
YAGNI. Proactive agent Teams you manage like humans.
Manage AI agent teams with a human-friendly interface.
jackcollinshq · Product Hunt
YAGNI Proactive agent teams you manage like humans
The full gallery
Tech stack
24 projects

Manage AI agent teams with a human-friendly interface.
jackcollinshq · Product Hunt
YAGNI Proactive agent teams you manage like humans

AI agent that generates comparable product concepts from ideas, sketches, images, and constraints.
@hedge8og · X
4月23日,我开始用 Codex 搭自己的产品。到现在,满3个月了。 截至7月19日,Codex 页面显示247.1亿个 Token,连续使用54天。标题里的“250亿”是取整,准确数字以截图为准。 这三个月,我把 做上线了,产品介绍视频改了很多版,也借助 Codex 做了不少以前一个人很难完成的工作。 具体一点:我用它整理过 BP、导出过 PDF、做过 PPT 工作稿,也把调研、文档、图片、浏览器操作、网站、视频和邮件这些常见 Skills 跑过一圈。有些后来真的进入了工作,有些试完就放下了。 现在回头看,最大的收获不是“我做过这么多种东西”,而是我越来越能分清:哪些能力能进入真实工作,哪些只是演示起来很厉害。 这些数字确实挺夸张。说实话,我自己看到也会觉得:是不是做了很多事? 但如果现在让我总结,我不会把它们当成绩。它们只能证明我很投入,蹬得快冒烟了,不能证明产品已经有价值,更不能证明商业已经成立。 我大学辍学,最高学历是高中,之前一直在制造业工作,也不会写代码。写这些不是为了卖惨,更不是想证明学历没用,只是先把我的真实起点说清楚。 2月 OpenClaw 火起来以后,我开始认真试各种 AI 工具,想先解决工作里那些重复、又不得不做的事情。 这期间还有一次,客户马上要我提案,但公司的设计师手上也有急活。我用 ChatGPT 做了产品效果图,最后拿到了订单。 老板后来跟我说:“早知道你可以帮我做这些,那些外包设计早就可以不用买了。” 到了4月,我又用扣子搭了发货模板和记账系统。原来需要手工对比核验的条形码、外箱码,我也开始想办法交给工具处理。 这张订单图只能证明订单记录是真实存在的,不能单靠它证明订单一定是 AI 带来的,更不是 Ohwait 的客户案例。AI 参与了产品效果图制作,之后拿到订单,是我对那次真实工作过程的记录。 那一刻让我兴奋的,其实不是发现了什么创业机会,而是我第一次觉得,模型真的可以成为人的“数字外骨骼”。 回头看这三个月,我现在有5个比较确定的结论。 ### 1. AI最好先从一个真问题开始 发货、记账、核验、临时要效果图,这些都不是什么宏大命题,但它们有一个共同点:问题原本就存在,而且有人正在为它花时间、花钱或者承担压力。 我现在判断一个 AI 工具有没有价值,还是看两件事:它有没有少让我重复

Compare AI coding models on real tasks with live previews, cost tracking, and ELO rankings.
@intheworldofai · X
On the World of AI Bench (vibe-coding composite): Claude Fable 5 → 85.2 GPT-5.6-sol → 82.4 kimi-k3 → 81.5 Moonshot’s K3 just walked in and claimed bronze on one of the toughest coding-focused leaderboards out there.

Compare and evaluate AI models across coding, reasoning, agents, and other benchmarks.
davidtsong · HN
Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities

Query spreadsheets and datasets with plain-English questions to generate instant answers and reports.
u/maybeImakemoney · Reddit
I built the thing. Now I am not sure the base use case is one people will pay for. Founder here. This started as a side learning project to see whether an LLM could answer questions about Excel data, back when they could not do it well. I built the first version on n8n, with workflows that ingested files, generated metadata with an LLM, and answered questions against the converted data plus that metadata. Then I started using it for my own analysis and report generation, saw that the time sav

AI operating system that transforms business problems into company briefs and accountable build plans.
@MarkZofMarkZ · X
- in process of updating it currently, making it better. How about you? What are you building?

AI decision system for SEO recommendations based on judgment instead of traditional dashboards.
@iraftopo · X
Replacing SEO dashboards with accountable decisions

Create surveys, quizzes, and interactive games with AI-powered insights in one platform.
@lemhamza · X

Autonomous AI research engine that generates full academic papers with real citations from a prompt.
@fedeponte1 · X
my first saas. i think i built something people actually want and completely failed at the business side. would genuinely love help. openpaper ( writes full, cited research papers from a prompt. research, outline, writing, real citations, export. the honest numbers: - ~2,300 signups - ~1,500 generated a full paper. people actually use it. - ~5 have ever paid. ~$45/mo. activation is great, revenue is basically zero. i've been staring at this for weeks. the paywall is on export (pay ~$12 to download the pdf). but the full cited paper is right there on screen, free, you can read it and copy-paste it. so i'm charging for the gift wrap after handing over the gift. almost nobody even reaches checkout. 76% generate exactly one paper and leave. one-and-done, so subscriptions make no sense. the audience is mostly students and researchers on personal gmail, all over the world, almost none on university or company emails. traffic is x and github. so i genuinely can't tell

Platform combining human and AI agents to execute and manage projects.
@1T31062175 · X

Verify AI agent decisions locally with transparent reasoning and MCP integration.
brandon_grutkowski · Product Hunt
Aurora Glass-box Quantitative AI for Humans and Agents

Inject engineered cognitive abilities into AI agents at inference time.
@frank_brsrk · X
reasoning tools for ai agents