
Choosing an AI Tool
You have three tabs open. ChatGPT in one, Claude in another, Gemini in the third. You paste the same question into all three, and you get three different…
Read tutorialManaging sensitive information and disclosure risk when supplying data to LLM services or processing it in LLM applications.
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You have three tabs open. ChatGPT in one, Claude in another, Gemini in the third. You paste the same question into all three, and you get three different…
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The first prompt is not a test of Claude. It is a test of whether you described the task.
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The "local is more private, cloud is more powerful" story sounds clean. It's also too simple to make a good decision with.
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Most people picture "AI for business" as one magic assistant that can handle anything you throw at it. That picture is wrong in a useful way. LLMs in…
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A team wants to prove that minimization is safer. So they multiply two numbers they invented, get a smaller product for the minimized option, and present…
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You do not need the best model. You need the model that matches the control you actually require.
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Most beginners pick an AI setup the way they pick a restaurant: the one that sounds best, then hope the bill and the wait are tolerable. Then the…
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The cursor is blinking in the paste box. You have a real task, a real dataset, and no rule that clearly says yes or no. This article is a set of reps for…
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Most people agree with data minimization right up until the moment the task needs context. Then the full customer email goes into the chat window, because…
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A cache hit returns in 40 milliseconds, reads fluently, and is wrong. Nothing in the response text tells you that. Only the metadata sitting beside it can.
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You have a real document you want an LLM to help with—maybe a customer support ticket, a contract, or a set of notes. It's full of useful context. It's…
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You're staring at a chat window. You've drafted a prompt that would save you an hour of work—if you paste in the real document. The cursor blinks. Your…
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