Technical insights and tutorials on AI engineering, web development, and software architecture.
Advanced patterns for building stateful, intelligent AI agents
Discover the 12 architectural patterns that transform AI agents from impressive demos into reliable production systems. A comprehensive guide for technical leaders designing agent-based solutions.
Most AI agents hit a 70-80% quality ceiling and then implode. Learn the 12 engineering patterns that separate production-ready agents from impressive demos, drawn from conversations with 100+ builders in the field.
Learn how to transform stateless AI applications into intelligent agents with persistent memory. Explore 10+ memory types, implementation patterns, and production-ready code examples.
Cognition AI reveals why popular multi-agent frameworks fail in production and shares the architectural principles behind Devon. Learn why context engineering beats complexity every time.
MCP servers, integrations, and professional implementations
Transform your monolithic AI workflow into a distributed, protocol-based architecture using the Model Context Protocol. Learn how to build scalable, maintainable workflow systems with proper separation of concerns.
Discover how the Model Context Protocol (MCP) enables building true agentic AI systems that go beyond simple chatbots. Learn the architecture, implementation patterns, and enterprise applications that make AI agents truly capable.
Discover how Model Context Protocol (MCP) servers are revolutionizing AI agent capabilities. Learn to build, deploy, and optimize MCP servers that extend AI applications beyond their training data.
Discover how Claude hooks transform your AI coding assistant into a proactive development partner with voice notifications, comprehensive observability, and automatic safety controls that prevent disasters before they happen.
Strategic insights for executives and business leaders
Major tech companies are losing users and productivity by forcing AI into every interaction. Learn why the current AI gold rush is backfiring and how to implement AI strategically without alienating your customers.
Discover how Claude Code represents a paradigm shift in software development, reducing onboarding time from weeks to days and enabling developers to focus on innovation rather than implementation.
Master the Model Context Protocol (MCP) in Python for building enterprise-grade AI applications. Learn server setup, client integration, OpenAI connections, and production deployment patterns.
Explore how Claude Code represents a new paradigm in AI-assisted development, from the history of programming tools to practical workflows that transform how we write code.
Design and implement an automated customer support ticket triage system using Model Context Protocol (MCP) architecture. Learn how to build enterprise-grade agentic AI systems with proper separation of concerns.
Master the art of measuring and maximizing AI ROI with comprehensive frameworks, cost modeling tools, and industry-specific strategies for justifying AI investments.
Discover how memory transforms AI from a forgetful intern into your most valuable team member. Learn the business benefits of stateful AI systems.
Practical ways small and medium businesses can use AI to save time, cut costs, and compete with the big players - no tech team required.
AI is powerful, but it needs the right architects to build solutions that actually work. Here's why AI engineers are the bridge between amazing technology and real-world results.
Core concepts and practical implementations
Learn the essential steps and best practices for building production-ready AI-powered applications, from model selection to deployment.
Master the fundamentals of building production-ready AI agents using pure Python and direct LLM API calls. Learn core patterns, workflow design, and best practices without complex frameworks.
Explore advanced prompt engineering techniques that can dramatically improve your LLM applications, with practical examples and real-world insights.
Deployment, operations, and production systems
Transform your static documentation into an intelligent knowledge graph using AI and machine learning. Learn how to build powerful search, recommendations, and content discovery capabilities.
A comprehensive guide to MLOps practices, from model versioning to monitoring, based on real-world experience deploying ML systems at scale.
A comprehensive technical guide to vector databases for AI applications. Compare performance, costs, and implementation strategies for Pinecone, Weaviate, Qdrant, Milvus, and pgvector.
Responsible AI design and societal impact
A comprehensive guide to implementing ethical AI practices in production systems, with practical code examples for bias detection, fairness metrics, and privacy-preserving techniques.
From Microsoft's sixth Copilot button to Notion's four simultaneous AI prompts, we're witnessing a massive regression in software design. Here's why AI integration is breaking fundamental UX principles and what we can do about it.
Discover how AI is quietly revolutionizing daily life - from managing your schedule to helping with dinner plans. No tech degree required to understand or benefit!
Discover why psychological confidence, not technical brilliance, determines whether your AI product succeeds or fails. Learn about the CAIR metric that's revolutionizing how we build AI products.