Ramp 自建 Agent 框架经验获 LangChain 创始人点评

this is great deepdive into what a managed harness looks like! some quick thoughts while reading: - many diff types of agents built on it. doesnt surprise me - a lot of agents look very similar inside these days - why not use off the shelf? (1) model and provider agnostic), (2) co-build with product teams, (3) own observability stack. I very much agree with points 1 and 3!!! and is something we obviously emphasize at langchain - "The simplest agent harnesses are truly just a while loop, but when you want to support a wide array of agentic products in production, the responsibility of the harness or framework expands quite a bit" - +100 to this, is why were investing in deepagents so much - "Using the “sandbox-as-a-tool” paradigm" - the massive trend seems to be going this way (is how deepagents is architected) - "Supporting non-blocking async agents as the default". we are working on this right now for deepagents! agree is the future - "The Connectors Service is the standard interface through which agents at Ramp interact with data sources. It centralizes authentication, credential management, access controls, and tool execution behind one API. This allows us to build and maintain integrations once, and reuse them across products." Also very important! and something we're thinking a bunch about for managed deepagents Kiryl @kir_lev We at Ramp tried a bunch of agent harnesses and ended up building our own. Cloud-native, model-agnostic, tailored to our infrastructure and product. And we published how we built it: builders.ramp.com/post/building-… 🔗 View Quoted Tweet 💬 9 🔄 3 ❤️ 28 👀 2846 📊 13 ⚡