Technology

💼 Institutional-Grade Arsenal: The world of hedge funds and institutional investing has long been shrouded in secrecy, with proprietary tools and strategies giving professionals a significant edge. However, the democratization of AI is changing this landscape, making powerful investment intelligence accessible to retail investors. Here’s a look at the tools that were once exclusive to Wall Street elites but are now available to those who know where to look. Real-Time Intel: BigData.

Building a RAG Chatbot in 45 Minutes: A No-Code Guide I built a RAG (Retrieval-Augmented Generation) chatbot in just 45 minutes—without writing a single line of code. This is an excellent way to learn or create a solution for an AI product manager portfolio. But how does it actually work? First, RAG isn’t just about vector storage. It can retrieve information from various data sources like Google Drive, SQL databases, or plain text files.

How to Automatically Generate Prototypes in Cursor Using Figma MCP Currently, the two most starred Figma MCP servers on GitHub are Figma-Context-MCP and Cursor Talk to Figma MCP. These tools enable seamless integration between Figma and Cursor, allowing for automated prototype generation and design-to-code conversion. Figma-Context-MCP vs. Cursor Talk to Figma MCP 1. Figma-Context-MCP Figma-Context-MCP leverages the Figma API key to fetch detailed element data, enabling precise control over design elements and converting designs into code.

The third Sequoia Capital AI Ascent just wrapped up in San Francisco. After watching all the available footage on YouTube, it’s clear there were some game-changing insights—essential reading for any AI founder or industry professional. 1. The Shift in Revenue Logic: Selling Outcomes, Not Tools AI isn’t about selling software—it’s about selling results. Pricing is shifting from features to outcomes. Old model: A CRM sells “customer management tools.” New model: An AI-driven CRM agent sells “X closed deals per month.

In the ever-evolving world of AI-driven design tools, understanding how systems like Google Stitch generate their outputs can provide valuable insights for designers and developers. Recently, I successfully reverse-engineered Stitch’s design prompts using methods inspired by online “trickery” techniques. Below, I’ll share the findings. The Design Prompt Here’s the reverse-engineered prompt used for both tools (refer to the uploaded image for the original text): You’re a friendly UX/Product designer that’s an expert in mobile and web UX design.

The Hard Truth About AI in the Workplace Slapping a chatbot into your company Slack isn’t “AI adoption.” Too many businesses make these mistakes: AI becomes just another tab employees forget to open. Models improve, but answers stay generic — no deep alignment with actual work. Information chaos persists because AI isn’t wired into daily workflows. The root issue? AI is often bolted on, not built in. Feishu’s Fix: AI That Works Where You Work Enter Feishu (Lark) Knowledge Q&A, launched today.

Alibaba just unveiled Qwen 3, its latest open-source large language model (LLM), and its flagship Qwen3-235B-A22B now rivals DeepSeek R1, Grok-3, and Gemini-2.5-Pro in benchmarks. With hybrid inference and enhanced Agent capabilities, Qwen 3 signals a shift — open source is China’s key to global AI dominance. The New Open-Source Power Duo: Qwen + DeepSeek For years, the open-source LLM ecosystem was ruled by Meta’s Llama and Mistral. But today, DeepSeek and Qwen are taking over.

We delve into the transformative ideas presented by OpenAI Agent Researcher Yao Shunyu during his discussions at CS 224N and Columbia University. We Stand at the Midpoint of AI For decades, the crux of AI has revolved around developing innovative training methods and models. This trajectory has proven effective: from defeating international chess and Go champions to outperforming most on SATs and bar exams, winning gold medals at IMO (International Mathematical Olympiad) and IOI (International Olympiad in Informatics) — milestones like DeepBlue, AlphaGo, GPT-4, and the O series were born from underlying training method innovations, including search, deep RL, scaling, and reasoning.

You’ve also jumped on the Dify.ai bandwagon? Smart move! It’s a seriously cool platform for building AI apps. But, like any powerful tool, it can get a little… expensive if you’re not careful. I’ve been playing around with it for a while now, and I’ve picked up a few tricks to keep my token usage (and my credit card bill) down. Think Before You LLM This is the big one. Every time you hit that “Run” button and the Large Language Model (LLM) spins up, you’re burning tokens.

This year’s Product Hunt Golden Kitty Awards are a love letter to AI—and developers are eating good. From code assistants to synthetic video wizards, tools that blend human creativity with machine speed dominated the rankings. Let’s break down the winners (and why your workflow needs them yesterday). Top Dog: Cursor The AI Pair Programmer That Just Gets You Forget clunky IDEs. Cursor, crowned Product of the Year, is where coding meets conversation.