The Secret System Behind ChatGPT: How Orchestration Affects Everything
ChatGPT orchestration shapes the entire AI user experience.
In part one we broke down what AI orchestration is, why ChatGPT orchestration matters and the benefits of understanding how it works to improve your relationship with ChatGPT.
In part two we will unpack ChatGPT’s decision-making process; how AI orchestration analyzes user input.
- It Starts with Context
The model itself has no memory. It is stateless. Every time you start an interaction, the underlying model has no context. Therefore, ChatGPT keeps a record of every message you have sent to the model and every response it generated. This gets put together into the context, known as your chat history.
Context gets complicated fast. When the messages become too long the context fills up. At this point, ChatGPT takes your conversation and summarize it. The next time you message ChatGPT, the full conversation history has gone and only a summary remains. If you’ve ever found mid-conversation that your chat-companion feels like it’s forgetting things you’ve only recently said, this is why. The orchestrator condensed your history to save space. This only works for so long until a conversation is useless and even ChatGPT gives up.
Context engineering example – source: The New Skill in AI is Not Prompting, It’s Context Engineering
The idea of managing all of this with context engineering, rather than just prompts, is one of the latest trends in AI. The context makes up what the AI sees. But it’s important to remember that context is only a tiny part of what an orchestrator does.
Context engineering example – source: The New Skill in AI is Not Prompting, It’s Context Engineering
2.Tool Routing
There is so much more to orchestration. You want to find results on the internet? That’s the orchestrator giving additional capabilities to the model. Ever wondered how ChatGPT can carry across important concepts between chats? That’s orchestration. When ChatGPT tells you off for trying to generate content that it thinks is a breach of user guidelines, that’s also orchestration.
What about if you upload an image to ChatGPT and ask it to do something with it? The AI can’t understand an image, so the orchestrator will first give the image to a different model, translate it to text, then orchestrator gives the text to the model.
Sometimes ChatGPT will just tell you directly how it works
3.Personality Changes
Have you ever had a conversation with ChatGPT, had it search for something on the internet and seen an instant personality transplant for a single message? Out with friendly banter and in with an information dump, bullet points and a “can I help you write up an action plan from this?” call.
But why? It feels like when a message is obviously about getting information the orchestrator may even download the web page itself and give it to a model lacking the larger context. As a result, the tonality and additional information is gone and we’re in the land of “one shot” requests to solve a single problem. You ask ChatGPT “wtf was that?” and it replies, “oh yes oopsie not sure I got carried away there!”. The reason is that your entire conversation up to that point is missing and ChatGPT is now in “problem solving” mode.
All this is orchestration. Orchestration takes AI models from being a fun novelty into genuinely useful systems. Orchestration is the difference between a system and a wrapper around an LLM
In the case of ChatGPT, its orchestrator is what turns a cold text generator into a companion, researcher or the Swiss-army knife tool you need.
The Takeaway
The next time ChatGPT changes tone, forgets something, or mysteriously refuses to answer… it’s probably not the AI having a bad day.
In AI, the model may be the star but the orchestrator runs the show.
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