#multi-agent AI design
1295 related articles
·4 min
Teaching AI to Have "Taste": Exploring Multi-Agent Design with Open-Source Skill Taste
Why does AI-generated UI all look the same? Designer SEN open-sourced a Skill called Taste that uses a four-agent pipeline to reverse-engineer website "taste" into verifiable design principles called Taste DNA.
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·3 min
The Deterministic Factual Substrate for Multi-Agent AI: A Deep Dive into Knowledge Kernel's Reproducible Grounding Design
A deep dive into how Knowledge Kernel builds a deterministic factual substrate for multi-agent AI through layered decoupling of reality, evidence, facts, and reasoning — with dataset_hash fingerprinting, atomic reloads, and observable telemetry.
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·2 min
GLEE Competition: A Detailed Guide to the NeurIPS 2026 Official Negotiation AI Challenge
NeurIPS 2026 GLEE Competition challenges AI agents to negotiate in real-time via natural language, covering bargaining, persuasion, and game strategies. Full guide on rules, approaches, and prizes.
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·2 min
Finyuus: A Deep Dive into the Code-First AI Workflow Governance Language
Deep dive into Finyuus, an open-source code-first AI workflow governance language built on Temporal with agent orchestration, Guards, human approvals, and Langfuse observability.
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·3 min
GitHub Daily · August 5: AI Agents Enter the 'Production Engineering' Era
GitHub Trending Aug 5: AI Agents shift from demos to production with new projects for state management, long-term memory, skill systems, and security.
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·3 min
Agentic Loop in Practice: Lessons from 86 AI Agents Building a GTA 6 Prototype in 22 Hours
A developer used an Agentic Loop with 86 AI agents over 22 hours to build a GTA 6-style 3D game prototype from scratch. Key insights on structured JSON debugging, multi-agent orchestration, and AI coding boundaries.
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·3 min
Mu: A Standardized Toolset Platform Designed for AI Agents
An in-depth analysis of Mu, a toolset platform built for AI Agents, exploring the importance of Agent tooling, Mu's design philosophy, competitive landscape, and its value in AI deployment.
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·3 min
Xberg v1 Open-Source Document Extraction Engine: CPU-Only Local Processing Supporting 101 Formats
Xberg v1 is an MIT-licensed open-source local document extraction engine. CPU-only, supporting 101 formats with built-in SPLADE and ColBERT retrieval, Rust-powered for RAG and ML pipelines.
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·3 min
MCP Session Analytics: Building Production-Grade Observability and Evaluation for AI Agents
How to build product analytics and evaluation capabilities for AI Agents at the MCP protocol layer, covering session-level tracing, tool call observability, and quality Evals.
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·3 min
How Large a Software Project Can AI Complete Independently? Capability Boundaries and Human-AI Collaboration Models
Analysis of AI programming tools' limits for independent software projects, covering context windows, architectural consistency, long-range planning constraints, and optimal human-AI collaboration patterns.
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·2 min
Murmell: A Cloud Canvas Tool for Multi-AI Agent and Team Collaboration
Murmell is a cloud-first AI collaboration tool supporting Claude Code, Codex and other agents running simultaneously, using file claiming to resolve conflicts, with all output committed to Git.
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·2 min
Tempest Open-Source Tool: Reduces Token Consumption by 64% for Parallel AI Coding Agents
Tempest is an open-source developer tool that reduces token consumption by up to 64% for parallel AI coding agents through shared code understanding and isolated workspaces.
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·3 min
Token Economics: The New Unit of Value Measurement in the AI Era
Deep dive into how Tokens evolved from a technical concept in LLMs to the core unit of measurement in the AI economy. Exploring Token consumption explosion, cost optimization, and Token economics.
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·2 min
Can OpenAI's Most Powerful Agent Independently Run a Business? Real-World Testing Reveals the Answer
OpenAI's top AI Agent was stress-tested in real business scenarios to see if it could independently run a company. The experiment reveals agent capabilities and limitations in decision-making, memory, and strategic planning.
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·4 min
Walsh Multi-Agent Trading System: How Risk Management Veto Power Ensures AI Autonomous Decision-Making Safety
Deep dive into the Walsh multi-agent trading system architecture, exploring how its risk management agent with veto power establishes safety boundaries for AI autonomous decision-making.
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·3 min
Deep Dive into Gemini Robotics ER 2: Breakthroughs in Video Understanding and Multi-Robot Collaboration
Deep analysis of Google Gemini Robotics ER 2's three core breakthroughs: video understanding, tool orchestration, and multi-robot collaboration, exploring how embodied reasoning drives robots from passive execution to autonomous intelligence.
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·3 min
Kopai: Turn Your Expertise into AI Agents and Earn Passive Income from Knowledge
Kopai is a no-code AI agent platform where experts upload knowledge to publish sellable AI agents, with per-message billing and 70% revenue share for creators.
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·2 min
Cogpit: A Self-Hosted Web Monitoring Console for Remote AI Coding Agents
Cogpit is an open-source self-hosted Web UI for remote Claude Code and Codex AI coding agents. Monitor in real time, manage multiple machines, and respond to permissions without SSH.
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·5 min
Tandem: A New Species Reinventing Office Leasing Brokerage with AI
Tandem is an AI-native office leasing brokerage using agentic AI to provide brokers with real-time listings, deal analytics, and landlord flexibility insights, transforming market intelligence from personal experience into system capability.
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·3 min
Building a GitHub Code Review Bot from Scratch: A Hands-On Guide to AI Agent Automation
A detailed guide on building a GitHub code review bot from scratch, covering cloud deployment, secure sandboxes, Vercel AI SDK, and multi-agent collaboration for automated development workflows.
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