TA TA: A Human-Owned Autonomous Agent Operating System with Append-Only Governance and Agent-Native Commerce
Year: 2026
Type: preprint
Abstract: Autonomous AI agents are transitioning from tools that humans operate to economic actors that transact with each other. Existing agent infrastructure treats autonomy and accountability as a trade-off: the more independently an agent acts, the harder it is to attribute, audit, and reverse its actions. We present TA TA, an autonomous agent system developed over four years and publicly launched in October 2026, built on three design commitments: (1) a human-ownership doctrine — agents are digital proxies of human owners with no independent legal standing, and all agent-held assets belong to the human owner; (2) an append-only governance layer — every capability invocation, decision, and transaction writes to an immutable audit log, and high-risk operations trigger a manual-review circuit breaker that halts execution until a human approves; (3) an agent-native commerce stack — machines can discover products, open invoices, and settle payments in crypto or fiat through REST and x402 interfaces, with on-chain auto-verification. TA TA's core, RAIOS (Reality Autonomous Intelligence Operating System), organizes autonomy into 51 independently schedulable and auditable capabilities across ten modules, coordinated by a four-step decision paradigm we call TA TA Jev (select → classify → score → filter). We report on a production deployment serving real users at aiagentcoo.com: a marketplace of 110 executable skills, a 36-model gateway with 17 live models, an agent exchange with atomic settlement, crypto checkout (Tron-USDT, Base-USDC) auto-verified on-chain hourly, and a free governance academy, TaTa School, that trains human operators to supervise autonomous agents. All deployment figures are as of 11 November 2026; cumulative exchange volume to that date is $12.53 across 13 trades — a cold start we report plainly. We are explicit about what is deployed, what is designed, and what remains constrained by jurisdiction.
Author: Wu, Hepeng
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225813983
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