According to Andrej Karpathy on Twitter, the next step for autoresearch is to make agentic systems massively asynchronous and collaborative, similar to SETI@home, shifting from emulating a single PhD student to a distributed research community; he notes current code grows a single synchronous thread, limiting parallel exploration and scale (source: Andrej Karpathy on Twitter, March 8, 2026). According to Karpathy, this architecture change implies distributed task sharding, result deduplication, and cross-agent memory, enabling broader hypothesis search, faster iteration, and more robust negative-result aggregation for AI R&D (source: Andrej Karpathy on Twitter). As reported by Karpathy’s post, businesses could leverage idle compute and volunteer or enterprise fleets to crowdsource model evaluation, literature mining, and reproducibility checks, creating new platforms for orchestrating autonomous research agents and marketplaces for micro-research tasks (source: Andrej Karpathy on Twitter).