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This article presents concrete UX design patterns for building agentic AI systems that prioritize user control, transparency, and trust.
This post describes how Google's Gemini Deep Think mode is being applied to solve professional research-level problems across mathematics, physics, and computer science.
This post explains how Vercel built an AI Engine Optimization (AEO) tracking system specifically for coding agents like Claude Code and OpenAI Codex.
Google launched a hosted Data Commons MCP server on Google Cloud Platform, removing the need for local Python environments to query public statistical data with AI agents.
Supabase has become an official Claude connector, enabling users to manage database infrastructure through natural language.
This post argues that Google's dual use of its search crawler (Googlebot) for both indexing and generative AI training gives it an unfair competitive advantage over publishers and rival AI companies.
Google is rolling out Project Genie, an experimental research prototype powered by Genie 3, allowing users to create and explore interactive worlds in real time.
This post introduces Moltworker, a middleware solution that enables running Moltbot (a self-hosted personal AI agent) on Cloudflare's infrastructure without dedicated hardware.
This post details how Grab scaled adoption of the Cursor AI coding assistant across engineering and non-technical teams, sharing key metrics and productivity findings.
This post describes a real-time AI racing coach built by Google Developer Experts using a split-brain architecture tested at Thunderhill Raceway.
Josh Clemm, VP of Engineering at Dropbox, explains how Dash uses knowledge graphs, MCP, and DSPy to build a universal work search and AI assistant.
LiteRT is Google's universal on-device AI inference framework evolved from TensorFlow Lite, now with full GPU and NPU acceleration across platforms.