From AGI to ASI
Paper • 2606.12683 • Published • 37
Hayula: An Implementation-First Multi-Agent Architecture on the Path from AGI to ASI
A Response to DeepMind "From AGI to ASI" (arXiv:2606.12683)
Yahya Saqban — HayulaLab — July 2026
Abstract
The recent DeepMind report "From AGI to ASI" (Genewein et al., 2026) identifies four pathways from AGI to superintelligence: scaling, paradigm shifts, recursive self-improvement, and multi-agent collectives. The fourth pathway—ASI emerging from large-scale multi-agent orchestration—is described as "poorly understood" and identified as one of the most critical open research questions. We present Hayula, an implemented multi-agent system that operationalizes all four pathways simultaneously. Hayula consists of 91 specialized AI agents across 4 machines, a recursive self-improvement engine, an A2A protocol, a live agent economy (Money Machine), hardware-interfacing agents, and an 8-layer ASI architecture at $0 cloud cost. This paper maps every DeepMind theoretical ASI requirement to implemented Hayula components.
Files
- 📄 paper.pdf — PDF (8 pages)
- 📝 paper.tex — LaTeX source
- 🌐 paper.html — HTML version
Quick Facts
- 91 agents across 4 machines
- $0/month cloud cost
- 14,354 curated prompts
- 48 specialized skills
- 3 live trading markets (Binance, Hyperliquid, Polymarket)
- 200ms trading loop (vs human seconds)
Based on Hayula Research
- Beyond Scaling (2026)
- Swarm of Specialists (2026)
- MENA AI Sovereignty (2026)
- Hayula-Core: 45-Agent Fleet (2026)
- Hayula Architecture (2026)
Citation
@article{saqban2026hayula-asi-v2,
title={Hayula: An Implementation-First Multi-Agent Architecture on the Path from AGI to ASI},
author={Saqban, Yahya},
journal={Hayula Labs Research},
year={2026},
note={Response to DeepMind arXiv:2606.12683}
}
Links
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