Engineering Reliable AI Agents in Production: Reliability, Security Boundaries, and Observability for FinTech and Web3 Systems

Abstract

This bilingual engineering report presents a practical framework for designing reliable AI agent systems in production environments. It focuses on explicit tool and permission boundaries, memory governance, observability, evaluation, human approval, failure recovery, and auditability. The report connects these concerns with the operational requirements of FinTech real-time systems and Web3 transaction workflows. It introduces the Controlled Action Protocol (CAP-1), a report-defined design proposal that binds an action proposal, policy decision, human approval, and execution record through identifiers, payload hashes, evidence, policy versions, and expiration windows. CAP-1 is not presented as a validated industry standard or a claim of industry-first novelty. The report also includes reference architectures, implementation guidance, risk analysis, and production-readiness checklists derived from the author's engineering practice from 2024 to 2026.本双语工程报告提出了一套面向生产环境的 AI Agent 可靠性工程框架,重点讨论工具与权限边界、记忆治理、可观测性、评估、人工审批、故障恢复和审计能力,并结合 FinTech 实时系统与 Web3 交易工作流的工程要求。报告定义受控行动协议 CAP-1,将行动提案、策略判定、人工授权和执行记录通过标识符、载荷 Hash、证据、策略版本和有效期绑定为可核验链条。CAP-1 被定位为本报告的设计提案,不被表述为已验证的行业标准,也不主张具有“行业首创”地位。报告同时给出参考架构、实施建议、风险分析和生产就绪检查清单,内容来源于作者 2024—2026 年间的工程实践总结。This is an author-directed technical report. Generative AI tools assisted under the author's direction with drafting, translation, language editing, diagram production, and document formatting; Pengpeng Han (Corn Han / 韩朋朋) retains responsibility for the report's factual accuracy, technical claims, source review, and final approval. Repository publication and DOI registration provide persistent identification and citation infrastructure; they do not imply peer review, third-party endorsement, or independent validation of the claims.本报告为由作者指导并负责的技术报告。生成式 AI 工具在作者指导下用于辅助起草、翻译、语言编辑、图表制作和文档排版;韩朋朋(Corn Han)对报告的事实准确性、技术主张、来源审核和最终批准承担责任。存储库发布及 DOI 注册用于提供持久标识和标准引用,不代表同行评审、第三方背书或对报告主张的独立验证。