完整作品展
技术栈
60 projects
用AlterOS设计Discord服务器模板，一键应用到任何服务器。
u/Zexo66 · Reddit
i built a Discord tool that uses AI to Audit your server. it can also generate a server template after months of development, i was able to bring this idea to life. with this tool / bot you can create your server template easily, without going through discord menus, all in one page and manually. however, if you're struggling or you just don't want to waste any time, you can also use the "AI Design Assistant" feature that helps you with the template overall. another feature is
使用托管 Postgres、身份验证、实时订阅和自动生成的 API 构建后端。
@im_pradee_p · X
Backend as a service
在代码合并时强制执行策略并审计AI辅助的更改。
@Scyloq · X
Currently building SentrAI. The merge-time control plane for AI-assisted software development. Enforce policy, audit every AI-generated change. Just finished an interactive demo and would love your honest feedback. Built with @Lovable
无代码应用构建器，支持AI工作流，专为非技术创始人设计。
@sanchoyai · X
2/ Meet Momen - the no-code builder for production-ready Apps Go to → Got a big app idea but can’t code? The no-code builder that lets non-technical founders create apps go from idea → millions of users. UI, database, workflow, AI — all in one. Not vibe coding, but something you can control, grow, and scale.
比较 git、Jujutsu 和 GitButler 在 Claude Code 和 Codex 代理上的性能。
videlov · HN
I was interested in answering this question so I built a benchmark comparing git, jj and gitbutler in agentic context https://vcbench.dev/ Disclaimer - I am a co-founder of GitButler
为开发者设计的轻量级高性能日志系统。
@CodeIsmySpotter · X
I am building a lightweight logger for developers:
在浏览器间直接共享文件和文本，无需服务器存储或登录
@bytestreak · X
Building a frictionless, forever free file sharing utility tool. Check it out here:
在多个运行时中设计、验证和比较AI代理部署，具有内置治理功能。
@paulrodturner · X
托管 JSON 数据库，用于存储 agent 内存，具有 REST 和 MCP 连接能力
@StuSim · X
hey Adam, I run , lightweight agent memory
使用在微虚拟机中运行代码的AI代码审查来捕获更多漏洞。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db
