
Best AI Coding Assistants 2025: GitHub Copilot, Cursor, and tools changing programming. Are developers being replaced? Job market impact.
Which brand leads in AI visibility and mentions.
Brands most often recommended by AI models
Top Choice
Models Agree
Overall ranking based on AI brand mentions
Rank #1
Total Analyzed Answers
Recent shifts in AI model responses
Rising Star
Growth Rate
Analysis of brand presence in AI-generated responses.
Brands ranked by share of AI mentions in answers
Visibility share trends over time across compared brands
Key insights from AI Apps comparisons across major topics
Full IDE assistance AI is generally favored over standalone code completion tools due to its broader functionality and integration, though user preferences for lightweight solutions remain relevant.
ChatGPT shows a slight preference for full IDE assistance with higher visibility for tools like Cursor (7%) and JetBrains (4.6%), which are associated with comprehensive development environments. Its sentiment tone is neutral-positive, reflecting a balanced view but emphasizing integrated solutions for productivity.
Deepseek appears neutral with no strong favoritism, giving comparable visibility to both standalone code completion tools like Tabnine (2.4%) and full IDE platforms like JetBrains (2.7%) and VS Code (2.7%). Its sentiment tone is neutral, focusing on versatility across user needs without clear bias.
Gemini leans toward full IDE assistance with higher visibility for Cursor (2.6%) and JetBrains (2.4%), suggesting a preference for tools offering deeper ecosystem support. Its sentiment tone is positive, valuing the comprehensive user experience these platforms provide.
Grok favors full IDE assistance, evident from higher visibility shares for Cursor (2.1%), JetBrains (2.1%), and VS Code (2.2%), which provide robust development environments over pure code completion tools. Its sentiment tone is positive, focusing on the practicality of integrated systems.
Perplexity slightly prefers full IDE assistance, with Cursor (2.6%) and JetBrains (2.6%) dominating visibility over standalone tools like Tabnine (1.8%). Its sentiment tone is neutral-positive, acknowledging the utility of broader assistance while recognizing niche use cases for code completion.
GitHub Copilot holds a slight edge over Cursor based on model visibility data and implied ecosystem integration, though neither is overwhelmingly favored across all models.
GitHub Copilot (under GitHub) has a visibility share of 2.7%, matching Cursor's share at 2.7%, indicating no clear preference, but GitHub's broader ecosystem association suggests a slight lean toward Copilot. Sentiment tone is neutral, focusing on visibility without explicit qualitative judgment.
GitHub Copilot (via GitHub) dominates with a 9.4% visibility share, while Cursor is not mentioned, signaling a strong preference for Copilot likely due to its integration with widely adopted tools like VS Code (also at 9.4%). Sentiment tone is positive toward Copilot, driven by high visibility and ecosystem relevance.
GitHub Copilot (under GitHub) and Cursor both share 2.7% visibility, showing no distinct favoritism, with focus split evenly across coding tools like VS Code. Sentiment tone is neutral, lacking deeper qualitative reasoning for either tool.
GitHub Copilot (via GitHub) edges out slightly with a 2.9% visibility share compared to Cursor's 2.7%, hinting at a marginal preference possibly tied to GitHub's established developer community. Sentiment tone is neutral to slightly positive for Copilot, reflecting subtle visibility dominance.
GitHub Copilot is explicitly mentioned with a 0.2% visibility share alongside GitHub at 2.7%, matching Cursor's 2.7%, but Copilot's direct reference may indicate a focused recognition over Cursor. Sentiment tone is neutral, with no strong qualitative bias toward either tool.
Tabnine emerges as the leading AI coding assistant for ROI based on consistent visibility across models and perceived value in productivity, while GitHub and Cursor also show strong potential depending on user ecosystem preferences.
Gemini shows a slight preference for GitHub (2.7% visibility share) and Tabnine (2.4%) over others like Cursor (2.4%) and ChatGPT (2.1%), likely due to their established ecosystems and integration capabilities, with a neutral tone reflecting balanced recognition of multiple tools.
Deepseek favors GitHub (3% visibility share) and AWS (2.7%) for their robust developer ecosystems and scalability, presenting a positive tone towards tools with wide adoption and integration potential for better ROI.
Perplexity equally prioritizes GitHub, Tabnine, and Cursor (each at 2.9% visibility share), emphasizing their relevance in coding efficiency with a positive tone, suggesting strong user accessibility and productivity value.
ChatGPT strongly favors GitHub (10.1% visibility share) and Tabnine (9.8%) for their comprehensive features and community support, adopting a positive tone that highlights superior ROI through user adoption and ecosystem strength.
Grok leans towards GitHub, Tabnine, and ChatGPT (each at 2.9% visibility share), focusing on their innovation and utility in coding workflows, with a neutral-to-positive tone indicating balanced value for cost.
Google shows minimal engagement with AI coding assistants, with no clear favorite (all at 0.2% visibility share including GitHub and JetBrains), maintaining a neutral tone and limited relevance to ROI assessment due to low focus on specific tools.
GitHub emerges as the leading AI coding tool for both junior and senior developers due to its consistently high visibility across models and strong ecosystem support.
GitHub dominates with an 8% visibility share, reflecting strong recognition and trust for developers at all levels. Its sentiment tone is positive, likely due to its comprehensive features and community support, making it ideal for both junior and senior developers.
GitHub leads with a 3% visibility share, though the model’s focus is narrower compared to others. The sentiment tone is neutral, emphasizing GitHub’s utility but lacking depth on accessibility for junior versus senior developers.
GitHub and AWS both hold a 2.7% visibility share, indicating balanced recognition, with a positive sentiment tone for tools supporting scalable development. The model perceives GitHub as versatile for both junior learning and senior complex projects.
GitHub stands out with a 2.4% visibility share, with a positive sentiment tone focused on its ecosystem integration, suitable for seniors, though VS Code (1.4%) may appeal more to juniors for accessibility. The model highlights GitHub’s robustness for all skill levels.
GitHub, VS Code, Tabnine, and Cursor each show strong visibility at around 1.9%, with a positive sentiment tone for user-friendly tools. The model suggests GitHub and VS Code cater well to both junior and senior developers due to their feature depth and ease of use.
GitHub emerges as the leading AI coding tool across models due to its consistently high visibility share and broad recognition as a versatile platform for various programming languages.
Grok favors GitHub with a notable visibility share of 2.7%, suggesting a preference for its collaborative and versatile ecosystem across programming languages. Its tone is positive, emphasizing GitHub’s role as a central hub for developers, while also acknowledging JetBrains (2.4%) for specific language support.
Deepseek also leans towards GitHub (2.6%) alongside Tabnine (2.6%), reflecting a balanced view of collaborative platforms and AI-driven code assistance for diverse languages. Its tone is neutral, focusing on functionality across tools like AWS (2.2%) for cloud-integrated coding.
ChatGPT strongly favors GitHub (9.8%) and Tabnine (9.3%) as top tools, highlighting their robust support for multiple languages and integration with environments like VS Code (7%). Its tone is highly positive, emphasizing user adoption and ecosystem strength for coding versatility.
Perplexity prioritizes GitHub (3%) and Cursor (2.9%), indicating a focus on accessibility and modern coding workflows across languages. Its tone is positive, valuing community-driven platforms and editor integrations like VS Code (2.2%) and JetBrains (2.4%).
Gemini highlights GitHub (2.6%) as a key player, alongside VS Code (1.9%) and JetBrains (1.8%), focusing on their adaptability to languages like Python and TypeScript. Its tone is neutral, emphasizing practical utility over specific AI tool dominance.
Key insights into your brand's market position, AI coverage, and topic leadership.
GitHub Copilot (Microsoft/OpenAI) and Cursor are the top two. Copilot integrates into VS Code, costs $10/month ($100/year), and is the most popular with 1M+ paid users. It's great for autocomplete and generating simple functions. Cursor is a full IDE built around AI - it can understand entire codebases, refactor large files, and chat about your code. Cursor costs $20/month and is preferred by serious developers for complex projects. Other contenders: Tabnine (privacy-focused), Codeium (free), Amazon CodeWhisperer, and Replit Ghostwriter. Most developers use multiple tools.
Junior developers are getting crushed, senior developers are becoming more productive. The harsh reality: entry-level coding jobs have disappeared. Companies that used to hire junior devs for basic tasks now use AI. Bootcamp graduates can't find jobs because AI writes the code they would have written. However, senior developers who use AI are 2-5x more productive - they focus on architecture and problem-solving while AI handles boilerplate. The market is splitting: AI made mediocre coders obsolete while making great developers superhuman. If you're learning to code now, you must be AI-native from day one or you're competing with free AI that works 24/7.
AI can write decent code for common tasks but struggles with complex architecture, security, and edge cases. Copilot is amazing for boilerplate, CRUD operations, and standard algorithms. It fails at: novel algorithms, optimizing performance, understanding business logic, security considerations, and debugging complex issues. The code AI generates often works but isn't maintainable or scalable. Real-world experience: AI writes code that passes tests but has subtle bugs discovered months later. Senior developers use AI to speed up routine tasks but review everything carefully. Shipping AI-generated code without human oversight is asking for disasters.
Yes, but differently than before. Don't just learn syntax - AI handles that. Learn: problem decomposition, system design, debugging, understanding business requirements, and judging code quality. Use AI from day one but understand what the AI generates. The dangerous path: copying AI code without understanding it. You become dependent and can't solve problems when AI fails. The smart path: use AI to speed up learning by generating examples, but always understand the logic. Companies want developers who can architect solutions and work with AI tools, not developers who just copy-paste AI output. The bar is higher now: you need to be good enough that AI enhances you rather than replaces you.
It's a tool, like StackOverflow was - but way more powerful. The debate: purists say learning with AI creates developers who can't code without help. Pragmatists say refusing AI is like refusing Google. The truth is nuanced: using AI to learn faster is smart. Using AI to avoid learning is career suicide. For students: use AI to understand concepts and see implementations, but code solutions yourself to build muscle memory. For professionals: use AI aggressively to ship faster. The industry moved on - companies expect you to use AI tools. Interviews are getting harder because AI raised the baseline. Everyone can write basic code now, so you need to be exceptional at higher-level skills.