Reddit poster argues current agent models already hint recursive self-improvement is plausible
aalluubbaa · reddit · 2026-09-14
Drawing on intensive hands-on agent use, the author argues recursive self-improvement (RSI) is not an absurd possibility:
- Today's strongest models (Astra/Ultra) already complete narrowly-defined, well-specified tasks at a solid success rate, and can combine niche concepts in ways other LLMs can't — capabilities not reflected in benchmarks.
- Yet they still fail at loosely-defined, genuinely novel jobs.
- The extrapolation: give a next-gen model ("Bel" or "Bel+1") the task of solving the bottlenecks blocking AGI (context retention, persistent memory, continuous learning — maybe 3-10 of them), run a million parallel instances for days on OpenAI-scale compute, fold any solved bottleneck back in as Bel+2, and repeat.
The author stops short of claiming this will happen, but argues believing it's impossible is less reasonable than believing it is — and that anyone can extrapolate this from current model behavior without trusting insider leaks or political narratives.
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