Models
LLM evaluation, fine-tuning strategies, model selection, benchmarking, and cost-performance analysis.
5 articlesin Models
Token Economics: Understanding and Optimizing LLM Costs
A practical guide to understanding token pricing, measuring real costs, and implementing optimization strategies — caching, prompt compression, model routing.
LLM Evaluation Beyond Vibes
Systematic approaches to evaluating LLM outputs — automated metrics, human evaluation frameworks, regression testing, and building evaluation pipelines.
Small Language Models in Production
When and how to use small language models like Phi, Gemma, and Mistral in production — quantization, deployment patterns, and latency-cost trade-offs.
When to Fine-Tune vs Few-Shot vs RAG
A decision framework for choosing between fine-tuning, few-shot prompting, and RAG for production LLM applications.
Claude vs GPT for Engineering Workflows
A practical comparison of Claude and GPT models for real engineering tasks — code generation, debugging, architecture reviews, and documentation.