• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: LLM frameworks

Multi-Agent Systems with LLMs: How Specialized AI Agents Collaborate to Solve Complex Problems
Multi-Agent Systems with LLMs: How Specialized AI Agents Collaborate to Solve Complex Problems

Tamara Weed, Oct, 8 2025

Multi-agent systems with LLMs use teams of specialized AI agents to solve complex tasks more accurately than single models. Learn how frameworks like Chain-of-Agents, MacNet, and LatentMAS work, where they're used, and the risks involved.

Categories:

Science & Research

Tags:

multi-agent systems LLM collaboration role specialization AI agents LLM frameworks

Recent post

  • Measuring GenAI Adoption: Telemetry, Surveys, and ROI Strategies
  • Measuring GenAI Adoption: Telemetry, Surveys, and ROI Strategies
  • Documentation First: Treat AI Output as a Draft That Needs Rationale
  • Documentation First: Treat AI Output as a Draft That Needs Rationale
  • Memory Footprint Reduction: Hosting Multiple Large Language Models on Limited Hardware
  • Memory Footprint Reduction: Hosting Multiple Large Language Models on Limited Hardware
  • Memory and Compute Footprints of Transformer Layers in Production LLMs
  • Memory and Compute Footprints of Transformer Layers in Production LLMs
  • Energy Efficiency in Generative AI Training: Sparsity, Pruning, and Low-Rank Methods
  • Energy Efficiency in Generative AI Training: Sparsity, Pruning, and Low-Rank Methods

Categories

  • Science & Research
  • Enterprise Technology

Archives

  • May 2026
  • April 2026
  • March 2026
  • February 2026
  • January 2026
  • December 2025
  • November 2025
  • October 2025
  • September 2025
  • August 2025
  • July 2025

Tags

vibe coding prompt engineering generative AI large language models Large Language Models AI coding tools AI governance data privacy transformer architecture LLM security AI compliance AI development AI coding assistants LLM optimization AI coding transformer models AI code security GitHub Copilot LLM deployment prompt injection

© 2026. All rights reserved.