AI tools that help throughout the development process.
섹션 링크 공유Coding Agents/Assistants Experience & Sentiment
Coding Agents/Assistants Experience & Sentiment
Once again Claude shows a clear lead over the competition in terms of positive sentiment, with Claude Code topping the rankings even if GitHub Copilot technically has a larger user base.
Group by:
Sort by:
Experience
- <span aria-hidden="true">🤓</span> 사용해 본 적 있음: Respondents who have used an item.
- <span aria-hidden="true">👀</span> 들어본 적 있음: Respondents who have heard about an item, but haven't used it.
- <span aria-hidden="true">🤷</span> 들어본 적 없음: Respondents who have never heard about an item.
Sentiment
- Positive: Respondents who are interested in learning more about a technology; or are willing to use it again.
- Neutral: Responents who did not indicate any sentiment about a technology.
- Negative: Respondents who are not interested in learning more about a technology; or have used it and had a negative experience.
섹션 링크 공유Coding Agents & Assistants Ratios Over Time
Coding Agents & Assistants Ratios Over Time
Claude Code and OpenAI Codex are neck-and-neck in terms of respondent satisfaction, but the Anthropic coding tool is actually used way more than its rival.
섹션 링크 공유Other Coding Agents/Assistants
Other Coding Agents/Assistants
Given its popularity, OpenCode should probably have been part of the main survey options. But it makes up for that omission by establishing a comfortable lead over the competition here, with Cursor a close second.
What other coding agents or assistants are you currently using?
(자유 형식 질문)
Multiple
섹션 링크 공유Number of Items
Number of Items
How many items in this category respondents have used.
섹션 링크 공유Paid Usage
Paid Usage
Echoing results from the Models section, Claude Code also comes in first when it comes which coding assistants developers are willing to open their wallets for.
Out of the agents & assistants mentioned here, which one do you or your company actually pay for?
Multiple
섹션 링크 공유추천하는 리소스
추천하는 리소스
AI Engineering Fundamentals
Add an agentic chat interface to an existing application. Then establish a rigorous eval harness to systematically improve the agent through context engineering, advanced tool use, RAG, and reliable production feedback loops.
AI Agents Fundamentals, v2
Learn the foundations of agent development like tool calling, agent loops, and and evals. Add human-in-the-loop approvals for higher-stakes operations.
우리를 지원해 준 파트너들께 감사 드립니다! 더 알아보기.