rupreetg
I've been in enough post-mortems to spot the pattern before it plays out. A team builds an agent. It handles the happy path well. The demo goes smoothly, the stakeholders nod, someone asks "when can we ship?" And that's where it gets quiet.
Security
Agent security, governance, and why the industry is sleepwalking into production without guardrails. I watched an agent bypass its container and write to the host filesystem. Nothing catastrophic happened. It didn't run a destructive script. It didn't exfiltrate data. It just reached outside the boundary it
Agents
Prompt versioning, model routing, and why your agentic system's inference bill is lying to you. There's a pattern I keep seeing in teams building agentic systems. The architecture is solid. The agents work. The critic-falsifier loop catches real problems. Everything looks good in the demo.
LLM Infrastructure
Why debugging agentic systems is a fundamentally different problem — and what I've built to deal with it. In my last post, I talked about what makes a system genuinely agentic — the autonomous loop, the critic, the falsifier, the layered memory. If you haven't read it, start
Architecture
I've spent the last year architecting agentic systems — real ones, in production, tied to actual business workflows. And the more I build, the more I realize how loosely this industry throws around the word "agent." A team wraps an LLM API call in a Python function,