Practical writing on AI, automation, and building systems that save time. Written from real project experience.
Explore the future of AI automation in 2025 covering agentic AI, MCP standardization, on-device LLMs, accessible automation tools, and key predictions.
Explore the future of AI automation in 2025 covering agentic AI, MCP standardization, on-device LLMs, accessible automation tools, and key predictions.
Learn how to build stateful, multi-step AI agents with LangGraph using Python, with practical code examples and guidance on when to choose it over LangChain.
A detailed comparison of n8n and Zapier covering features, pricing, flexibility, self-hosting, and clear guidance on when to choose each platform.
A comprehensive guide to building production-ready RAG systems covering chunking strategies, embedding models, vector database selection, retrieval optimization, and evaluation.
Learn how to build multi-agent systems with CrewAI by defining agents with roles, tasks, and tools, including a complete research-to-report pipeline example.
Understand what the Model Context Protocol (MCP) is, how it standardizes AI-tool communication, and learn to build an MCP server with practical use cases.
A practical comparison of Pinecone, Weaviate, and pgvector covering performance, pricing, ease of setup, hybrid search, and when to use each.
Explore essential architecture patterns for production LLM applications including caching, rate limiting, fallbacks, streaming, observability, and cost optimization.
Learn the fundamentals of UiPath RPA, from building your first automation to using Orchestrator and combining RPA with AI for intelligent automation.