AI & Machine Learning

Learn how to build winning AI products by combining unique data, functionality, and customer insights to create competitive advantage in today's hyper-competitive landscape.

A comprehensive analysis of four key AI frontiers in 2024: reasoning models, open weights, cost efficiency, and speed performance, revealing critical trade-offs for developers and enterprises.

Learn how Zapier transforms AI agent failures into features using data-driven evaluation frameworks, feedback loops, and strategic testing approaches.

Discover how to replace manual prompt crafting with automated optimization systems that use evaluators and AI agents to achieve 5x better performance without traditional prompt engineering.

An in-depth analysis of the most significant large language model releases and developments from the past six months, exploring performance, capabilities, and industry trends.

Explore the common deployment headaches developers face with AI agents and discover infrastructure solutions that enable stateful, long-running agent deployments beyond traditional serverless limitations.

Learn proven strategies for implementing Model Context Protocol (MCP) clients in large organizations, including centralized gateways, authentication patterns, and standardized integration approaches.

Learn how Strands, an open-source SDK from AWS, simplifies AI agent development to just models and tools, eliminating complex scaffolding and enabling rapid deployment.

Learn the architectural patterns and engineering principles that transform experimental AI agents into reliable, production-grade software systems.

Learn the essential principles for building production-ready AI agents that move beyond simple prompt-and-loop patterns to create truly reliable LLM-powered software.