Agentic Infrastructure for the Autonomous Enterprise on Google Cloud (AIAEGC)

Module 1 - The Shift to Agency

Topics:

• 1. The Pillars & Governance
• 2. The Architectural Friction Forces
• 3. The Autonomous Maturity Scale

Objectives:

• Analyze the "Agency Gap" by diagnosing the functional intersection of Reasoning, Memory, and Tools with Data Governance to move from Track A (Chat) to Track B (Workers).
• Diagnose the four technical frictions (Integration, Statelessness, Latency, and Governance) that prevent AI pilots from scaling into production.
• Evaluate infrastructure readiness using the L1–L5 Maturity Scale to prioritize "Paved Road" investments for Level 4+ autonomy.

Activities:

• 1 Use Case
• 2 Case Studies
• 1 Demo

Module 2 - Building the "Paved Road"

Topics:

• 1. Reference Stack & Tool Archetypes
• 2. The Memory Decision Guide
• 3. Multi-Agent Orchestration Patterns
• 4. The Paved Road Lifecycle

Objectives:

• Apply the Vertex AI SDK and Vertex AI Reasoning Engine to standardize agent deployment and manage persistent conversation state.
• Evaluate the trade-offs between AlloyDB and Vertex AI Vector Search to select the optimal storage layer for metadata-heavy vs. high-scale agents.
• Apply specific orchestration patterns (Hub-and-Spoke, Linear Relay, or Parallel Critic) to manage complex, multi-departmental goals.
• Design an agentic deployment arc from Sandbox to Certified production to ensure infrastructure precedes autonomous action.

Activities:

• 4 Demos

Module 3 - The Autonomous Perimeter

Topics:

• 1. Threat Modeling for Agentic Systems
• 2. Identity Hierarchy & Credentials
• 3. Defending the Boundary: Model Armor
• 4. Responsible AI & Human-in-the-Loop

Objectives:

• Apply agentic threat modeling to identify and mitigate risks like Indirect Prompt Injection and Tool-Chaining exploits.
• Apply a three-layer identity model using Workload Identity Federation to ensure "Least Privilege" for autonomous workers.
• Apply Model Armor as a real-time security proxy to filter malicious inputs and redact sensitive output data.
• Analyze Responsible AI production requirements to embed accountability, traceability, and "Human-in-the-Loop" checkpoints within the Autonomous Perimeter.

Activities:

• 1 Use Case
• 4 Demos

Module 4 - Sustaining Autonomy

Topics:

• 1. Infrastructure ROI
• 2. The GenAIOps Lifecycle
• 3. The Innovation Harvest

Objectives:

• Analyze platform ROI by shifting from vanity metrics to Infrastructure Leverage Ratios and Component Reusability to prove the value of the "Paved Road."
• Apply a continuous feedback loop using Golden Datasets and reasoning traces to detect and remediate "Reasoning Drift."
• Apply the "Innovation Harvest" methodology to scale successful siloed tools into global, certified Gemini Enterprise assets.

Activities:

• 1 Use Case
• 1 Demo

Module 5 - Summary and Quiz

Topics:

• Review of Core Concepts

Objectives:

• Evaluate understanding of core course concepts through scenario-based questions.

Activities:

• 5 scenario-based multiple choice questions.