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LLM security, production ML, and AI risk — the technical side of artificial intelligence.

Why Quantized Small Models Will Dominate AI's Future — An Honest Take
AI5 min readApr 22, 2026

Why Quantized Small Models Will Dominate AI's Future — An Honest Take

The shift from giant generalists to tiny specialists. Why INT8/INT4 quantized small language models — not ever-larger frontier LLMs — are where most real business value will actually be captured.

quantizationsmall-language-modelsslm
Build LLM Vocab: Tokens, Embeddings, Vocabulary Size, and Context Windows Explained
AI7 min readApr 22, 2026

Build LLM Vocab: Tokens, Embeddings, Vocabulary Size, and Context Windows Explained

The core plumbing behind every large language model — tokens, tokenisation, embeddings, vocabulary, and context windows — explained in plain English with examples you can actually try.

llmtokenstokenization
LLM Context Windows and Memory: How Models Handle Extended Dialogues
AI4 min readApr 22, 2026

LLM Context Windows and Memory: How Models Handle Extended Dialogues

Why LLMs forget, how much they can actually remember, and the four techniques — bigger windows, RAG, persistent memory, and efficient attention — that push past the limit.

llmcontext-windowtokens
Fine-Tuning vs Retrieval-Augmented Generation (RAG): Choosing the Right Approach for Custom LLMs
AI4 min readApr 22, 2026

Fine-Tuning vs Retrieval-Augmented Generation (RAG): Choosing the Right Approach for Custom LLMs

Fine-tuning bakes knowledge into the model's weights; RAG lets it look things up. A clear-eyed comparison across cost, latency, freshness, and accuracy — plus when to use both.

fine-tuningragretrieval-augmented-generation
Fine-Tune an LLM on Your MacBook with LoRA: A Hands-On Guide
AI6 min readApr 21, 2026

Fine-Tune an LLM on Your MacBook with LoRA: A Hands-On Guide

Fine-tune an open-source LLM on a MacBook in under ten minutes. A working LoRA + Phi-2 pipeline on Apple Silicon, trained on the GDPR, with no cloud bill attached.

lorafine-tuningphi-2
The Hidden Risks of Exposing LLM APIs
AI6 min readMar 18, 2026

The Hidden Risks of Exposing LLM APIs

Shipping an LLM behind a REST endpoint feels routine — until you realise the model itself is an attack surface. Prompt injection, exfiltration through retrieval, and timing side-channels, with fixes that actually hold up.

llm-securityprompt-injectionrag-security
Building RAG Systems That Don't Fall Apart in Production
AI6 min readFeb 5, 2026

Building RAG Systems That Don't Fall Apart in Production

A ten-document RAG demo is an afternoon project. A half-million-document RAG system with real users is an engineering discipline. Here's what actually breaks, and the architecture that holds up.

ragllmvector-search

7 posts