AI Agents
AI Agent Architectures: A Complete Technical Guide
From single-agent loops to multi-agent orchestration, a comprehensive overview of every major AI agent architecture pattern driving autonomous systems today.
LLM
RoPE
RoPE Explained: The Matrix Math Behind Every LLM
Rotary Position Embeddings power every major LLM, yet few tutorials show the actual matrix math. This deep dive walks through the linear algebra that makes modern transformers understand sequence order.
LLM
The 'Lost in the Middle' Effect: LLMs' Context Blindspot
Large language models struggle to use information placed in the middle of long contexts, favoring content at the beginning and end. This 'lost in the middle' effect has major implications for RAG systems and AI reliability.
LLM
Building Type-Safe LLM Pipelines with Outlines and Pydantic
Learn how to build reliable LLM pipelines with guaranteed structured outputs using the Outlines library and Pydantic schemas for type-safe AI applications.
LLM
LLM Quantization Explained: FP32, FP16, BF16, and INT8 Formats
Understanding numeric precision formats is crucial for deploying AI models efficiently. Learn how FP32, FP16, BF16, and INT8 quantization affects model performance, memory usage, and inference speed.
RAG
Why Your RAG System Fails: The Chunking Problem Explained
Most RAG failures aren't LLM issues—they're chunking failures. Learn why text segmentation strategies determine retrieval quality and how to fix common mistakes.
LLM
Reinforcement-Aware Knowledge Distillation Advances LLM Reasoning
New research combines reinforcement learning with knowledge distillation to improve how smaller language models learn complex reasoning from larger teacher models.
LLM
AutoQRA: Joint Quantization and LoRA for Efficient LLM Training
New research introduces AutoQRA, a framework that jointly optimizes mixed-precision quantization and low-rank adapters, enabling more efficient fine-tuning of large language models on limited hardware.
AI Agents
SlotBot: Building AI Agents That Impersonate Business Owners
A developer's deep dive into creating SlotBot, an AI agent that mimics solo business owners for scheduling tasks, revealing key lessons about agentic system architecture and the future of AI impersonation.
Content Moderation
ML Sampling + LLM Labeling: A New Framework for Content Moderatio
New research proposes combining ML-assisted sampling with LLM labeling to measure policy-violating content at scale, offering a methodological breakthrough for detecting synthetic media and deepfakes.
LLM
Variability Modeling Meets LLMs: Tuning Inference Parameters
New research applies software product line variability modeling to systematically optimize LLM inference hyperparameters like temperature and sampling strategies.
Multi-Agent Systems
Supervisor Agents: Orchestrating Multi-Agent AI Systems
Learn how supervisor agents coordinate specialized AI workers in multi-agent systems. This guide covers architectural patterns, LangGraph implementation, and practical orchestration strategies.