Systems Design Approach to Prompt Engineering: Understanding LLM Attention Mechanisms
Attention Is the New Big-O A Systems Design Approach to Prompt Engineering 1. Understanding Attention: Your First Step to Better Prompts If you’re human, you’re probably reading this from left to …
Read the full articleYou might also wanna read
Metacognition in Large Language Models: A Comprehensive Review of Current Research and Future Directions
Metacognition is a foundational component of intelligence critical to effective learning, problem solving, decision-making, communication, a
Metacognition in Large Language Models: A Comprehensive Review of Current Research and Future Directions
Metacognition is a foundational component of intelligence critical to effective learning, problem solving, decision-making, communication, a
Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work
LLMs don’t fail because they forget—they fail because they remember too much. As conversations grow, prompts accumulate redundant and low-va

Prompting as Design: A Structured Approach to AI Interaction and Creative Briefing
Prompting is more than giving AI some instructions. You could think of it as a design act, part creative brief and part conversation design.
How Prompt Caching Works in Large Language Models
In this blog, we will learn about how Prompt Caching works. We will also see why we need it, how it actually works inside a large language m
Balancing the Brains: Tackling the Composition-Knowledge Challenge in LLMs
LLMs often struggle with integrating compositionality and knowledge. New methods like Concretized Proposition Prompting show promise in brid
Prompt Injection Explained as a Role Confusion Problem in LLMs
LLMs can't tell who's speaking. We show they identify roles by writing style, not tags, and exploit this with CoT Forgery, injecting fake re

Comments
Sign in to join the conversation.
No comments yet. Be the first.