Notas del episodio
In this episode, we’re diving into the biggest problem plaguing long-running LLM deployments: context drift and brevity bias. Your models start strong, but they decay over time, demanding costly retraining and frustrating MLOps teams. Static prompt engineering is a dead end.
Today, we're unlocking Agentic Context Engineering, or ACE—the future of production AI. Detailed in an essential article by the experts at Diztel, ACE is not just a better prompt; it’s a fully operational system layer. It allows your LLMs to learn through adaptive memory and evolve instructions automatically, just like a human team member.
Key Takeaways:
1. Instead of static prompts, Agentic Context Engineering (ACE) enables LLMs to “learn” through instructions, examples, and adaptive memory.
2. ACE directly tackles context drift and b ...
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Agentic Context EngineeringDiztel