Systems, agents, retrieval, infrastructure

Capstone: Enterprise AI Operating Loop

The capstone synthesizes runtime architecture, retrieval, tools, MCP, mobile constraints, evals, security, and observability into one production scenario. Learners design an enterprise assistant that can answer from multimodal knowledge, call constrained tools, escalate uncertainty, and produce auditable outcomes.

Deep dive summary

What this module actually teaches.

Passage 1The capstone synthesizes runtime architecture, retrieval, tools, MCP, mobile constraints, evals, security, and observability into one production scenario. Learners design an enterprise assistant that can answer from multimodal knowledge, call constrained tools, escalate uncertainty, and produce auditable outcomes.

Passage 2Students work from requirements rather than a blank canvas: latency targets, compliance constraints, support workflows, permission boundaries, evaluation metrics, and rollout milestones. The deliverable is a design package that a real engineering team could critique before implementation.

Passage 3The capstone emphasizes architectural judgment. Learners must explain tradeoffs, identify failure modes, propose mitigations, and show how the system improves over time through telemetry and eval-driven iteration.

Learning operating system

Module prerequisites, concepts, outcomes, and artifacts

Prerequisites

  • Completion of the preceding software engineering modules
  • system design experience

Key concepts

  • end-to-end AI architecture
  • enterprise permissioning
  • multimodal retrieval
  • MCP tool ecosystem
  • operational evals
  • rollout strategy
  • AI governance

Target audience

  • Advanced engineers and technical leaders preparing to own end-to-end AI systems in production organizations.

Outcomes

  • Produce an AI system design package with architecture and quality gates
  • Defend tradeoffs around performance, cost, safety, and user experience
  • Plan staged rollout and continuous improvement for an AI feature set

Artifacts

  • enterprise assistant design brief
  • production readiness review
  • rollout and eval operating plan

Code example

Real patterns, ready to copy into your editor.

A code reference card that frames this module's concepts in real syntax. Copy any example to study it or adapt it directly in your own editor.

Copy-ready snippets
curriculum/se-enterprise-ai-capstone-operating-loop.tsts
1type ModuleBrief = {2  track: string;3  difficulty: string;4  keyConcepts: string[];5  reviewGate: 'human-review-required';6};7 8export const moduleBrief: ModuleBrief = {9  track: 'Software Engineers',10  difficulty: 'Masterclass',11  keyConcepts: [12    'end-to-end AI architecture',13    'enterprise permissioning',14    'multimodal retrieval',15    'MCP tool ecosystem',16    'operational evals',17  ],18  reviewGate: 'human-review-required',19};