framework
Microsoft's open-source framework for building applications with multiple LLM agents that converse and collaborate to complete tasks.
An engineer writing on dev.to spent two weeks on prompts and a larger model before concluding that his ten-step agent workflow broke at the fourth handoff because one supervisor was holding every worker's output.
Reality
COGEXT's author pushed 150 samples from cookbooks, DEV posts and Hacker News through his own extractor. The unbiased 120 yielded one promise, and the 13 in the enriched set averaged 0.79 confidence with a single deadline between them.
Reality
A dev.to post argues that agents chaining tool calls fail as an architecture problem rather than a prompting one. Its confirmation gate on write tools holds even when the model's own confidence number is wrong.
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A dev.to teardown ran 107 I/O-bound data engineering tasks under a sub-15-second median and a one-cent-per-task budget. What it yields is a map of where each framework's abstraction gives way once the task count climbs.
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Durable execution restores orchestration state. It cannot untake a payment, a send, or a ticket, and no ranked feature table for AutoGen, CrewAI, LangGraph or Flowise closes that gap.
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A dev.to teardown describes a framework where the messaging adapter is the frame and the agent loop lives inside it. The session lane is where you pay for that choice.
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A single developer's capability layer for AI agents is pre-1.0 and self-reviewed. The primitive it argues for is still the floor: scoped, signed, dated, revocable, recorded.
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A field guide on dev.to describes a logistics agent that cleared 94% of test cases and 11% of 4,000 real tickets a day. The model was fine. Nobody designed the system around it.
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Graph engineering acquired guides and comparison tables within weeks of a tweet that was mocking the field's renaming habit. The tweet's author later called the hype silly.
Reality