Practices for Integrating AI Agents into Enterprise Systems 【Trust Boundary Split】 💡 Catchy Message "Running your customer-facing and employee-facing agents on the same stack? That's a ticking time bomb for data leakage." Employee agents and customer agents have fundamentally different trust levels, data boundaries, and failure costs. Treating them as one design is how internal data leaks through customer-facing channels. 🔥 Problems Solved - Internal data leakage through customer-facing agent paths (the most critical risk) - Adversarial input exploitation (jailbreaks, indirect prompt injection) causing runaway behavior - Accidentally applying employee-tier "relaxed assumptions" to customer-facing agents - Irreversible brand damage and legal liability from customer-facing failures 🏗️ The Pattern Separate employee-facing and customer-facing agents into two distinct trust planes -- physically or logically isolated. Employee agents authenticate via corporate IdP (Okta/Entra ID) with broad internal data access. Customer agents live in a DMZ-equivalent isolated environment, accessing only explicitly published read models (projections of approved data). All customer-facing output must pass through DLP (Data Loss Prevention) inspection. Guardrails for the customer plane are significantly stricter: jailbreak detection, topic restrictions, tone control, and denial policies. You can share orchestration infrastructure and model gateways, but data access paths must always be separated. ✅ When to Adopt - Use when: Both customers and employees use agents. B2C/B2B companies where customer touchpoints and internal operations share infrastructure. - Skip when: Purely internal-only use cases (separation adds cost without benefit). ⚠️ Pitfalls - Sharing orchestration infrastructure and mistakenly assuming data paths are also safe. Infrastructure sharing and data path separation must coexist. - Deferring customer-facing guardrail design to "phase 2." Jailbreak detection, topic restrictions, and denial policies must be part of the initial architecture. - Neglecting audit log design for customer identifiers and PII retention policies, leading to compliance violations. 🛠️ Implementation Approach - Set up network segmentation to isolate the customer plane. Deploy customer-facing agents in a DMZ-equivalent environment using VPC/subnet separation, blocking direct access to internal networks. - Build CQRS read models (projections of approved public data) for the customer plane. Replace direct internal DB access with curated views of explicitly publishable data only. - Deploy a DLP (Data Loss Prevention) inspection pipeline on the customer-facing output path. Route all output through this pipeline to detect and block internal data leakage. - Apply strict guardrail policies to the customer plane: jailbreak detection, topic restrictions, tone control, and denial policies -- significantly stricter than the employee plane. - Separate authentication infrastructure. Use corporate IdP (Okta/Entra ID) with SSO for employees and customer IdP (Auth0/CIAM) for customers, keeping auth paths fully independent. #AIAgents# #EnterpriseArchitecture#