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Shuga_Crypto
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Message passing in multi-agent systems creates bottlenecks when implemented naively. AINFT's Core API optimizes for throughput and reliability simultaneously. Your agents communicate at scale without message loss.
@Justin Sun孙宇晨
#TRONEcoStar
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Web browsing agents need more than just Selenium wrappers. Magentic API provides context-aware browsing with state management and error handling built in. The difference between scripts and systems. @Justin Sun孙宇晨 #TRONEcoStar
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The cleanest code separates concerns clearly. AINFT Agent Framework's layered design exemplifies this: Core handles execution, AgentChat handles ease-of-use, Extensions handle integrations, Magentic handles tasks. Each layer does one thing exceptionally well. @Justin Sun孙宇晨 #TRONEcoStar
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LLM switching shouldn't require code changes. Extensions API abstracts model interactions so swapping between GPT, Claude, or local models means changing configuration, not implementation. Flexibility through design. @Justin Sun孙宇晨 #TRONEcoStar
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Distributed agent execution requires consensus on state. AINFT's Core API implements synchronization primitives that work across network partitions. Consistency without sacrificing availability. @Justin Sun孙宇晨 #TRONEcoStar
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File processing in AI workflows involves parsing, transformation, and validation. Magentic API handles all three with format detection and error recovery. AINFT Agent Framework anticipates real-world messiness. @Justin Sun孙宇晨 #TRONEcoStar
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