Side by side example
Same model (claude-opus-4-6). Same task. Two different agent harnesses
@LangChain Deep Agents CLI: 9s
Claude Code: 16s
The harness IS the performance. 1.7× difference, zero model changes
@mikeysee@convex Crazy - I am in the process of removing a field from a Convex Prod server and learned about the “three step” migration process today
The ripple effect is real
Appreciate the timely video!
Neat - @GoogleAI just mentioned @ContextRepo along side one of my hero’s @AndrewYNg
A couple weeks ago I attended Andrew’s and @hwchase17’s talk about the Future of AI Agents live at LangChain Interrupt -
Inspiring 🍀
@MattPRD https://t.co/SkXBVmF9sP has to be the best agent-readiness tool available rn, and it’s free
Literally gives you the prompts to improve your app agent surface - easy to pick off low hanging fruit
Created by @assaf_elovic (Tavily Creator) - there is a wealth of timely info on Ora
Ridiculously cool open source example using @LangChain_JS
The Multi-Modal children’s bedtime story generator is an excellent example of LangChain streaming UI & stream namespace subscriptions - great patterns to learn from!
Great share @bromann 🔥
As an upcoming parent, I keep imagining all the tiny routines ahead 😊👼
One I am especially excited for: using AI for making up bedtime stories.
So I built an app that creates one on demand: story, illustrations, and narration all streaming in together with @LangChain_JS ❤️
a few months back, it become clear to us that a large part of technical work would be driven by agents in the future. coding agents were becoming ubiquitous and highly capable.
since we build a platform for technical users, we needed to update our beliefs and strategy accordingly! LangSmith Engine automates the improvement of agents by looking through recent traces and finding problems according to a taxonomy of common agent issues that we have defined.
we launched the product at our annual conference last week and the reception so far has been very exciting. and we're just getting started 📈