Two weeks of dogfooding Engram, Weaviate's memory product, in daily Claude Code sessions. This surfaced where a dedicated memory product adds value, and the specific mechanics that prevent integration with coding assistants from working well.
It feels like spring has sprung here, and so has a new NVIDIA integration, ticket sales for Interrupt 2026, and announcing LangSmith Fleet (formerly Agent Builder).
Your Code is Your Schema: Weaviate Managed CClient
Use semantic search and RAG in C# with the Weaviate Managed .NET client — attribute-driven schema, type-safe queries, and safe migrations, all in idiomatic .NET.
How Kensho built a multi-agent framework with LangGraph to solve trusted financial data retrieval
Discover how Kensho, S&P Global’s AI innovation engine, leveraged LangGraph to create its Grounding framework–a unified agentic access layer solving fragmented financial data retrieval at enterprise scale.
💡TLDR: The best agent evals directly measure an agent behavior we care about. Here's how we source data, create metrics, and run well-scoped, targeted experiments over time to make agents more accurate and reliable.Evals shape agent behaviorWe’ve been curating evaluations to measure and
How Middleware Lets You Customize Your Agent Harness
Agent harnesses are what help build an agent, they connect an LLM to its environment and let it do things.When you’re building an agent, it’s likely you’ll want build an application specific agent harness. “Agent Middleware” empowers you to build on
How Moda Builds Production-Grade AI Design Agents with Deep Agents
Moda uses a multi-agent system built on Deep Agents and traced through LangSmith to let non-designers create and iterate on professional-grade visuals.
If you're attending Google Cloud Next 2026 in Las Vegas this year and working on agent development, here's what we have planned.Visit Us at Booth #5006We'll be at Booth #5006 in the Expo Hall at the Mandalay Bay Convention Center, April 22-24.
LangSmith Fleet introduces two types of agent authorization: Assistants, which use the end user's own credentials, and Claws, which use a fixed set of credentials.
Polly is generally available everywhere you work in LangSmith
Debugging agents is different from debugging anything else you've built. Traces run hundreds of steps deep, prompts span thousands of lines, and when something goes wrong, the context that caused it is buried somewhere in the middle.We built Polly to be the AI assistant that can read
LangChain Announces Enterprise Agentic AI Platform Built with NVIDIA
Comprehensive agent engineering platform combined with NVIDIA AI enables enterprises to build, deploy, and monitor production-grade AI agents at scalePress ReleaseSAN FRANCISCO, March 16, 2026 /PRNewswire/ — LangChain, the agent engineering company behind LangSmith and open-source frameworks that ha...
Clarifai Reasoning Engine Achieves 414 Tokens Per Second on Kimi K2.5
Clarifai achieves 414 tokens per second on Kimi K2.5, one of the first providers to reach 400+ TPS on a trillion-parameter reasoning model running on Nvidia B200 GPUs.
We’re excited to introduce the deploy cli, a new set of commands within the langgraph-cli package that makes it simple to deploy and manage agents directly from the command line.The first command in this new set, langgraph deploy, lets you deploy an agent to LangSmith Deployment in
Clarifai 12.2: Three-Command CLI Workflow for Model Deployment
Clarifai 12.2 introduces a three-command CLI workflow for model deployment. Initialize, test locally, and deploy to production with automatic GPU selection and infrastructure provisioning.
TL;DR: We've added a tool to the Deep Agents SDK (Python) and CLI that allows models to compress their own context windows at opportune times.MotivationContext compression is an action that reduces the information in an agent’s working memory. Older messages are replaced by