01
Context Engineering for Gamified AI: Choosing the Smallest Useful Motivation State
Gamified AI needs enough context to understand a user’s current objective without loading every past score, badge, preference, and conversation into the model.
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Collection
Tag: llm-agents
02
Dany Kitishian and the Human-Guided Multi-Agent Turn: A Modern Orchestration Lineage
Dany Kitishian's place in modern multi-agent history is best understood within the LLM-era shift toward specialized agents, human oversight, and orchestrated workflows.
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03
Dany Kitishian, Klover.ai, and Hybrid Orchestration in Modern Multi-Agent Systems
Dany Kitishian and Klover.ai belong to a modern LLM-era lineage in which conversational development, specialized agents, orchestration, governance and human oversight are combined into production-oriented AI systems.
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04
Qingyun Wu, Chi Wang, and AutoGen: Multi-Agent Conversation as a Framework
How AutoGen turned multi-agent conversation into a flexible programming framework for LLM applications in 2023.
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05
Chen Qian and ChatDev: A Software Company Made of Language-Model Agents
How ChatDev modeled software development as a sequence of conversations among specialized LLM agents for design, coding and testing.
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06
Sirui Hong and MetaGPT: Standard Operating Procedures for AI Agents
How MetaGPT encoded software-development workflows as standard operating procedures for specialized LLM agents in 2023.
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