How I built claude-ds — a drop-in wrapper that runs Claude Code with DeepSeek V4 as the backend. Covers the architecture, environment variable reverse-engineering, vision workarounds, and honest tradeoffs from daily use.
A practical guide to configuring Claude Code for maximum productivity — covering the layered configuration architecture, hooks for 100% enforcement, MCP server integrations, plugin ecosystem, context management, and worktree-based parallel development.
A comprehensive knowledge guide covering frontier model releases, agentic AI, MCP vs function calling, the evolution of RAG, edge AI with small language models, and what it all means for AI engineers.
A deep dive into harness engineering — the emerging discipline of designing systems, constraints, and feedback loops that make AI agents reliable in production. Covers core architecture, real-world case studies, and practical implementation.
A brief introduction: who I am, what I've built, and what you'll find on this blog about AI/ML engineering in production.