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

Secure Prompting for Vibe Coding: How to Ask for Safer Code

Secure Prompting for Vibe Coding: How to Ask for Safer Code

Oct, 2 2025

Caching and Performance in AI-Generated Web Apps: Where to Start

Caching and Performance in AI-Generated Web Apps: Where to Start

Dec, 14 2025

Interoperability Patterns to Abstract Large Language Model Providers

Interoperability Patterns to Abstract Large Language Model Providers

Jul, 22 2025

Fintech Experiments with Vibe Coding: Mock Data, Compliance, and Guardrails

Fintech Experiments with Vibe Coding: Mock Data, Compliance, and Guardrails

Jan, 23 2026

Latency Optimization for Large Language Models: Streaming, Batching, and Caching

Latency Optimization for Large Language Models: Streaming, Batching, and Caching

Aug, 1 2025