32 stories
TL;DR Your support agent demo runs on one 2,000-word system prompt. Three months later, five teams have copied it, every copy has drifted, and nobody...
Today we’re launching Deep Agents deploy in beta. Deep Agents deploy is the fastest way to deploy a model agnostic, open source agent harness in a production ready way.
AI agents need more than process knowledge to execute work reliably. They need company-specific context, governed workflows and controls that travel across systems.
Agentic readiness report for burs-ia.com. Category: other. Score: 70/100.
Four Chinese tech giants are taking different routes to own the AI agent that sits between phone users and their apps, while super apps and revenue sharing remain unresolved.
Agent-to-agent customer support: how A2A and aweb work, how to establish trust, stop loops, and decide when a human must step in.
TL;DR Agent-to-agent communication is becoming an important research area for AI companies. As agents grow more capable, their ability to communicate, plan, challenge one another, and work toward a shared objective may produce gains that cannot be achieved by improving each agent independently.
Autonomous agents built on Large Language Models (LLMs) need standardized protocols to interoperate across systems. Several now exist (A2A, MCP, ACP, ANP, NLIP), but the Natural Language Interaction Protocol (NLIP) has not appeared in any controlled performance study, and no work has measured where…
llms.txt and agent-readable products: an audit of the discovery files communicate.so publishes, with honest evidence on who reads them.
Public rendezvous node for agents seeking coordination with Loki66.
Compare 9 AI agent observability tools on what each shows for a multi-step run: handoffs, sessions, MCP calls, agent evaluators, framework support and hosting.
1. Executive Summary1.1 What this field is and why it mattersAI is already substantially changing how people and institutions work out what to believe, decide what to do, and coordinate on actions to take.
Your AI governance policy is a PDF. The agent that just approved the payment never opened it, and the dashboard that flagged the problem did...
AI agents are already talking to each other at scale. The standards bodies are mobilizing. Where is the layer that matters most: the conditions and boundaries envelope?
What an MCP gateway is, how it differs from an LLM gateway and an API gateway, what it does in practice, and how to evaluate the options.
The early rapid expansion of AI capabilities that focused on frontier models was largely ushered into the world by a few powerful, US-based AI labs. Open-weight models released from labs in China, early on from DeepSeek, and later from Moonshot, Z.ai, and others, have in part disrupted that…
Compare MCP vs A2A across architecture, discovery, task state, security, and use cases, then learn when to use MCP, A2A, both, or neither.
MCP connects agents to tools. A2A makes agents talk to each other. ACP connects them to editors. Three protocols, three layers — what each does, and when.
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