I put our Contextual Scaffolding Framework and OpenAI’s GPT-5 Prompting Cookbook into NotebookLM and asked it “What aspects of the gpt-5 prompting cookbook are most important to know in order to apply the contextual scaffolding framework most effectively?”
It gave me a sensible set of prompting strategies, so I told it to integrate them into an updated Contextual Scaffolding Framework for ChatGPT-5.
I’ve given the updates a cursory review; they look good apart from a reference to use of an API (Application Programming Interface) which is probably outside our scope. But it’s late; a proper review will have to wait for another day. Perhaps a job to do in collaboration with ChatGPT-5.
Is contextual scaffolding a worthwhile concept? The findings from some research with Perplexity suggest it is:
Contextual scaffolding is not only still applicable to ChatGPT-5, it is more effective and occasionally more necessary, due to ChatGPT-5’s increased context window, steerability, and the complexity of its reasoning capabilities. The consensus among thought leaders is that scaffolding remains best practice for directing AI behavior, ensuring relevance, and achieving quality outcomes in collaborative tasks. Leveraging both new features (custom instructions, preset personas, automatic reasoning mode selection) and established scaffolding techniques is recommended to get the best results. The trend is towards combining sophisticated context guidance with the model’s own adaptive reasoning for “human+AI” workflows.