Archive: 2025/09

Learn what to allow, limit, and prohibit in AI-assisted vibe coding policies to prevent security breaches, ensure compliance, and keep your team productive in 2025.

Despite the rise of massive language models, tokenization remains essential for accuracy, efficiency, and cost control. Learn why subword methods like BPE and SentencePiece still shape how LLMs understand language.

KV caching and continuous batching are essential for fast, affordable LLM serving. Learn how they reduce memory use, boost throughput, and enable real-world deployment on consumer hardware.

Learn how embeddings, attention, and feedforward networks form the core of modern large language models like GPT and Llama. No jargon, just clear explanations of how AI understands and generates human language.

Recent-posts

Training Data Poisoning Risks for Large Language Models and How to Mitigate Them

Training Data Poisoning Risks for Large Language Models and How to Mitigate Them

Jan, 18 2026

Stopping AI Hallucinations: Practical Strategies for Reliable Generative AI

Stopping AI Hallucinations: Practical Strategies for Reliable Generative AI

Apr, 12 2026

Allocating LLM Costs Across Teams: Chargeback Models That Actually Work

Allocating LLM Costs Across Teams: Chargeback Models That Actually Work

Jul, 26 2025

Template Repos with Pre-Approved Dependencies for Vibe Coding: Setup, Best Picks, and Real Risks

Template Repos with Pre-Approved Dependencies for Vibe Coding: Setup, Best Picks, and Real Risks

Feb, 20 2026

E-Commerce Product Discovery with LLMs: How Semantic Matching Boosts Sales

E-Commerce Product Discovery with LLMs: How Semantic Matching Boosts Sales

Jan, 14 2026