Good AI systems aren't assembled from trending libraries. They're shaped with intent — each layer deliberate, each decision load-bearing.
A script runs. An agent decides. The difference is architecture, not prompt engineering. I build systems that understand context, weigh options, and act with purpose. No bloated chains. No framework soup. Just the parts that earn their place.
Every agent answer must trace back to retrieved context. If it can't cite the source, it doesn't ship. RAG isn't a feature — it's the foundation.
Agents need room to reason, but within hard boundaries. State machines enforce the rails. The LLM handles the thinking inside them.
Map the problem. What data exists, where it flows, what breaks. No code until the constraints are clear.
Tight architecture. Every component has a reason. If it doesn't serve the system, it doesn't exist.
Load test, observe, break it yourself. Production readiness isn't a checkbox — it's what happens at 3 AM when nobody's watching.