Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Build a comprehensive chat analytics system with conversation metrics collection, conversion tracking, satisfaction scoring, session analysis, and A/B testing frameworks to continuously improve your chat agents.
Build a rich message renderer for AI agent chat interfaces that handles markdown, syntax-highlighted code blocks, tables, and embedded images using React and TypeScript.
Get started with Chroma DB for local vector search — learn to create collections, add documents with auto-embedding, query by similarity, and persist data to disk for rapid AI prototyping.
Build automated CI/CD pipelines for AI agent services using GitHub Actions with prompt regression testing, integration tests, Docker image builds, and canary deployment strategies.
Implement the Circuit Breaker pattern to protect AI agent systems from cascading failures with automatic failure detection, open/half-open/closed states, and graceful recovery.
Implement text classification systems using structured outputs. Build sentiment analysis, intent detection, and hierarchical category classification with enum constraints, confidence scores, and multi-label support.
Implement robust safety guardrails for Claude-powered agents including content filtering, input validation, output screening, refusal handling, and multi-layer safety architecture.
Use Claude's Batch API to process thousands of agent tasks at 50% reduced cost. Learn how to create batches, poll for completion, retrieve results, and design batch-friendly agent workflows.
Build a code review agent that parses GitHub PR diffs, analyzes code changes with Claude, generates actionable suggestions, and posts review comments via the GitHub API.
