Place one project's decisions on the landscape — decision exercise
Exercise: place one project's decisions on the landscape
Original fictional scenario. No cloud account, API calls or paid services are required. Difficulty: beginner · Estimated duration: 15 minutes
An insurer's generative AI programme has a backlog of open decisions. All names and details below are invented.
| # | Open decision |
|---|---|
| 1 | Should the research team train its own claims model on TPUs or GPUs? |
| 2 | Which foundation model should power all five internal tools? |
| 3 | Who is allowed to deploy a new agent to production? |
| 4 | May the claims agent issue refunds under 200 without a person approving? |
| 5 | Should adjusters get meeting notes captured automatically in Meet? |
| 6 | Should staff search Jira and SharePoint from one place, seeing only what they may? |
| 7 | Should agent quality be measured continuously on live traffic? |
| 8 | Should the coding assistant be rebuilt on a different model? |
Your decision
- Place each decision on one layer: infrastructure, models, platforms, agents or applications.
- For each, name who usually makes it: an engineering or procurement team, a builder team, or a business owner.
- Decision 2 changes something under five tools at once. Explain what that means for testing.
- Decision 4 is about autonomy. State what bounds what the agent may do on its own.
Rubric (10 house points)
- 4 points: all eight decisions on the right layer (half a point each).
- 2 points: a sensible owner for each layer.
- 2 points: decision 2 explained as a model change reaching every application built on it.
- 2 points: decision 4 answered with tools, permissions and a human review point.
Reference solution
1 — infrastructure (accelerators, networking and storage). 2 and 8 — models. 3 and 7 — platforms (governing who deploys; assessing and refining agent quality). 4 — agents (what an agent may do through its tools). 5 and 6 — applications (Gemini in Workspace for notes; Gemini Enterprise for permissions-aware search across connected apps).
Owners follow the layer: engineering and procurement for infrastructure; builder teams for models, platforms and agents; business owners for applications.
Decision 2: foundation models are the core many applications are built on, so a model change must be retested in all five tools. Rejected alternative: "test only the tool whose team asked".
Decision 4: an agent acts through the tools it is given, within permissions granted to it, with people supervising. Give it a refund tool only up to the limit, grant that permission explicitly, and keep a person reviewing above it. Rejected alternative: "trust the model's judgment because it is accurate on average".
Sources and scope
All names, decisions and rubric points above are house-authored. The layer definitions applied are grounded in:
- https://docs.cloud.google.com/ai-hypercomputer/docs/overview
- https://docs.cloud.google.com/docs/ai-ml/generative-ai/develop-generative-ai-application
- https://docs.cloud.google.com/gemini-enterprise-agent-platform/overview
- https://cloud.google.com/discover/what-are-ai-agents
- https://docs.cloud.google.com/gemini/enterprise/docs
- https://knowledge.workspace.google.com/admin/generative-ai/workspace-with-gemini/google-workspace-with-gemini