推文详解了如何使用 OpenClaw 构建包含隔离画像、上下文记忆和成本优化模型路由的可扩展多智能体架构。

部署运维📅 2026/03/31
#CI/CD#部署#开发者#Discord#文档#全自动#GitHub#低风险#手动触发#Telegram#代码#生产中
openclaw is the most underbuilt-on platform in AI right now.

hermes just dropped multi-agent profiling, contextual memory, and MCP server mode. these are genuinely good features. but what's wild is that most of this has been possible on @openclaw architecture for months. people just aren't building on it.

here's what i mean. this is my current setup and what it actually does:

multi-agent profiling - i run 62 agents across 3 separate companies. each agent has its own 

SOUL(.)md (personality and rules), MEMORY(.)md (long-term context), and AGENTS(.)md (role, who it reports to, what it can spawn). 

my content writer has zero knowledge of my infrastructure agent. no context bleed. no mixed memory. completely isolated workspaces.

why this matters: without profiling, every agent shares the same brain. 

that's fine for one task. the moment you scale to multiple use cases it falls apart. profiling is the difference 
between "a chatbot that does stuff" and "a team that operates."

contextual memory per chat - every discord channel and every telegram thread writes to its own memory file. 

when an agent wakes up in a conversation, the first thing it does is read what happened in that specific chat. 

it knows what you discussed last tuesday. not because the model remembers, but because the memory layer is wired up.

why this matters: the number one complaint about openclaw is "it forgets everything." it doesn't forget. you just haven't told it where to remember. channel memory + workspace memory + event logs = genuine cross-session awareness.

model routing - not every task needs the expensive model. orchestration runs on opus. writing runs on sonnet. background crons run on gemini flash for free. research runs on minimax. this alone cut my costs by about $75/month without losing quality.

why this matters: most people run everything on one model and wonder why it's expensive. matching the model to the task is the easiest optimisation nobody do the hermes feature i'm actually most excited about is MCP server mode. 

right now i run openclaw through discord, which works, but if i could pipe it through cursor's UI with obsidian open on the side, that changes the whole workflow.

none of this is hard to set up. it just requires treating openclaw as infrastructure to build on, not a finished product to use.

Interested to hear what others have to say.