Building a smarter AI code assistant for 2025 (and beyond)
Since launching our AI code assistant in 2018, we’ve learned a lot about what developers and organizations value most, namely privacy and confidentiality, hyperpersonalized results, and deployment flexibility. But that only scratches the surface of an increasingly popular but complex and still developing technology. This article from The New Stack looks at the current state of the industry, examines the challenges enterprises often face when adopting AI, and previews what’s still to come as AI continues to improve the developer experience.
//Around Tabnine//
Enterprise engineering teams using LLMs in their AI code assistants need to strike a balance: maintaining the productivity gains from these LLMs while minimizing the likelihood of copyleft-licensed code getting into their codebase. Tabnine’s new Provenance and Attribution feature 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 — drastically reducing the risk of IP infringement.
Join us for a Tabnine Live demo on January 9 to see how this new feature can help your team.
Las Vegas is made for memories, and we have plenty from AWS re:Invent. Beyond the AI buzz, we felt a lot of electricity at the Tabnine booth from talking with attendees. And time and again, there were a few key reasons they were excited about Tabnine, including our model flexibility, data privacy, IP protection, and personalization features. Here are our takeaways from the week.
We recently hosted a webinar with Carahsoft aimed at helping teams unlock the potential of GenAI without sacrificing security. Watch and learn how to keep your code private with air-gapped and VPC deployment options, explore tailored AI models designed to meet the unique needs of large organizations, boost productivity and enhance workflows with smarter coding tools, and maintain data integrity at scale.
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It can require an awful lot of time and patience to find and fix bugs and errors in a large, enterprise-grade application. And once you do find the issue, figuring out a suitable fix can be equally difficult — or trigger new issues that require additional changes. Enter: Tabnine’s Code Fix Agent, which helps developers fix errors and bugs within their code with the click of a button or a simple command.
We continued a busy end of the year in November, releasing major upgrades to our free AI code assistant, including access to more AI agents and advanced personalization features. We also added support for Jira Cloud for our Enterprise self-hosted customers, enabling smarter workflows and enhanced productivity, and made interacting with Tabnine AI Chat easier and more resourceful.
LLMs are the backbone of AI, and because they’re trained on vast datasets from across the internet to recognize, generate, and interpret human language, they’re useful for helping with simple tasks: chocolate cake recipes, canned email responses, making quick parodies of Kendrick Lamar songs. But using AI for software development requires something more robust than a generic LLM like ChatGPT. Here are five reasons why.
//Across the AI-verse//
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2 个月Thanks for sharing