#cross-agent state sharing
6 related articles
Expert Opinions·2 min
Cross-Agent State Sharing: A More Practical Context Solution Than Memory Management
Analysis of context fragmentation in multi-Agent collaboration, comparing memory vs. state management approaches, and how tools like Opal Bridge enable seamless switching between Claude Code, Codex, and other Agents.
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·2 min
Forge: Adding Reliability Guardrails to Local Model Tool Calling
Forge is an open-source Python middleware for local models (Ollama, llama.cpp, vLLM) that boosts tool-calling reliability via three-layer guardrails: validation, rescue parsing, and retry.
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·5 min
The Definitive Guide to Claude Code: Core Methodology and Best Practices for Agentic Programming
A deep dive into Claude Code, the definitive course from DeepLearning.AI and Anthropic: from agentic principles and context optimization to three hands-on cases—RAG chatbot, Figma-to-frontend, and data analysis. Master AI-assisted coding methodology.
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·7 min
AI Agent Development: A Four-Stage Competency Model from 15K to 40K RMB Salary Growth Path
A detailed four-stage competency model for AI Agent development: from Python/RAG basics (15K) to workflow orchestration (20K), inference optimization (30K), and Agent cluster governance (40K RMB).
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Tutorials·3 min
Enterprise Multi-Agent Development: Low-Code Platforms vs. Hand-Written Code — An In-Depth Comparison
In-depth comparison of two enterprise multi-agent development approaches: low-code platforms like Dify vs. hand-written code with LangGraph. Covers efficiency, flexibility, security, and prompt injection defense strategies.
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Product Reviews·2 min
PaperClip + Claude Code Multi-Agent Coordinated Development in Practice: Full Workflow Demo of an AI Virtual Team
Hands-on demo of building a multi-Agent development team with PaperClip and Claude Code, featuring Delivery Lead, Frontend/Backend Engineers, QA, and Code Reviewer roles in a full AI-automated development workflow.
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