Dual-Mode Intelligence
Switch seamlessly between "Thinking Mode" for complex tasks and "Non-Thinking Mode" for rapid responses. This flexibility empowers developers to tailor AI behavior to specific needs, enhancing both performance and user experience.
PROMPT ENGINEERING
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Dual-Mode Intelligence Switching for AI Performance
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XML Prompts Remain Superior for Serious LLM Practitioners
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Sorry, but it's not. I've been prompting/fine-tuning LLMs since 2019, and have tried just about everything, ran tests, etc. etc. There's a reason most serious practitioners use XML prompts for almost everything.
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Tool Call ID Mismatch Errors Fixed in AI Framework
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It's SO good, and doesn't break with annoying tool call ID mismatch errors
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Building Custom AI Tools Without Built-in Tool Calling
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This is what I do! I just build it myself instead of relying on built-in tool calling 🙂
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Optimized Prompts for Advanced AI Models
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Oh, I meant that that looked like an optimized-for-o3 prompt!
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Igor Taber leads insane second round with AI Matt
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Thankfully @igorTaber was just as insane as me and led our second round after chatting with AI Matt!
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Structured Output Limitations in AI Systems
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JSON output != JSON input I've had quite bad luck w/ forced structured outputs in general though
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Structured Tags in AI: From Simple to Complex Use Cases
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Our use cases range from extremely simple (i.e. output three options in tags) to absurdly complex (super nested tags with counters, metadata, etc.) Prompt clearly, and it'll work.
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Prompt engineering beats validation libraries for reliable outputs
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We don't really. It just works. I've seen so many validation libraries and techniques come and go, but most serious builders I know don't bother with them. They're essentially just nerd traps. Prompt the model well, and it'll output the right format 99%+ of the time.
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Using XML for Prompt Engineering Techniques
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We actually use XML for writing prompts 🙂 There are ways to get it in the right space, just needs a bit of exploration!