Venkatesan Ramachandran

AI made our junior engineers faster and our senior engineers slower Last year I rolled out AI development tools across an engineering organisation. Code generation, automated testing, bug detection, intelligent code review. We built custom AI assistants for documentation and code optimisation. Added architectural decision support later. The results were

MLOps at scale: model deployment in days, not months Two years ago, getting a model from a data scientist's notebook into production took us somewhere between six weeks and four months. The process involved a Confluence page nobody read, a series of meetings where people argued about test

Entry-level engineering jobs have dropped 60% since 2022. That is not a slow decline. That is a collapse. At the same time, senior AI talent demand is running at 3.2 to 1 against supply. Every company wants the same 200 people. Nobody is building the next generation. I have

Building an enterprise LLM platform that actually ships Most enterprise LLM projects die in pilot. I've watched it happen from the inside, and I've been the one picking through the wreckage afterwards. A team spins up a proof of concept with OpenAI's API, someone

Hot config reload without restarts: PostgreSQL LISTEN/NOTIFY at 738K RPS Every API gateway I have worked with has the same problem. You change the config, you restart the process. Connections drop. Requests fail. At low traffic this is fine. At 700K+ requests per second, "fine" stops being

How I learned to talk about engineering in money Early in my career, I could not answer a simple question: what is the return on your engineering investment? I knew my systems were good. My teams shipped on time. But when someone asked me to put a number on it,