A solo founder using Bolt or Lovable can go from idea to working prototype in a weekend. Cursor handles multi-file refactoring on a production codebase. V0 generates polished UI components from a description. The founder who previously needed six months and $80,000 in savings or seed funding can now ship a testable product in two weeks for under $8,000 in tool costs. - Source: dev.to / 2 months ago

You see the same clean layouts, balanced spacing, Tailwind-based styles, and accessible components everywhere. Even AI tools like v0 and Bolt follow Shadcn-style patterns without calling it out. - Source: dev.to / 5 months ago

In early 2026, when you open v0.app and type a sentence to generate UI, it outputs Next.js + React + shadcn/ui. When you use Lovable to build a product prototype, it's powered by TypeScript + React + Vite + Tailwind. When you're vibe coding on Bolt.new, although it supports multiple frameworks, React is still the default. - Source: dev.to / 6 months ago

Meanwhile, stakeholders and product owners are engaging directly with AI tools such as Figma Make, Bolt, and Lovable to try ideas rapidly in interactive environments. Teams get faster feedback loops without creating wasteful prototype branches or long review cycles. - Source: dev.to / 6 months ago

Thanks for the comment, I suggest you plug the repository into Gemini or Claude Code and ask it to build 3 examples of original declarative agents, different from each other, and that are not simple chatbots - app builder bolt.new managed to create a chatbot on its own when I asked it to do so using "npm install beddel" (https://bolt.new/~/sb1-evqess6o), it's a simple and commonplace example, but it was amazing to... - Source: Hacker News / 7 months ago

This repository contains two Python scripts that demonstrate how to create a chatbot using Streamlit, OpenAI GPT-3.5-turbo, and Activeloop's Deep Lake. The chatbot searches a dataset stored in Deep Lake to find relevant information and generates responses based on the user's input. Source: about 3 years ago

u/Remote_Cancel_7977 we just launched 100+ computer vision datasets via Activeloop Hub yesterday on r/ML (#1 post for the day!). Note: we do not intend to compete with HuggingFace (we're building the database for AI). Accessing computer vision datasets via Hub is much faster than via HuggingFace though, according to some third-party benchmarks. :). Source: about 4 years ago

Hub, our open-source package, lets you stream datasets while training to PyTorch/TensorFlow. Check out how we achieved 95% GPU utilization while training on ImageNet at 50% less cost. We're building the Database for AI, with everything it should contain. If there's an adjacent feature that would make it more useful for your workflow, do let us know! Source: over 4 years ago

I'm Davit from Activeloop (activeloop.ai). Source: over 4 years ago