ZDNET的关键外卖
- 整个是GitHub竞争对手，围绕编码agents而建。
- 该平台旨在消除编码瓶颈。
- AI-write代码改变了开发者花费的时间。
AI加快了编码速度，对基础设施提出了新的要求，并改变了开发者的工作方式。 Entire是前GitHubCEO托马斯·多姆克的开发商平台，旨在成为这些变化的解决方案。
另外：ServiceNow和Nvidia 发布 Arc，是企业的新AI agent.
该平台现今可供使用，基于Entire分散的Git网络宣布在7月建成，该平台旨在承受导致GitHub停电的AI编码活动的急剧增加。
更多来自 ZDNET
是什么使整个不同
标准编码经验的第一个变化是它用它所谓的拖拉机来取代拉动请求。
“与经典的用diff审查代码更改的Pull Request模型不同，Trails为开发者提供类似于航空公司飞行员的机头显示
Gartner的2027个技术趋势刚刚下降
" 所有数据不仅在Entire的网络界面上提供，而且通过开源全CLI提供。 这允许编码agents在循环中处理发现，而人类开发者则验证进度。 当所有 evals 都满意，他们可以合并代码而不需要查看代码本身。”
全部称，运行此过程的agents是自定义的，每个跟踪显示如何使用agents符号。
Dohmke 称将这个想法、agent的踪迹和开发商的会议结果作为一等文物，“它使用多个 agents 来生成验证 AI 生成代码的质量和成功率的 evals 来让开发者自信地合并，而不审查 diff 中的每一行。”
由于上述分散网络，该公司还提供Git托管服务，“比GitHub快达89x”，比Cursor源头快6倍。 该平台允许开发者在世界各地多个地点创建、迁移和托管私人储存库，目前从美国、印度、澳大利亚和欧盟开始。
PHP2Shell：还没有补齐吗？现在采取这些步骤来缓解
另一个区别因素是连续内存，它把repo中代码旁边的开发者会话日志作为数据源。 Agents可以使用它们来寻找答案，这，全称帮助它们使用多达71%的代币。 这与AI聊天器中的其他内存功能类似，这些功能通过利用过去的对话或其他agent交互，在提供时，缩短了收集上下文的时间，以加快查询响应时间。 称连续内存由密码基图和“代理脑”组成
全部可供今天所有开发者尝试。
本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
ZDNET’s key takeaways
- Entire is a GitHub rival built around coding agents.
- The platform is designed to remove coding bottlenecks.
- AI-written code has changed what developers spend time on.
AI has sped up the pace of coding, putting new demands on infrastructure and changing how developers work. Entire, a developer platform from former GitHub CEO Thomas Dohmke, aims to be the solution to those changes.
Also: ServiceNow and Nvidia launch Arc, a new AI agent for enterprise
The platform, available for use today, is built on Entire’s decentralized Git network, announced in July, which is designed to withstand the sharp increase in AI coding activity that has caused mounting GitHub outages.
More from ZDNET
What makes Entire different
The first change Entire makes to the standard coding experience is that it replaces pull requests with what it calls Trails.
“Unlike the classic Pull Request model of reviewing code changes with a diff, Trails offer developers a heads-up display similar to an airline pilot, with customized evals that are scored by agents on every code push,” the company said.
Also: Gartner’s 2027 tech trends just dropped – and they go beyond AI
“All data is available not only on Entire’s web interface, but also through the open-source Entire CLI. This allows coding agents to address findings in a loop, while the human developer validates the progress. When all evals are satisfied, they can merge the code without needing to look at the code itself.”
Entire said that the agents running this process are customizable, and each trail shows how agents are spending tokens.
“With Trails, Entire treats the idea, the agent trace, and the outcome of a developer’s sessions as first-class artifacts for review alongside the code,” Dohmke said. “It uses multiple agents to generate evals that verify the quality and success of AI-generated code to let developers confidently merge without reviewing every line in the diff.”
The company also claims it offers Git hosting “up to 89x faster than GitHub” and six times faster than Cursor origin, thanks to that aforementioned decentralized network. The platform lets developers create, migrate, and host private repositories in multiple locations across the world, currently starting with the US, India, Australia, and the EU.
Also: PHP2Shell: Haven’t patched yet? Take these steps now to mitigate
Another differentiating factor is Continuous Memory, which keeps developer session logs next to code in the repo as a data source. Agents can use them to search for answers, which, Entire said, helps them use up to 71% fewer tokens. This is similar to other memory features in AI chatbots that reduce time spent gathering context by using past conversations or other agent interactions, where provided, to speed query response time. Entire said Continuous Memory is made up of a codebase graph and an “agentic brain” that uses previous sessions and prompts as lessons so agents don’t repeat mistakes.
Entire is available to try today for all developers.
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