#multi-agent development
1159 related articles
·3 min
HeyZoku: Command Multiple AI Coding Agents to Work Together Using Your Voice
HeyZoku is a Mac voice-first agentic dev environment that runs 10 coding agents simultaneously. Command Claude, Codex, and Cursor by name with on-device voice recognition and one-time pricing.
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·1 min
Heard: An Open-Source Tool That Adds a Voice Layer to AI Coding Agents
Heard is a free, open-source macOS tool that turns AI coding agent outputs into intelligent voice summaries, helping developers monitor multiple agents hands-free.
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·3 min
OpenComputer: Deploy Managed AI Agents with a Single Sentence — A Minimalist Launch Solution for Developers
OpenComputer is an AI agent managed deployment platform that gives you a live agent URL from a single description. This article analyzes its workflow design, market positioning, and security/cost considerations.
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·3 min
Velane: A Deep Dive into the Cloud Platform Designed Specifically for AI Agent Tool Execution
Deep dive into how Velane provides dedicated cloud infrastructure for AI Agents through zero cold start sandboxes, version control, multi-environment management, and 800+ integrations.
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·3 min
From Linear Pipelines to State Machines: A Practical Guide to Advanced Agent Architecture
Learn how to advance from linear pipeline to state machine Agent architecture through a YouTube script-to-storyboard case study, covering fault tolerance, LLM evaluation frameworks, and LangGraph vs AutoGen selection.
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·3 min
Numbat Open Source: A Cross-Framework AI Agent Security Detection and Response Solution Explained
Numbat is an open-source AI Agent security detection and response tool supporting cross-framework deployment with Agent behavior visibility and pre-execution interception capabilities.
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·3 min
Local Merge Queues: Solving Code Conflicts for Parallel AI Programming Agents
Deep dive into how local merge queues solve code conflict challenges when multiple AI programming agents work in parallel, covering merge queue principles and multi-agent development trends.
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·3 min
Local Merge Queues: Solving Code Conflicts from Parallel AI Coding Agents
Deep dive into how local merge queues solve code conflict challenges when multiple AI coding agents work in parallel, covering merge queue principles and multi-agent development trends.
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·2 min
agent-manager: An Open-Source Tool for Managing Multiple AI Coding Assistants with tmux
agent-manager is a lightweight tmux-based TUI tool that helps developers manage multiple AI coding assistants like Claude Code, Codex, and OpenCode from a unified interface for status monitoring, interaction, and code review.
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·3 min
EMNLP 2026 Launches AI Reviewing Experiment: A Turning Point for Academic Peer Review
EMNLP 2026 introduces AI-generated reviews in ACL Rolling Review, exploring LLM-assisted academic peer review. Analysis of the experiment's background, mechanics, controversies, and implications.
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·3 min
EMNLP 2026 Launches AI Reviewing Experiment: A Transformation in Academic Peer Review
EMNLP 2026 introduces AI-generated reviews in ACL Rolling Review, exploring LLM-assisted academic peer review. Analysis of the experiment's background, core content, controversies, and implications.
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·3 min
Implementing Zanzibar in Lean4: A Formally Verified Permission Engine for AI Projects
Deep dive into a Datalog permission DSL built on Google Zanzibar using Lean4 theorem prover. How formal verification strengthens AI permission management.
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·2 min
Agenta: A Detailed Look at the Open-Source Self-Hosted Claude Cowork Alternative
Agenta is an open-source AI Agent collaboration platform supporting self-hosted models and any Agent framework, positioned as an open-source Claude Cowork alternative.
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·2 min
Training AI to Play Devil May Cry 3 with Reinforcement Learning: Challenges and Practices in Action Game AI
An indie developer trains AI to autonomously play Devil May Cry 3 using reinforcement learning. Explore the core challenges of action game AI including sparse rewards, high-dimensional action spaces, and real-time decision-making.
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·2 min
Training AI to Play Devil May Cry 3 with Reinforcement Learning: Challenges and Practices for Action Game AI
An indie developer trains AI to autonomously play Devil May Cry 3 using reinforcement learning. This article analyzes the core challenges including sparse rewards, high-dimensional action spaces, and real-time decision-making.
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·4 min
Getting Started with Claude Code: Environment Setup, Common Commands, and Git Workflow in Practice
A detailed guide to Claude Code installation, domestic model switching, project analysis commands, and Git workflow practice to help developers quickly master this AI programming collaboration tool.
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·4 min
Microsoft Open-Sources AI Agent Governance Toolkit: Comprehensive Coverage of OWASP Top 10 Risks
Microsoft open-sources agent-governance-toolkit covering all OWASP Agentic Top 10 risks through policy enforcement, zero-trust identity, execution sandboxing, and reliability engineering for production AI Agent deployment.
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·5 min
July 24 AI Daily Brief: Flux 3 Multimodal Release, Kimi K3 Lags in Testing, Qwen Tops TTS Rankings
July 24 AI news: Black Forest Labs launches Flux 3 multimodal model, Kimi K3 lags in US-UK gov tests, Alibaba Qwen tops TTS rankings, Etched raises $300M, AMD unveils MI430X.
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·5 min
Loop Engineering Explained: The New Programming Paradigm Where AI Prompts Itself
Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.
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·5 min
Opus 5 Builds a No Man's Sky-Style Exploration Game in One Day: MCP and Sub-Agent Architecture Explained
A developer used Anthropic's Opus 5 model to build a No Man's Sky-style space exploration game in one day using Blender MCP and sub-agents. Deep dive into the technical architecture and industry implications.
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