A comprehensive deep dive into the 12 standout open-source LLMs of 2026. Explore their architectures, context windows, licenses, ideal production use cases, and how SLMs compare to LLMs, single vs multi-agent systems, and Claude Code permissions.
This blog post demystifies 11 core system design concepts by explaining them through relatable analogies featuring a consistent cast of characters. It covers fundamental distributed architecture principles—such as Load Balancing, Caching, Database Sharding, Microservices, and the CAP Theorem—making complex backend topics accessible and easy to understand for software engineers and interview candidates.
A comprehensive, deep-dive breakdown of the different layers and features of our Sun, from the nuclear forge of the core to the mysteries of the vast corona.
Explore the core components and loops that define modern AI agents. Learn about planning algorithms, short-term vs. long-term memory layers, tool integration, and structural parameters for building stable agentic workflows in production.
Distributed systems require robust service-to-service communication. Learn why synchronous communication breaks down at scale and explore essential patterns—like the Transactional Outbox and Saga Orchestration—that make event-driven architectures work in production.
Discover how Large Language Models interact with external services. We detail function calling, API execution pipelines, and how the Model Context Protocol (MCP) standardizes integrations from N x M complexity down to N + M.
Demystify the internals of the Java Virtual Machine. We trace the compilation path from source code bytecode down to ClassLoader delegation, linking stages, runtime memory layout regions, and the execution engine.
Explore the state of the art in design-engineering synchronization. Learn how Figma's MCP server enables AI agents to generate code via Figma Code Connect, and how Code-to-Design DOM reconstruction generates native Figma layers from running apps.