Florian•editedOpinion PinnedAI has already entered code writing, algorithm optimization, and model development. But after a task is completed, what remains may be reusable capability—or merely an answer and scattered logs. The difference becomes apparent only when a similar problem comes up again: can the system reuse what it learned, or must it pay the cost of exploration all over again? Recursive Self-Improvement (RSI) co…
Florian•The difficulty in getting an agent to complete a long task often lies midway through. It may have already written the code but missed the actual delivery steps; it may also have simply encountered an ordinary error and be looking for an alternative on its own. At this point, we want it to correct its course promptly, but we also don't want to interrupt it every time something happens. Meta² studi…
MetaHarnessTerminal-Bench 2.1RSI
Florian•When an intelligent agent handles enterprise tasks, it often spends considerable effort on preparatory work: finding APIs, browsing directories, parsing spreadsheets, and determining which script generated a particular table. Change the question, and all that preparation gets repeated. Models can certainly keep getting stronger, but if many tasks take place in the same workspace, we can ask anothe…
