Understanding Model Behavior on Signal & Syntaxhttps://tomarcher.io/learningpaths/understanding-model-behavior/Recent content in Understanding Model Behavior on Signal & SyntaxHugoen-usMon, 09 Feb 2026 06:00:00 -0700How Large Language Models (LLMs) Know Things They Were Never Taughthttps://tomarcher.io/posts/how-large-language-models-know-things-they-were-never-taught/Mon, 09 Feb 2026 06:00:00 -0700https://tomarcher.io/posts/how-large-language-models-know-things-they-were-never-taught/When you ask an LLM without web search enabled a question like “What happened in the news this morning?”, the LLM will respond by telling you that it doesn’t have access to current events and suggest you check a more current news source such as Reuters or Google News. Conversely, ask an LLM with web search enabled the same question, and you receive a detailed rundown of breaking stories, political controversies, and sports news from the past 24 hours.Temperature and Top-P: The Creativity Knobshttps://tomarcher.io/posts/temperature-top-p-creativity-knobs/Wed, 24 Dec 2025 12:00:00 -0800https://tomarcher.io/posts/temperature-top-p-creativity-knobs/Every API call to ChatGPT , Claude , or any other LLM includes two parameters most people either ignore or tweak randomly: temperature and top-p. The defaults work fine for casual use, so why bother understanding them? Because these two numbers fundamentally control how your model thinks. The temperature value determines whether the model plays it safe or takes creative risks while the top-p value decides how many options the model even considers.