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What happens when AI agents can find each other, communicate, negotiate, and work together?Continue reading on Medium »
In this article, you will learn the key differences between single-agent and multi-agent AI systems, and how to decide which architecture fits your problem. Topics...
Most production agent projects do not fail because the model is weak. They fail because one agent was asked to hold too much at once: routing, planning, tool use, memory, and error...
More agents. More coordination. More complexity. But is the result actually better?Continue reading on Medium »
A hands-on guide to defining specialist agents and coordinating their work in the Codex CLI The post From One Agent to a Team: Understanding Codex Subagents appeared first on Towar...
Most agent projects start the same way: one model, one prompt loop, three or four tools. That's the right place to start, and for a lot of workloads it's also the right place to st...
Multi-agent coding systems don't necessarily fail because agents can't communicate. They can fail because important commitments made in conversation have nowhere to live afterward....
Let the AI decide which agents to run — and run the right ones simultaneouslyContinue reading on Data Science Collective »
AI applications are rapidly moving from single-model applications toward systems composed of multiple specialized agents. One agent may specialize in weather information, another i...
The Agentic SOC needs two protocols, not one. Learn how MCP and A2A work together as the vertical and horizontal layers of multi-agent security operations
Bring multiple ACP-compatible agents into the conversations where your team already works with an open-source, self-hostable alternative to Claude Tag. The post AgentConnect -- the...
We have spent the last two years learning how to ground a single AI agent in enterprise data. That was the easy part. Coordinating a fleet of them turns out to be a different probl...
Multi-agent systems need deeper guarantees than fluent responses: they must select the right tools, respect constraints, and explain their decisions. Learn how to build a Strands-b...
Moving from static model assignment to intelligent, task-level LLM selection. The post Optimizing LLM Inference Costs in Multi-Agent Systems with Adaptive Model Routing appeared fi...
Huawei-backed openJiuwen has open-sourced AgentOS for Enterprise, a runtime for multi-agent swarms with sandboxes, tenant isolation and appliance deployment in hours.
Когда в работе появляется несколько независимых задач, возникает очевидная идея - "почему бы не поручить их разным AI-агентам одновременно, вместо того чтобы ждать, пока один агент...
Software agents are transitioning from conversational text generators into autonomous economic acto...
We built a nine-agent pipeline that turns a natural language use case into working code, an interactive preview, and an implementation guide in under 4 minutes. It serves roughly 8...
Stop struggling with LLM hallucinations. Learn the multi-agent patterns and infrastructure needed to build reliable, scalable AI systems in production. The post Mastering Multi-Age...
The history of agentic AI is a progression spanning more than seven decades of artificial intelligence research. Symbolic reasoning established computational problem solving, exper...
Here’s a quick strategy to manage multiple AI agents easily. (Don’t worry, it’s all one tool.)
Many teams build a multi-agent AI prototype in days but hit a wall in production. This post defines five production challenges (orchestration, per-agent model selection, reliable o...
Stop passing raw Markdown between AI agents. Here is how Entroly creates a Rust-powered, witness-verified control plane to halt…Continue reading on Medium »
When Codex is the right shape for the problem, when Claude Code is, and how I split 5 specialist agents between them on dense AI capacity work. The post When to Use One Model and W...
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