AverageDevs - Real-World Web Dev Guides for Working Developers
How to Build Feedback Loops That Improve AI Output Quality
A practical engineering guide to building feedback systems that continuously improve AI output quality through data collection, evaluation pipelines, retraining strategies, and architectural patterns for production LLM applications.
Techniques for Reducing Hallucinations in LLM Based Applications
A practical, engineering focused guide to diagnosing and reducing hallucinations in LLM based apps using prompt design, retrieval, constraints, evaluation, and architecture patterns.
Context Windows for LLMs: How to Optimize Prompts for Long Documents
A practical, engineering-focused guide to token limits, chunking, retrieval, compression, and prompt budgeting so your long-document LLM features stay fast, accurate, and affordable.
Understanding tokenization in LLMs - How text becomes model input
A practical deep dive into tokenization for large language models: how raw text is normalized, split into subwords, mapped to IDs, and packed into context windows for predictable latency and cost.
TOON: A Token Efficient JSON Alternative for LLMs
A pragmatic proposal for a token-efficient data notation that plays nicely with LLM tokenizers, with TypeScript encoders, streaming patterns, and safety practices.
AI Coding Assistants: Benefits, Risks, and a Pragmatic Adoption Guide
An expert yet practical look at what AI coding assistants do well, where they fail, and how to adopt them safely with measurable outcomes.
Retrieval‑Augmented Generation (RAG): A Practical Guide for Production
What RAG is, when to use it, how it works under the hood, and concrete patterns to ship grounded, reliable LLM features in production.
Vector Databases for Semantic Search: Pinecone vs Weaviate vs Chroma (with TypeScript examples)
A developer’s guide to vector databases for semantic search: how embeddings work, when to use Pinecone, Weaviate, or Chroma, and how to build a Next.js/Node pipeline for ingestion and hybrid retrieval with TypeScript code.
Compare OpenAI, Anthropic, and Gemini APIs for developers - strengths, pricing, and integration differences.
Developer-focused comparison of OpenAI, Anthropic (Claude), and Google Gemini: capabilities, strengths, pricing considerations, SDK ergonomics, streaming, structured outputs, and integration gotchas - with TypeScript code snippets.