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Thoughts on data engineering, GenAI, distributed systems, and software architecture.
Most developers treat Claude Code like a chatbot with file access. It's not. It's a closed-loop agent where all intelligence lives in the model and all side effects live in the client.
Most 'agents' in production are workflows. Here's how to pick the right architecture without over-engineering or under-delivering.
Everyone's building AI agents, but nobody agrees on what one actually is. Here's what the pioneers, practitioners, and skeptics really mean when they say 'agent'.
Everyone talks about RAG like it's magic. It's not. It's plumbing. Here's the practical guide to embeddings, vector databases, and retrieval that actually works in production.
After years of juggling pip, venv, pyenv, and pipx, UV consolidates everything into one tool that's 10-100x faster. Here's the complete cheat sheet.
The tools I use daily are 10-100x faster than what I used two years ago. Here's what changed and why.
Everyone's chasing flashy demos while missing the fundamentals. Here's what actually matters: treating your docs like infrastructure, making them machine-readable, and thinking out loud instead of typing compressed garbage
Your team wants Redis. Your database needs indices. We got 97% faster with EXPLAIN ANALYZE instead of architectural rewrites.
After years of using default terminal tools, I rebuilt my workflow with modern alternatives. The result? 100x faster file searches, 80% fewer keystrokes, and workflows that don't require a mouse. Here's what actually matters.
I discovered a game-changing approach to building features with Claude Code: interview first, spec second, code last. Here's how slowing down actually speeds things up.
After 1.5 years with Cursor, Claude Code pulled me into its ecosystem. Here are the underrated features, keyboard shortcuts, and workflow patterns that made the difference.
The most powerful AI isn't a single genius brain-it's teams of specialists arguing, reviewing their own work, and signing contracts. Here's how modern agentic systems actually work.
Lessons learned from debugging K8s CrashLoopBackOff of self-hosted Langfuse
I was browsing the internet, looking at SaaS boilerplates. You know, those starter templates that promise to save you months of work.