Ben AI demystifies the technical framework behind Claude Cowork, breaking down essential components like memory management, file access, and automated skills. Learn how to leverage local context, MCPs, and autonomous routines to build a scalable second brain that streamlines complex workflows and improves AI performance for individual projects or entire teams.
Google basically split Antigravity into multiple apps and the internet is LOWKEY crashing out trying to understand what happened.
This honestly feels like Google’s direct answer to tools like Claude Code, Codex, OpenAI Agents, and the entire rise of autonomous AI workflows.
At its Google I/O conference on Tuesday, Google unveiled an AI-powered overhaul of Search centered around a reimagined “intelligent search box” — what the company describes as the biggest change to this entry point to the web since the search box debuted more than 25 years ago.
Redis built its name as the caching layer that kept web applications from collapsing under load. The problem it is targeting now has the same structure but is harder to solve: production AI agents failing not because the models are wrong, but because the data underneath them is scattered, stale and structured for humans rather than machines. Retrieval pipelines built for single queries cannot absorb the volume agents generate.
The gap Redis is targeting is structural: agents make orders of magnitude more data requests than human users, but most retrieval layers were built for the human-scale problem. Redis Iris, launched Monday, is the company's answer: a context and memory platform that sits between an agent and the data it needs to act.
The company formerly known as Intercom just did something that no major customer service platform has attempted at scale: it built an AI agent whose sole job is to manage another AI agent.
Fin Operator is a new AI-powered system designed specifically for the back-office teams that configure, monitor, and improve Fin, the company's customer-facing AI agent. Rather than replacing human support agents — which is what Fin itself does on the front lines — Operator targets the growing army of support operations professionals who spend their days updating knowledge bases, debugging conversation failures, and combing through performance dashboards.
The /goal is incredible in both Codex and Claude Code, and really this is the beginning of being able to work with AI coding agents in a completely different way - for longer running and more complex tasks, with less human oversight.
In this video I break down how to use /goal, how to structure your goals before running them, and how to build a full application from one /goal just using a prd and product-roadmap markdown file.
Claude Code use cases go way beyond coding. In this video we break down how to use Claude Code as a second brain, video editor, research engine, and design tool. From AI automation to claude code skills, see how anthropic claude can run your day.
