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Stop Telling Your AI What Format You Want. Start Writing It.

You ask the model for a JSON object. Your parser gets this: Certainly! Here's the JSON you asked for: {"severity": "high", "summary": "Login fails after password reset"} Let me know if you'd like me…

  • Seed desired format directly into model's response to avoid extraneous phrases.
  • Utilize API features like structured output or JSON mode for better control.
  • Implement validation to ensure generated output conforms to specified format.

Stop Using LLMs Like Search Engines

Most devs use modern language models wrong. They open a chat window, paste an error stack trace, and wait for a magic snippet. When it works, they celebrate.

  • LLMs are spatial compressors of human text, not search engines.
  • Treating LLMs like APIs requires explicit architectural constraints and data types.
  • Building domain-specific wrappers with internal documentation improves results.

Semantic Caching and Live Internet Search: Tools That Let AI Cache Answers to Save Money, and Pull Data From the Web When It Needs To

Say you open the logs of your chat system and they are full of questions like these: "How do I change my password?" "Forgot my password, what do I do?" "Where do I reset my password?" All three mean…

  • Semantic caching saves costs by remembering answers to similar questions.
  • Live internet search provides real-time data when needed.
  • Two methods work together with a sorting step to determine appropriate approach.

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