LLM

Hermes Agent ships with a Kanban style task board that can easily saturate your self hosted LLM gateway if you let every task run at once.

Hermes Agent treats skills as the default way to teach repeatable workflows. Official documentation describes them as on-demand knowledge documents aligned with the open agentskills.io shape, loaded through progressive disclosure so the model sees a small index first and only pulls full instructions when a task actually needs them.

Hermes Agent from Nous Research is a model-agnostic, tool-using assistant you run locally or on a VPS.

Most AI agent stacks still treat security as a post-demo fix. NemoClaw starts from the opposite assumption and makes isolation, policy, and routing day-zero defaults.

Modern assistants still forget everything when you close the tab unless something persists beyond the context window. Agent memory providers are services or libraries that hold facts and summaries across sessions — often wired in as plugins so the framework stays thin while memory scales.

This section collects guides on persistent knowledge and memory for AI systems — how assistants keep facts, preferences, and distilled context across sessions without stuffing every token into one prompt. Here, memory means intentional retention (user facts, summaries, plugin-backed stores), not GPU RAM or model weights.

You know the drill. You open a chat with an AI agent, explain your project, share your preferences, get some work done, and close the tab. Come back the following week and it’s like talking to a stranger — all context gone, every preference forgotten, the project re-explained from scratch.

OpenClaw did not fail as a product. It lost its fuel.

For a long time, llama.cpp had a glaring limitation:
you could only serve one model per process, and switching meant a restart.

Most teams misuse Claude Skills in one of two ways. They either turn SKILL.md into a dumping ground, or they never graduate from giant copy-pasted prompts.

Hermes AI assistant, officially documented as Hermes Agent, is not positioned as a simple chat wrapper.

OpenClaw has two extension stories, and they are easy to mix up.

Plugins extend the runtime. Skills extend the agent’s behavior.

This article is about OpenClaw plugins — native gateway packages that add channels, model providers, tools, speech, memory, media, web search, and other runtime surfaces.

OpenClaw looks simple in demos. In production, it becomes a system.

The quiet loophole that powered a wave of agent experimentation is now closed.

Vane is one of the more pragmatic entries in the “AI search with citations” space: a self-hosted answering engine that mixes live web retrieval with local or cloud LLMs, while keeping the whole stack under your control.