AI Tools & Frameworks Directory

Clay is the creative tool for growth — a platform where go-to-market teams build, enrich, and activate lists of companies and people. Sales teams use Clay to source target accounts, qualify leads with AI-powered research, draft personalized outreach, and route opportunities through their CRM. Clay's...

Deploy Public MCP servers as an API endpoint and integrate its tools into LLM workflows using function calling.

You can't monitor agents like traditional software. Inputs are infinite, behavior is non-deterministic, and quality lives in the conversations themselves. This article explains what to monitor, how to scale evaluation, and how production traces become the foundation for continuous improvement.

Learn how we built a production-ready, end-to-end RAG application in just 36 hours using the Query Agent and the new Weaviate Agent Skills library.

A key part of Agent Builder is its memory system. In this article we cover our rationale for prioritizing a memory system, technical details of how we built it, learnings from building the memory system, what the memory system enables, and discuss future work.

You can't build reliable agents without understanding how they reason, and you can't validate improvements without systematic evaluation.

An enterprise-ready AMD MI355X guide covering AI inference, LLM training, memory scaling, performance trade-offs, and deployment strategies.

Today, we're expanding what you can do with LangSmith Agent Builder. It’s an big update built around a simple idea: working with an agent should feel like working with a teammate.We rebuilt Agent Builder around this idea. There is now an always available agent (”

Learn how monday Service developed an eval-driven development framework for their customer-facing service agents.

Build production-ready agent workflows with a single prompt in Claude Code, Cursor, and GitHub Copilot.

TLDR: Our coding agent went from Top 30 to Top 5 on Terminal Bench 2.0. We only changed the harness. Here’s our approach to harness engineering (teaser: self-verification & tracing help a lot).The Goal of Harness EngineeringThe goal of a harness is to mold the

An enterprise-ready AMD MI355X guide covering AI inference, LLM training, memory scaling, performance trade-offs, and deployment strategies.

Deploy production agentic AI with public MCP servers on Clarifai. Includes Artifacts for versioned pipeline storage and Pipeline UI improvements. Available in Public Preview.

Every time LLMs get better, the same question comes back: "Do you still need an agent framework?" It's a fair question. We've now built three generations of them, and each one looked different from the last. So here's what we believe:

Interrupt - The Agent Conference by LangChain - is where builders come to learn what's actually working in production. This year, we're bringing together more than 1,000 developers, product leaders, researchers, and founders to share what's coming next for agents—and how

Thank you to Nuno Campos from Witan Labs, Tomas Beran and Mikayel Harutyunyan from E2B, Jonathan Wall from Runloop, and Ben Guo from Zo Computer for their review and comments.TL;DR:More and more agents need a workspace: a computer where they can run code, install packages, and access

Today, we're thrilled to announce that LangSmith, the agent engineering platform from LangChain, is available in Google Cloud Marketplace. Google Cloud customers can now procure LangSmith through their existing Google Cloud accounts, enabling seamless billing, simplified procurement, and the ability...

An enterprise-ready AMD MI355X guide covering AI inference, LLM training, memory scaling, performance trade-offs, and deployment strategies.

Memory isn't just a feature for AI applications—it's infrastructure. As agents scale, the limited loop of stateless interactions breaks down, and continuity becomes a systems problem that requires active maintenance.

An enterprise-ready AMD MI355X guide covering AI inference, LLM training, memory scaling, performance trade-offs, and deployment strategies.

2025 was a defining year for us at Weaviate. Instead of chasing shiny features, we focused on an overarching goal - upgrading our infrastructure and technology in order to better support AI systems.

By Chester Curme and Mason DaughertyAs the addressable task length of AI agents continues to grow, effective context management becomes critical to prevent context rot and to manage LLMs’ finite memory constraints.The Deep Agents SDK is LangChain’s open source, batteries-included agent harness. It p...

By Chester Curme and Mason DaughertyAs the addressable task length of AI agents continues to grow, effective context management becomes critical to prevent context rot and to manage LLMs’ finite memory constraints.The Deep Agents SDK is LangChain’s open source, batteries-included agent harness. It p...

Explore NVIDIA GH200 Grace Hopper superchip—architecture, AI use cases, benchmarks, and a decision guide for large-scale LLMs, HPC, and enterprise AI.