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AllPath: Layered Verification for a Deployed, Self-Revising LLM Trading Agent under Human-Gated and Autonomous Regimes

Tian Zhang, Meng Li · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.26662 · cited by 0 works (OpenAlex) · open-access PDF

Japanese

LLMのオペレーターは、すべてのオペレーターの手のテストと自動ベンチマークのハーネスでほとんど独占的に評価されています。デプロイメントは、アクションが不可逆的である場合に、異なる質問を提起します:誰がオペレーターのアクションを検証し、それぞれのメディアが構造的に捕捉できる失敗を提案しているか。私たちは、AllPathで、リスクの限界を押し付ける個人LLMのオペレーターが、ライヴ・ペーパー・ブローカーズアカウントで展開しています。システムは、決定的なルールエンジンを通じてポジションを監視し、毎晩彼自身の日を検証し、彼自身の取引戦略に同様のレビューを提案します。 検証は3つの層に

Machine translation (Meta M2M100); the English original follows.

Abstract

LLM trading agents are evaluated almost exclusively in backtests and autonomous benchmark harnesses. Deployment, where actions are irreversible, raises a different question: who verifies the agent's actions, and which failures can each verifier structurally catch? We report on AllPath, a personal LLM trading agent deployed against a live paper-brokerage account. The system watches positions through a deterministic rules engine, and each night it reviews its own day and proposes revisions to its own trading strategies. Verification is split across three layers. Code verifies what must not depend on judgment: deterministic gates enforce risk limits and block any strategy revision that fails an integrity check. The agent verifies itself within fixed bounds: its nightly review has an iteration cap and no tools that can act. A human verifies judgment, through approval screens that show the current state of each proposal. We also compared two verification policies for the agent's self-revisions on the live system: two and a half weeks with every self-revision human-gated, then five weeks with reflection revisions auto-applied behind the same code gates, while the operator's chat channel stayed human-gated throughout. Each layer caught a different kind of failure. The code gates rejected no proposal; their role was keeping revisions consistent. The human rejected two proposals that passed every code check, both over a disagreement about the market, and later removed 11 of the 19 rules the agent had added on its own, at a median lag of eight days. The most instructive production incidents, such as strategies silently left unmonitored, passed every gate; the operator found them by hand, and the fix each time was an interface change that makes the condition visible. We contribute the layered architecture, the two-regime account, and a production incident taxonomy, none observable in a backtest.

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Topics: Code (set theory), Computer science, Benchmark (surveying), State (computer science), Channel (broadcasting), Reflection (computer programming)

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