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eagleeyethinker

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1 ポイント·投稿者 eagleeyethinker·2 か月前·0 コメント

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1 ポイント·投稿者 eagleeyethinker·2 か月前·0 コメント

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1 ポイント·投稿者 eagleeyethinker·5 か月前·0 コメント

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1 ポイント·投稿者 eagleeyethinker·5 か月前·0 コメント

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1 ポイント·投稿者 eagleeyethinker·5 か月前·0 コメント

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1 ポイント·投稿者 eagleeyethinker·6 か月前·0 コメント

Decision AI is the engine. GenAI is the interface. Agents are the operators

eagleeyethinker.substack.com
1 ポイント·投稿者 eagleeyethinker·6 か月前·1 コメント

Stop Calling Everything an AI Agent

eagleeyethinker.substack.com
4 ポイント·投稿者 eagleeyethinker·6 か月前·1 コメント

コメント

eagleeyethinker
·5 か月前·議論
IDEs have changed. Dramatically. They’re no longer just code editors. Today’s enterprise teams operate across four types of IDEs: 1. Traditional IDEs 2. Cloud IDEs 3. IDEs with Embedded AI 4. Agentic IDEs Each solves a different problem – stability, collaboration, productivity, and automation. The real future? A hybrid IDE strategy.
eagleeyethinker
·5 か月前·議論
Most machine learning stories about logistic regression spend too much time on bells and whistles — math formulas or “accuracy numbers” you’ll never see in production. What actually makes logistic regression useful in real systems isn’t the math itself — it’s what the model forces you to think about.
eagleeyethinker
·6 か月前·議論
Most companies are building chat interfaces and calling it “AI strategy.” The real value is in decision engines: models that prioritize, classify, forecast, and optimize. This post breaks down the real stack: Decision AI as the engine, GenAI as the UI, and agents as the control layer that connects them.