@abhishekbariyaa · X

@Puneet626 · X

hi, let's connect, i'm building

u/youex-ai · Reddit

Built a CRM w/ MCP -- Biggest misunderstanding on first look? We launched an MCP connector a few weeks ago that connects our CRM data. We're still working through our product market fit, so I asked Claude What is the biggest thing people misunderstand about YouEx.ai when they first see it? I was actually not even thinking about researching our actual CRM data, but that's what it did. The answer was actually really insightful: Your own data points at it: a large sha

@abhishek_gadhia · X

@AIDailyGuy · X

the form built for agents

keyserfaty · Product Hunt

Agentcard for companies Give your agent a debit card

@AiShivam · X

AgentStacKPro is an OS for AI agents designed to make them production-ready, and it holds incredible potential. You can also check out the project I currently developed

@SaikatKuma87126 · X

Just shipped AI CRM 🚀 A lightweight CRM with AI-powered sales insights. Would love your feedback: Building with Next.js + Prisma + Gemini AI. #buildinpublic #NextJS #AI

AI Todo — 像很多程序员一样，我日常要兼顾工作任务、生活琐事、项目计划，时常感到事情多但漏掉的也不少。想用智能方式管理这些待办，但市面上的工具要么设计臃肿，要么 AI 能力很弱。于是我花了几周开发了 AI Todo，目标是:

@AIWMCX1 · X

Consultants don’t need more noise. AIWMC Quantis helps turn messy business ideas into clear scenarios, runway views, and risk signals — so you can spend less time rebuilding analysis and more time giving the client a real answer.

@harryjwang · X

I've used many of the major conference systems. Plenty still have docs as an unsearchable static site — or worse, as PDFs that stopped tracking the product three versions ago. Somehow, still true in 2026. We took an AI-first path with instead. Our docs are generated from the codebase itself. A custom Claude Code skill writes each page and retakes the screenshots whenever a feature changes — so the docs don't drift from the product. Every page still gets reviewed by a human before it ships. Now you can talk to them, too. We just shipped "Ask AI" over our docs: This feature also turned out to be a nice teaching case for agentic RAG vs. classic RAG: • Classic RAG: chunk → embed → vector DB → retrieve once, by fixed rules • Agentic RAG: hand the model a search tool and let it drive — write a query, read the results, rewrite, retry At more than 100 pages, still no vector database needed. And every answer cites the exact page it came from. #Age

u/sweetnessssss · Reddit

Nine months ago I quit my data science job to build an app. The app is still hungry. Nine months ago I left a comfortable data science job at a travel company to build a sports betting app. Comfortable is and odd word for a job - it means the money arrives on schedule and nobody in your family asks if you're okay. The app is called THE LINEUP ( https://thelineup.pro/ ) -- it does the unromantic parts of betting: comparing prices, working with projections and tracking what happened afterwar