136 related articles
Sx 2.0: Sharing AI Skills via Dropbox …
Sx 2.0 distributes team AI skills via shared Dropbox folders — no servers, zero deployment cost. A deep dive into its design philosophy, technical trade-offs, and the future of AI skill asset management.

John Carmack and Turing Award winner Richard Sutton co-founded Keen Technologies. Their debut paper Physical Atari has robots playing real Atari games via cameras and mechanical controllers in real time.

ChatGPT desktop gets a major upgrade, integrating Codex into new Work and Codex modules. Hands-on tests cover auto PPT generation and full AI video production pipelines.

Deep dive into Claude Code cloud sessions (Claude Cowork): build context repositories, assign minimum-privilege credentials, and orchestrate parallel AI agents as an engineering team.

Deploy DeepSeek-V4-Flash DSpark on 8× H20-141G using GPUStack's SGLang backend on Day 0. Full walkthrough of Web UI config, parameter tuning, and 200 tokens/sec benchmark results.
MailFlow Open Source Email Client: A D…
MailFlow is an open source email client project built for developers, prioritizing privacy, self-hosting, and extensibility. Here's why it matters and how to evaluate whether to contribute.

A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.

A hands-on test of MiniMax as an AI Agent brain using the Hermes V0.18 framework: fast inference, low cost, stable long tasks—but clear flaws in complex reasoning and tool calling. Learn its three strengths, three weaknesses, and best-fit workflows.

A systematic breakdown of the AI agent development learning path, covering four stages: fundamentals, RAG knowledge bases, tool use, multi-agent collaboration, and hands-on projects.

AI Agents are becoming the core form for deploying large models. This article explores the AI Agent Builder profession, revealing the SME deployment gap and a complete path from fundamentals to delivery.

An in-depth guide to building an AI-driven second brain with Obsidian + Hermes Agent. Covers living files, VPS deployment, core memory mechanisms, and skill visualization.

A systematic guide to Coze's positioning and capabilities, covering Agent-building platform categories, Skill modules, workflow orchestration, and multi-Agent team building.

How can you prepare efficiently for a Java backend interview? This article breaks down the core methodology of "process-driven interview engineering," covering resume optimization, understanding principles, scenario analysis frameworks, and production troubleshooting.

When an intern uses AI to generate professional-looking slop code, stand-ups balloon from 15 to 45 minutes. This article dissects why AI slop is hard to spot and offers practical team solutions.
OpenAI Targets the Home Market: How Ch…
OpenAI is recruiting a family product manager, targeting older adults and caregiver scenarios. An in-depth analysis of ChatGPT's shift from productivity tool to home digital assistant.

ECC is an agent optimization framework for AI coding assistants like Claude Code, Cursor, and Codex, enhancing them with skills, memory, security, and research-first development capabilities.

OpenAI releases GPT-5.6 (SOUL/TERRA/LUNA), with Ultra mode running four agents in parallel; Meta launches Muse Spark 1.1 with million-token context; ChatGPT desktop unifies Chat, Work, and Codex.

GPT-5.6 is officially released, merging ChatGPT and Codex into one app and launching the three-tier Sol, Terra, and Luna models. A detailed breakdown of 16 hands-on tests plus Worker mode and Codex dev upgrades.

Many teams add message queues, search engines, and caches before they ever need them. This article maps out what Postgres can cover—task queues, full-text search, JSON storage—and when you actually need Redis, Kafka, or Elasticsearch.

A complete AI Agent learning roadmap covering agent principles, prompt engineering, RAG, multi-agent systems, and hands-on projects — from zero to real-world deployment.