Build end-to-end observability for AI agents: traces, metrics, logs, and evals to debug, govern privacy, and scale quality, reliability, and cost.
Learn how Constitutional AI aligns models using explicit principles, self-critique, and AI feedback, with recipes, code, and evaluation tips.
An up-to-date, practical comparison of Llama vs. Mistral open‑weight models: architecture, licenses, context windows, modality, and deployment tips.
A practical, modern guide to model compression via quantization—PTQ, QAT, calibration, mixed precision, and LLM-focused methods—with code and checklists.
Designing an AI legal document review API: architecture, security, playbooks, evaluation, and examples for reliable, auditable contract analysis.
Build a production-ready AI recipe generation API with JSON schema, prompting, validation, caching, and code in Node.js and Python.
