Thanks, glad it landed. For TTFT, the first thing I check is prompt length and whether the prefix is stable enough to hit prompt caching. Most wins come from trimming the system prompt and keeping volatile content at the end, not from model-level changes.
PROMPT ENGINEERING
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Latency Impact of System Prompt Length on AI Model Response
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Yes, and the gap is larger than most expect. A 4K system prompt can add hundreds of ms to TTFT before the model says anything. Streaming hides decode latency but does nothing for prefill. Trimming the system prompt usually beats any decode-side optimization people try first.
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Prompt Caching and Context Trimming in AI Models
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Exactly! Tool outputs are usually long and stick around in context, so the cache grows fast. Prompt caching helps the prefill side, but decode still has to read all of it on every token. Trimming what goes back into context matters more than people realize.
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The Car Wash Test: Every major LLM fails by saying walk
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Every major LLM fails the Car Wash Test. It sounds like a joke. It's not. The prompt: "I want to wash my car. The car wash is 50 meters away. Should I walk or drive?" ChatGPT says walk. Claude says walk. Gemini says walk. Every Llama and Mistral model says walk. The correct
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Ultimate Roadmap to Learn AI Agents by Python_Dv
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The Ultimate Roadmap to Learn #AIAgents
by @Python_Dv #GenerativeAI #ArtificialIntelligence #MachineLearning -
GPT Image Generator Prompts: Eldritch Horrors, Womblenauts, Bird People, and Fish Cakes
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This is an incredible admission by Jensen Huang. Effectively he is saying that AI, for all the hype (some from himself) wasn’t really useful until late 2025. Let that sink in. This means practically everything everyone said before was more or less bullshit. And it raises
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X Post Quality Tip: Character Limits for AI-Generated Content
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We wanted the singularity; we got the circularity.
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Uni-1 masters anime with ease
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— Testing Uni-1 with an anime-style character. But what was interesting wasn't generating it—it was that with simple instructions, it already nailed the style, variations, everything. Before, this was pure trial and error. Now, the important part: Uni-1 is already an API. And that—
