LLM Learning Basics: Pre-training and Fine-tuning
Explains large-scale pre-training and task-specific fine-tuning through the lens of the BERT workflow.
Explains large-scale pre-training and task-specific fine-tuning through the lens of the BERT workflow.
A practical guide to integrating RedisBloom into a signup duplicate-check flow, covering request routing, sharding, synchronization, rebuild strategies, and monitoring.
A clear explanation of what the Transformer encoder and decoder each do, grounded in the original architecture and illustrated with simple examples.
An analysis of Superpowers — a skill library that injects disciplined development practices like TDD, debugging, brainstorming, and code review into AI coding agents — covering its architecture and design philosophy.
A deep dive into the Playwright repository — covering the core engine, client/server protocol, fixture-based test runner, why it has become so popular, why it feels slow when paired with an LLM, and what the alternatives look like.