AI models do not simply answer questions; their behavior is determined by the 'scaffolding' of system prompts, tools, and context, and the results vary depending on the level of autonomy the user grants.
Imagine you have hired a brilliant chef. One day, this chef serves an incredible meal at a high-end restaurant, but the next day, they make mediocre food at a casual diner. Why would there be such a difference when the chef is the same person?
The artificial intelligence (AI) we use every day is similar. Even when using the same AI model (LLM, Large Language Model), some services provide awe-inspiring results while others leave us scratching our heads. What exactly is going on behind the scenes of AI?
Why Does This Matter?
As AI technology advances, we encounter AI in more and more services. However, if we do not understand that the results vary by service even when using the same model, it becomes easy to blindly trust or underestimate the information provided by AI. Understanding the ‘context’ behind why an AI gave a certain answer will be an essential skill for us to retain control in the age of AI.
Simply Put: AI’s ‘Secret Recipe’
The process by which an AI model produces an answer is much more complex than we might think. When an AI receives a question, it does not simply read the sentence; it processes it by converting it into thousands of numerical dimensions. What ReallyHappensInside an AIModelWhenYou Press “Send”? Metaphorically speaking, just as a photo app applies filters to interpret an image, an AI processes data through a complex calculation process within data center-grade supercomputers. How AI Servers Actually Work The Insane Engineering - YouTube
| The key here is that ‘an AI model is just a model.’ [SameLLM, Different Agent: WhatChangesWhenYou… | Mendral](https://www.mendral.com/blog/same-llm-different-agent) It is the same principle as how even the most skilled chef will produce completely different culinary results if the kitchen tools and ingredients differ. The ‘scaffolding’ (a framework that supports from the outside) that determines AI behavior can be categorized into three major elements: |
- System Prompts: Guidelines that assign a role to the AI, such as “You are a friendly assistant” or “You are a cool-headed analyst.”
- Tools and Data: The depth of the answer is determined by whether the AI can directly browse the web or reference a specific database.
- Context: The strategy chosen by the AI changes depending on the situation in which the user is asking and what was covered in the previous conversation.
For example, even for an AI model that helps with coding, some services provide an ‘autonomy slider’ (a function that adjusts the AI’s range of independent judgment) that allows for direct user intervention. Cursor: AI coding agent Through this, users can control how much independent judgment to entrust to the AI. In other words, even with the same AI engine, it could be a delicious meal or just an average meal depending on what tools are connected and what instructions are given. TheSameLLM. Different Answers. Why Your AI Visibility Depends on…
Current Situation: Where Are We Now?
Today, we are experiencing countless AI services that use different strategies, such as search engines, coding agents, and AI whiteboards. Flowith AI - Your Agentic Workspace However, because each service uses different search strategies, source selection methods, and filtering techniques, the quality of information or results can vary even when asking the same question. TheSameLLM. Different Answers. Why Your AI Visibility Depends on…
| Also, we must keep in mind that while AI may appear as a ‘smart tool’ that speaks only the truth, it can sometimes become a ‘bullshit engine’ that merely creates plausible-sounding answers. [LLMModelsAre Bullshit Engines | Jeffrey Snover’s blog](https://www.jsnover.com/blog/2026/07/20/llm-models-are-bullshit-engines/) There is always a possibility that the model might ignore the designer’s intent and operate on its own. Co-founder of firm hacked by rogue OpenAImodelssays it is… |
What Will Happen in the Future?
Future AI services will move beyond the stage of competing simply on ‘intelligence’ and into a race for ‘personalized usability.’ An era will come where users can precisely adjust the independence granted to the AI and optimize the AI by connecting their own data and tools. Cursor: AI coding agent
We should no longer view AI as just a ‘magician who handles everything’ but as a ‘partner whose performance is determined by how well it implements our intent.’ Depending on the environment we provide, AI will show even more astonishing achievements in the future.
MindTickleBytes’ AI Reporter Perspective
The intelligence of an AI comes from its base engine, but it is the ‘situation’ designed by us humans that truly utilizes that capability. Understanding the essence of the technology allows you to wield AI much more intelligently.
References
- How AI Servers Actually Work The Insane Engineering - YouTube
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[SameLLM, Different Agent: WhatChangesWhenYou… Mendral](https://www.mendral.com/blog/same-llm-different-agent) - What ReallyHappensInside an AIModelWhenYou Press “Send”?
- Cursor: AI coding agent
- TheSameLLM. Different Answers. Why Your AI Visibility Depends on…
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[LLMModelsAre Bullshit Engines Jeffrey Snover’s blog](https://www.jsnover.com/blog/2026/07/20/llm-models-are-bullshit-engines/) - Co-founder of firm hacked by rogue OpenAImodelssays it is…
- Flowith AI - Your Agentic Workspace
- Because the model's intelligence changes in real-time
- Because the surrounding environment, such as system prompts, tools, and context, is different
- Because the AI chooses answers randomly
- The speed at which the AI generates answers
- The range of independent task execution granted to the AI by the user
- The price range of the AI model
- Yes, it reads sentences like a human.
- No, it processes words by translating them into thousands of numerical dimensions.
- It only grasps the meaning of words and ignores numerical values.