Agentic R&D Insights

This year, I dove headfirst into Agentic Coding and automated workflows, integrating them intensely into my daily development and research. The general consensus is that AI crossed a critical threshold late last year, and my hands-on experience confirms it. I’ve barely written any code manually this year, and the output from AI agents has been staggering. To give you an idea of the scale: my tensorcircuit-ng (TC) repository saw a net increase of over 20,000 lines of python code. It took me barely two days to organically integrate and rewrite QuEra's newly released tsim into the TC framework. On the research front, I built paper-reproduction infrastructure within TC, allowing me to reproduce highly complex, representative quantum physics papers in mere minutes—I’ve knocked out over a dozen so far. Once, I spent less than a day running an end-to-end automated pipeline that handled a referee report: supplementing experiments, plotting graphs, writing the reply, and revising the manuscript