Ever wonder why your powerful AI fails at simple instructions? It's a battle between its training and your context. This article breaks down why complex fixes fall short and reveals a psychological prompt trick that yields huge gains, heralding a new era of AI interaction. 🤯

We'll talk about

• The Core Problem: Why large language models often ignore the context you provide them, defaulting to their pre-trained knowledge.
• The Complex Path: An analysis of advanced but limited methods like Supervised Fine-Tuning (SFT), Reinforcement Learning (RL), and Activation Steering.
• The Simple Solution: Unpacking the specific prompt reframing technique that led to a massive 200% performance increase.
• The Psychology Behind It: A breakdown of why this simple change in communication is so effective at guiding AI behavior.
• The Big Picture: What this discovery means for the future of AI development and the emerging era of "Software 3.0".

Keywords: Prompt Engineering, AI Tools, LLM, Supervised Fine-Tuning, Direct Preference Optimisation, Software 3.0.

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