
Paramu Kurumathur discusses the evolution of his development work and the impact of AI on coding.
My guest today is a good friend and colleague - and not to forget with whom I was a co-author for a book, Paramu Kurumathur. In this episode, Paramu discusses how his recent development work evolved from small Google Apps Script utilities copied and adapted from online examples to building AI-connected applications via APIs to tools like Gemini and ChatGPT, including enabling Q&A over his book content. He describes surprises from “conversing” with his books—especially that LLMs retain details he has forgotten—while noting key risks such as hallucinations and the need for precise prompts. He explains learning Cursor with guidance from our colleague, Raja, discovering that it can generate code, and rapidly producing a proof of concept that maps citizens to the Government welfare schemes using PDFs, Chroma DB, sentence transformers, and queues—work that took about a week instead of months. The conversation contrasts older development eras with today’s dependency-heavy environments, argues many SDLC intermediate steps are compressed, and highlights transferable mid-career skills in requirements and problem translation, alongside concerns about limited debugging and testing depth…
Guest: Paramu Kurumathur
Products: Google Apps Script, AI-connected applications, Gemini, ChatGPT, Cursor, Chroma DB, sentence transformers, queues
Books & works: book
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