Beyond Model Selection: True Architectural Freedom for Enterprise AI Software Development
February 21, 2025
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4 -min read
Learn how Tabnine is transforming enterprise AI development with expanded LLM support, including Llama 3.3 and Qwen 2.5, plus a game-changing capability that lets you integrate any LLM of your choice.
Generic AI code assistants are failing enterprise teams - it's time for a new approach
February 19, 2025
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6 -min read
Research continues to highlight persistent accuracy, security, and maintainability issues in code generated by generic AI assistants.
Unboxing Schrödinger’s Dataset: The real level of IP risk in AI generated code
February 10, 2025
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5 -min read
This article takes a deep dive into the true level of IP risk associated with AI-generated code, leveraging recent research from Carnegie Mellon University to separate fact from fiction.
Control every interaction: Introducing Tabnine’s new personalization features
February 6, 2025
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5 -min read
For AI to drive meaningful impact it must deliver recommendations that are tailored to each team’s specific practices and preferences.
Even high-quality code can lead to tech debt
February 4, 2025
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< 1 -min read
Eran Yahav, Tabnine's CTO and co-founder, spoke with Stack Overflow about software development and AI.…
December Changelog
January 23, 2025
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4 -min read
Tabnine's December updates reflect our focus on making AI a more pragmatic, secure, and customizable part of your development workflow.
Getting the most from GenAI through personalization
January 23, 2025
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2 -min read
Our Personalizing AI coding assistants to your organization guide explores how to effectively "onboard" Tabnine into your organization.
Measuring the Impact of AI Coding Assistants
January 23, 2025
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2 -min read
This report aggregates and analyzes the most significant research available on AI code assistants and provides a simple, logical framework for you to calculate the value for your team.
AI Code Assistant Buyer’s Guide
January 23, 2025
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2 -min read
Tabnine's AI Code Assistants Buyer's Guide helps engineering leaders through the critical considerations for choosing and adopting AI code generation technology.
