Long-Form Interview on Self-Improving Agents
Stefania_druga · x · 2026-07-17
An in-depth interview with Stefania Druga, Staff Research Scientist at Sakana AI, focusing on research agents and Recursive Self-Improvement (RSI).
Key topics include:
- Catastrophic forgetting during long-horizon agent research tasks, and how a "memory-centric" harness can mitigate it
- Sovereign AI vs. open-weights: building on controllable models rather than getting locked into a single vendor
- Why computer use remains a massive headache even as models grow more capable
- Domains better suited for self-improving research agents: math, genomics, rare diseases
- A discussion on which tasks should remain human, and what humans should do once automated away
More from AGI Musings
- Misquoted: Anthropic Staff Warned of Double-Digit Extinction Risk by 2030, Not Dismissed It — davidmanheim · 2026-09-11
- Economist Ben Moll: You Can Model Anthropic's 15% AI GDP Growth, But It Won't Happen — sebkrier · 2026-09-11
- Cohere Labs launches interactive tool mapping which tasks of 178 occupations AI can automate — Cohere_Labs · 2026-09-11
- AI researcher on SkyNews flags concerns over inequality, power and criminal misuse — schwarzjn_ · 2026-09-11
- VC compares AI doom rhetoric to pandemic-era fear messaging — StewartalsopIII · 2026-09-11
- Anthropic Insiders: Not Everyone at the Lab Believes in High p(doom) — anpaure · 2026-09-11