The New AI Stack

Multi-user AI development environments where teams build together with shared AI assistants. Architecture patterns and emerging tools for real-time AI collaboration.

Agents use tools, persist state, and take autonomous action. Chatbots just respond. Understanding this distinction explains why skill ecosystems exist.

AI makes old code patterns obsolete. Why boilerplate code, scaffolding, and repetitive patterns should be generated on demand rather than maintained by hand.

Package distribution challenges for AI tools and frameworks. How binary dependencies, precompiled libraries, and framework distribution are evolving alongside AI development.

Runtime method swizzling techniques remain relevant in the AI era. How AI agents leverage dynamic dispatch, monkey patching, and runtime modification patterns.

Why open-source AI skills matter for the future of development. How OpenClaw's open skills movement is democratizing AI capabilities across the industry.

Cron jobs, shell scripts, and ClawFlows workflows all automate tasks — but they're designed for different problems. Here's how to choose.

Convert your docs to llms.txt format so AI tools can consume them. Practical guide to structured documentation for AI consumption.

A detailed comparison of OpenClaw and Claude Code across architecture, model flexibility, extensibility, messaging channels, and security models.

ClawFlows workflows compose skills into routines. Here's the architecture — how workflows call skills, pass state, and handle errors across steps.

Every Claude user has lived through session amnesia. Here's why it happens, why CLAUDE.md is a partial fix, and how Hermes solves it at the runtime layer.

Self-improvement in Hermes is not model fine-tuning. It is the agent writing markdown SKILL.md files when it encounters a lesson worth remembering.