The era of writing elaborate prompts for AI is giving way to loop engineering, a technique where the system self-evaluates and corrects itself in cycles until it achieves a precise result. For the average user, this means chatbots will be more autonomous and efficient, eliminating the need to master the art of asking good questions.
How Cyclic Self-Evaluation Works in Current Models 🤖
Loop engineering operates through an iterative process: the AI generates a response, analyzes it for errors or inconsistencies, and adjusts its output in successive rounds. This requires high token consumption, since each correction cycle involves processing and generating more data. Platforms like OpenAI or Anthropic are already exploring this architecture to reduce human intervention, although the computational cost grows significantly.
The Luxury of Not Thinking: Chatbots That Answer Themselves 💡
Soon you will be able to ask the AI for a market analysis without worrying about phrasing the exact question. The system will correct itself until the result is acceptable. The downside is that, in the meantime, your token bill will rise like the price of a coffee at the airport. In the end, convenience comes at a price: you will pay for every doubt the AI resolves in its perfectionist loop.