Cainew

🧭 Architecture-first system design: 26 bilingual tutorials, 25 architecture templates, and 6 end-to-end cases covering distributed systems, AI-native systems, RAG, coding Agents, and production trade-offs.

🐹 A free, open-source, native macOS GUI for the Mole CLI (mo): clean, uninstall, optimize, analyze disk, and watch live status. Plus long-range history + an MCP server for AI agents. Coming to Windows

Interactive AI General Education Course — 30 Lessons, Zero Math

A local control plane for AI agents — see what they do, approve what matters, keep secrets out. Rust + Tauri + Chrome MV3.

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Clean-room, model-agnostic harness for Claude Code-class coding agents

GBase — Recursive Self-Improvement Agent Framework. Memory, evolution, quality gates, identity system, and 40+ auto-registered tools.

The Vue framework for terminal UIs. SFC & JSX, Yoga flexbox, HMR, and testing out of the box.

A library-science-inspired personal knowledge management system with LLM agents

Meet the AI team for your team. WorkClaws are collaborative, proactive AI coworkers who work in Slack and Microsoft Teams just like every other colleague. They're fully customizable to get work done your way by learning skills and routines. Unlike most AI products that pair one person with one assistant, WorkClaws can collaborate 24/7 with your whole team. Each Claw has a job title, a manager in your org chart, and a cloud-hosted ClawOS computer with the ability to access more than 3,000 apps.

Slackbot’s new MCP Client ends fragmented AI work by connecting 20+ apps (Atlassian, Linear, Canva, Zoom) to one conversational interface. Ask Slackbot in plain language to act across tools—sign docs, update tickets, view dashboards—then share results in team channels for true multiplayer collaboration.

Meet Mellum, a family of fast language models, including a next-generation model for ultra-low-latency and high-performance inference.

Most AI agent workflows lose useful context between sessions, tools, and chats. The usual fixes are either too manual, like copying notes into docs, or too heavy, like setting up a database, vector store, or custom RAG stack. pumaDB gives agents a simple shared place to save and reuse notes, facts, preferences, project context, transcripts, task state, and other useful memory. No database setup, vector DB, or infrastructure to manage

Basedash now has groups and access controls. Bundle users into groups — internal teams, external clients, leadership — and give each one access to exactly what it needs: data sources, MCP servers, dashboards, chats, and automations. Set a group's AI context so the assistant answers differently per audience, and row-level security applies to every question. The right people see the right data.

The weights are the billions of numbers forming an AI's brain. Type a name and see how strongly the leading AI models recognize it. Are you in the weights?

Renowned US scientist John Jumper is departing from Google DeepMind to join Anthropic in a significant leadership shift within the AI industry. His move reflects the competitive talent landscape among leading AI research organizations.

Amazon canceled a film project featuring Sam Altman following the announcement of their partnership with OpenAI, potentially to avoid conflicts of interest or competitive concerns. The decision reflects the complex business relationships between tech giants and AI companies.

An agency was accused of stealing a bestselling author's book and using AI technology to republish it under their own brand without authorization. This incident highlights copyright and intellectual property concerns in the age of AI-assisted content creation.

Companies are reducing their AI usage as operational costs become increasingly prohibitive and strain budgets. This trend suggests a more measured approach to AI adoption as organizations reassess ROI and sustainability.

This piece discusses how large language models have become increasingly complex, making them harder to understand and control as they scale up in sophistication. The complexity of modern LLMs presents ongoing challenges for researchers and developers.