Blog
Essays by Vikas Goel on AI agents, Voice AI, self-evolving systems, and the gap between AI demos and AI in production.
Tokenmaxxing isn't just a metrics fad. AI agents burn tokens because they were trained on GitHub's verbose code — and run without a harness. From a CTO running production AI in front of 290M+ users, here's what's actually going on, and what to build instead of writing longer rule files.
AI agents are not a faster chatbot. They are autonomous systems that can hold a goal across hundreds of steps, recover from their own mistakes, and act in the world. The implications for business are bigger than most leaders realise — and the failure modes are different than the ones they're preparing for.
What I've learned from putting AI voice agents on real customer calls across India, the Middle East, and Latin America. Latency budgets, language switching, and why a single hallucination is a customer-impact event, not a chat-window inconvenience.
Pure-AI customer service is a sales pitch. Pure-human customer service is increasingly unviable at scale. The interesting question is what the right blend looks like — and which decisions about that blend are made by the architecture vs. left for runtime.
Twenty-five years of building enterprise systems has taught me that the model is the easiest part. The substrate underneath — observability, recovery, queueing, idempotency, identity, budget control — is where AI automation actually succeeds or fails at scale.
In 2020, with twenty years of software engineering behind me, I enrolled in an M.Tech in AI at BITS Pilani. It was the most useful thing I've done in the last decade. Here's why — and why I think more experienced engineers should take their AI education more seriously than they currently do.