📝 Articles & Tutorials
Deep dives on building real software with AI. No fluff — just practical guides for developers who ship.

Inside Moonshot AI's breakthrough open weights release: 200k token scratchpad reasoning, Mixture of Experts (MoE) architecture, and head-to-head SWE-bench coding benchmarks against DeepSeek R1 and Claude 3.7.

Inside jcode (jcode.sh): The ultra-lightweight Rust AI coding CLI featuring 1000+ FPS rendering, 1800x faster native Mermaid diagrams, vector semantic memory, and autonomous multi-agent swarm orchestration.

Anthropic CEO Dario Amodei responds to rumors of US bans on Chinese open-weights models. A deep analysis of chip export enforcement, industrial-scale distillation crackdowns, and mandatory pre-release safety benchmarks.

A deep dive analysis of Anthropic's Claude Opus 5 system prompt revelation — covering Claude Mythos 5, Project Glasswing, Claude Cowork, Claude Tag, and Fable 5 safeguard routing mechanisms.

Why Anthropic deleted 80% of Claude Code's system prompt for Claude 5 — and how to rightsize your skills, CLAUDE.md files, and harness context.

An exhaustive architecture guide on Anthropic's open MCP standard, custom TypeScript MCP servers, JSON-RPC 2.0 primitives, and enterprise multi-agent workflows.

An exhaustive deep dive into tuning Anthropic's thinking_budget API parameter, prompt caching economics, reasoning block inspection, and multi-file state refactoring.

An operational blueprint detailing terminal agent workflows, CLAUDE.md harness design, multi-agent prompt loops, and continuous Playwright test verification.

An empirical comparison analyzing SWE-bench Verified scores (92.4%), hybrid thinking budgets, API token pricing, context window degradation, and multi-file code refactoring performance.

The complete master course on multi-agent graph architecture: eliminating fake edges, the Diamond Pattern, the Stop Rule, the Human Gate, and 3 production build prompts for Claude Code CLI.

A step-by-step career roadmap for mastering LLM APIs, RAG vector databases, autonomous multi-agent loops, and production MLOps without an academic computer science degree.

The ultimate production-readiness prompt framework combining Product Management, QA Automation, Staff Engineering, Security, UX, Performance, and SEO auditing into a single autonomous loop.