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
Learn battle-tested patterns for building production-grade tool-calling AI agents, including error handling, retry strategies, validation, and reliability engineering.
Learn to build an AI agent that creates compelling rental listings with auto-generated descriptions, photo captions, SEO-optimized content, and multi-channel distribution.
Build a complete research agent that searches the web, evaluates sources, synthesizes findings, and generates structured reports using Claude and the Anthropic SDK.
Build a complete CrewAI multi-agent team with researcher, analyst, and writer agents that collaborate through a task pipeline to produce a comprehensive market analysis report.
Build a research synthesis agent that collects data from diverse sources in parallel, resolves conflicting information, and produces coherent analytical summaries using structured prompting.
Learn how to build an AI agent that manages restaurant reservations, handles capacity logic, confirms and cancels bookings, and operates an intelligent waitlist with automatic promotion.
Build a complete resume parsing pipeline from PDF to structured data. Covers PDF text extraction, schema design for work experience and education, LLM extraction, validation, and output formatting.
Learn to build an AI agent that parses resumes, evaluates candidates against job requirements, generates match scores, and implements bias mitigation strategies for fair automated hiring workflows.
Design and implement an AI agent that monitors reviews across platforms, performs sentiment analysis, generates brand-appropriate responses, and escalates critical issues for human attention.
