6/ With Groq’s efficient inference and Qwen3‑32B’s pinpoint citations, Scira transformed. It wasn’t just fast. It was sustainable. Add in Vercel AI SDK, Next.js, and a crisp Shadcn UI and you had a stack users loved. They even preferred it to GPT‑4o.
TOOLS
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Scira: Full-Stack AI Search Engine Reaches 1 Million Searches Monthly
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7/ Today, Scira is a full-stack AI search engine used by 60,000+ people each month, with more than 1 million searches served. The GitHub repo has earned 8,000+ stars and continues to climb. Built in public. Maintained solo. Proven by use, not hype.
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Scira and Groq: How Accessible AI Saves Startups
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Scira grew fast, but it wasn't built to scale affordably. Running large models like Anthropic was burning over $1,000/month. Every search chipped away at Zaid's savings.
He nearly pulled the plug. Then @GroqInc stepped in with compute that could finally keep up. -
Zaid’s Journey Building a Better AI-Powered Web Search Tool
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2/ Like many great dev stories, it started with frustration. Zaid wanted a better way to search across the web using AI. Something fast, clean, and customizable. Perplexity was powerful, but felt closed and out of reach. So he started building.
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MiniPerplx: Open-Source Search with Research Groups Feature
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— Groq Inc (@GroqInc) 30 juin 2025
He called it “MiniPerplx” at first: a lightweight, open-source alternative. No login. No paywall. No noise.
Then he added Research Groups which allowed search across YouTube, Reddit, and X, all at once, grouped by source. It actually worked. That’s when it took off. pic.twitter.com/Jitwo8ad9F3/ He called it “MiniPerplx” at first: a lightweight, open-source alternative. No login. No paywall. No noise. Then he added Research Groups which allowed search across YouTube, Reddit, and X, all at once, grouped by source. It actually worked. That’s when it took off.
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Solo founder builds open-source Perplexity competitor without funding
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This solo founder built an open-source competitor to Perplexity with no team, no funding, and no permission. What started as a weekend project now powers over 1M searches, with 60K+ monthly users. This is the story of @sciraai and how Zaid Mukaddam built what others wouldn’t.
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Hugging Face Science Team Showcases Year of AI Contributions
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The @huggingface Science team now has an org on the hub and it's really cool to look back at all their contributions of the past 12 months! Fineweb, LeRobot, TheStack, StarCoder2, SmolLM2, Big Science, LLMleaderboard, TRL, Nanotron, or some of the courses that have been followed
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MongoDB Text-to-MQL with LangChain: Natural Language Queries
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@MongoDB supports Text-to-MQL with LangChain, allowing you to convert natural language queries directly into MongoDB queries. This makes it easier to build apps and agents that interact with your data seamlessly. Read the blog: https://
mongodb.com/blog/post/prod
uct-release-announcements/introducing-text-to-mql-langchain-query-mongodb-using-natural-language?utm_campaign=langchain_text_to_mql&utm_source=mongodb&utm_medium=blog&utm_term=langchain
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Building an Agent with Authentication and Payment Processing
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New Video: How to Build an Agent with Auth and Payments AI Services often track LLM requests via credits. We just released a video showing how to build a LangGraph.js app that does exactly this! It has:
– Stripe for payments
– Supabase for auth & credits
– LangGraph