Bringing Continual Learning to Every Company: Trajectory’s Ronak Malde

Today’s agents are stuck in what Ronak Malde calls “pseudo continual learning”: intelligent, but updated in offline batches, like a paper road map you can’t reroute mid-trip. Ronak, co-founder of Trajectory, explains why closing that loop is the next learning paradigm, and why training your own model, which used to take a dedicated research team, months of work and hundreds of millions in compute, is now something a company can do in a few clicks. He details two research bets: a Group Size-1 variant of GRPO that removes the need for a simulated environment by learning from single real-world rollouts instead of 16 replays of the same task, and a meta-grader that can propagate 100 representative traces across 10,000. Ronak explains how Harvey trained a model six times cheaper than frontier, taking an open-source baseline from 4% to 18% on its own legal benchmark. He defines the difference between continual learning and recursive self-improvement (the former keeps humans in the loop) and predicts product builders will become gardeners, setting trellises for products that grow on their own. Hosted by Pat Grady and Lauren Reeder, Sequoia Capital