By skyforbes A deep dive into how token limits, model behavior, and prompt structure silently sabotage your conversations — and how to take back control with smart prompt engineering.
The Night the Response Vanished
It was 1:42 a.m. when Arjun finally leaned back in his chair, staring at his glowing screen.
For the last three hours, he’d been crafting a complex prompt for ChatGPT — a carefully structured instruction set designed to generate a 50-page technical spec for his startup’s new API.
He hit “Enter.”
The familiar typing dots appeared. Lines of clean Markdown documentation began to unfurl like magic.
Section after section flowed smoothly — authentication, endpoints, data models, examples. Arjun smiled. This was going to save him days of work.
And then… it stopped.
Mid-sentence. Mid-JSON.
The last line read:
"pagination": {
"type": "cursor",
"cursor_param": "next_cursor",