Production-grade Agent Platform Architecture

Positioning

This case supports one primary direction: enterprise Agent platform architect. It is not a demo story or a broad AI application narrative. The value is turning LLM and Agent capability into a governed platform that can enter core business workflows.

Architecture Scope

The platform boundary should cover five production capabilities:

1. Agent runtime: task state, orchestration, retries, handoff, and trace replay.
2. Tool system: tool registry, schema governance, capability release, and MCP-style integration.
3. Permission and audit: callable scopes, approval flow, risk control, and operation logs.
4. Evaluation gates: replay sets, badcase taxonomy, regression checks, and release thresholds.
5. Enterprise integration: CRM, ERP, BI, OA, customer service, sales, finance, and internal workflow systems.

Senior Ownership

• Not a single workflow: define reusable platform capability.
• Not prompt-only work: own runtime, permission, evaluation, observability, and release quality.
• Not isolated engineering: connect product, algorithms, business systems, security, and operations.
• Not pure delivery: explain reliability, cost, risk, adoption, and ROI with measurable evidence.

Evidence To Add

Future project details should fill in the real evidence:

• Platform scale: number of workflows, tools, users, departments, and integrated systems.
• Quality gates: task success rate, tool misuse rate, human handoff rate, and regression pass rate.
• Reliability: latency, availability, rollback, traceability, and production incident handling.
• Cost: model routing, cache, token cost, inference cost, and operational cost.
• Business result: hours saved, throughput improvement, conversion lift, service quality, or revenue impact.

Interview Angle

This is the anchor case for senior positioning. The narrative should show that the candidate can own a production Agent platform, not only implement Agent features.