#sub-agents
283 related articles
·2 min
GPT-5.6 Used 64 Sub-Agents to Tackle a Graph Theory Conjecture — How Far Are We from a Real Proof?
GPT-5.6 Soul Ultra used 64 parallel sub-agents to generate a proof draft for the Cycle Double Cover Conjecture in one hour. We break down the multi-agent pipeline and explain what's still missing before this counts as a real mathematical result.
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·3 min
Claude Code Workflow in Action: 68 Sub-Agents Working Concurrently
Hands-on test of Claude Code's Workflow mode with 68 concurrent sub-agents. Covers setup, write-review separation, real concurrency results, and token costs.
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·3 min
Claude Code Dynamic Workflows: Orchestrating Hundreds of Sub-Agents Working in Parallel
Deep dive into Claude Code Dynamic Workflows: enable parallel sub-agent orchestration via three methods for multi-agent collaboration and automated pipelines.
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·4 min
Pi Coding Agent Deep Configuration Guide: A Complete Breakdown of Custom Tools, Sub-Agents, and the Skill System
A complete Pi Coding Agent configuration guide refined over two months, covering custom tools, sub-agents, persistent memory, security, and skill systems.
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·2 min
The Right Way to Use Claude Code Sub-Agents: 3-5 Beat 100 Every Time
Deep dive into Claude Code Sub-Agent mechanics: from 5 built-in Agents to custom configs, comparing ECC, Superpowers, and GizTech community solutions.
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Deep Dives·3 min
Claude Sub-agents vs Agent Teams: How to Choose Between Two AI Multi-Agent Collaboration Patterns
Deep comparison of Claude sub-agents vs agent teams: architecture differences, use cases, and real-world results. A Pokémon RPG case study shows how agent teams achieve 95%+ feature completeness.
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Tech Frontiers·3 min
Claude Code Sub-Agents and Cursor BugBot Launch: AI Programming Tools Get Major Upgrades
Anthropic adds custom sub-agents to Claude Code, Cursor launches code review Agent BugBot, Qwen releases 92-language translation model, and Google unveils three experimental AI products.
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·3 min
Kimi K3 Hands-On Tutorial: Claude Code Sub-Agent Configuration & GPT-5.6 Comparison Test
Complete guide to configuring Kimi K3 as a Claude Code sub-agent, including API setup, YFlow workflow building, and head-to-head comparison with GPT-5.6 and Claude Fable 5.
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·4 min
Harness Engineering: The Core Infrastructure for Taking AI Agents from Demo to Production
Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to go from demo to production.
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·4 min
Harness Engineering: The Core Infrastructure for Taking AI Agents from Demo to Production
Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to reach production. Based on Scott Moss's workshop.
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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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·4 min
GPT-5.6 Value Maxing Practical Guide: From Token Stacking to Output Optimization Methodology
Deep dive into OpenAI GPT-5.6 Value Maxing strategies covering Sol/Terra/Luna model selection, KV cache optimization, Prompt compression, and programmatic tool calling to help developers achieve more output with fewer Tokens.
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·4 min
Kimi K3 Deep Dive: 2.8 Trillion Parameter Open-Source Model Closes the Gap with Closed-Source Frontier for the First Time
Moonshot AI releases Kimi K3 open-weight model with 2.8T parameters and 1M token context. Our deep dive covers coding, 3D dev, agent capabilities, and safety concerns.
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·3 min
Why Kimi K3's Open-Source Model Has OpenAI and Anthropic Running Scared
Deep analysis of the AI industry shockwave triggered by Kimi K3: the double standard behind distillation accusations, performance comparisons with GPT-5.5, real security concerns, and how open-source models threaten closed-source giants.
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·3 min
Why Kimi K3's Open-Source Model Has OpenAI and Anthropic Running Scared
Deep dive into why Kimi K3 is rattling OpenAI and Anthropic: distillation double standards, GPT-5.5 comparisons, real security risks, and how open-source models threaten closed-source business models.
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·3 min
From Frontend to Agent Development: A Complete 6-Week Systematic Learning Path
A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.
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·5 min
Complete Breakdown of Core Competencies for AI Agent Engineers: From Demo to Production-Grade Systems
Deep breakdown of 4 core AI Agent engineer competencies: business decomposition, multi-Agent architecture, quantitative evaluation, and engineering delivery—bridging the gap from Demo to production.
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·5 min
From Chat to Agent: Automating Your Entire Business Workflow with AI Agents
Veteran AI practitioner Remy breaks down the leap from chat models to AI agents: how agents work, the three pillars of context, tools, and skills, MCP connections, and hands-on architecture to make you a 100x employee.
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·4 min
Claude Code from Scratch: A Complete Guide from Installation to Enterprise-Grade Development
A complete guide to Claude Code from beginner to enterprise practice: covering CLI installation, connecting domestic LLMs via CC Switch, basic commands, Git workflow integration, automated bug fixing, and engineering capabilities like MCP and SubAgents.
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·3 min
Context Engineering: Why Does More Context Make AI Dumber?
Anthropic introduces Context Engineering, revealing Context Rot: the more tokens in the window, the worse AI retrieval accuracy. Learn the three principles, just-in-time retrieval, and three moves against context overflow.
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