Building Laminar: Ramp's Managed Agents Platform (14 minute read)

TLDR AI Products
agent-harness ai-agents in-house-platform llm-tooling observability engineering

Summary

Ramp 详细介绍了其内部构建的 Laminar 智能体平台，提供对话历史存储、会话压缩、工具调用接口、消息队列与转向、子智能体、多人聊天及可观测性等功能，首个版本由智能体在六周内生成代码完成。

Laminar is an in-house agent harness for Ramp's agentic products. It features secure conversation history storage, session compaction, standard interfaces for tool calling, message queuing and steering, subagents, multiplayer chat support, observability tooling, and much more. The first version of Laminar was built in six weeks with a small team of obsessive, experienced engineers who worked with and steered the agents. Its code was generated entirely by agents using the most powerful models available at the time. While building in-house has become cheaper, Ramp still needs good engineers to be on-call, keep the platform healthy, and figure out what product teams actually need and how it fits into the bigger picture.
Original Article

Similar Articles

Ramp Glass (4 minute read)

TLDR AI

Ramp 推出 Glass，一款共享公司知识、可复用技能与协作会话的 AI 工作区，通过 Ramp Router 模型路由使 AI 成本下降 30%，并显著扩展了工作流自动化。

What if an agent runtime never tells the model what to do next?

Reddit r/AI_Agents

作者介绍了一种名为 LCRK（LIA Cognitive Runtime Kernel）的被动式智能体运行时架构：基础设施只检测事件、维护持久内部状态并提供工具访问，不负责编排下一步动作，由模型自主决定是否行动、做什么或保持静默。该系统不依赖 LangChain、CrewAI 或 AutoGen，源码暂未公开。

Making LLM context assembly programmable

Reddit r/AI_Agents

RAMPART is a Python library that makes LLM context assembly programmable, allowing developers to register named blocks of context for placement before the model's first token. It improves performance by tens of percentage points on various models through block clustering and tool access control.