering guidance and code suggestions if it doesn’t.
As the first AI code assistant to offer an integration with Atlassian Jira, Tabnine enables you to accomplish macro-level tasks with a single click. You can directly ask Tabnine to implement a story, bug, task, or subtask — there’s no need to decipher requirements in a Jira issue, break it down into tasks, and feed specific prompts into an AI chat window.
With the launch of these new agents, Tabnine now leverages the text in Jira issues title and description as context as you work on a project. Additionally Tabnine continues to leverage locally available code and data in the developer’s IDE as context for personalized recommendations.
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