Workshop Guide — Agentic ROI Model

Quantify investigation toil reduction using Aether + Agent Builder proof.

Challenge 2: Run Agent Builder workflow in Serverless, then prompts 1 → 2.

1. ROI assumptions

Aether Games — Challenge 2 — Agentic ROI for my top investigation use case from Challenge 1.

Anchor to **Aether launch-night metrics** (matchmaking queue, auth failures, SLO budget).

Build assumptions table:
| Assumption | Value | Source |
- Ops team size (FTE)
- Incidents / month
- % investigation toil today (use 40% as baseline)
- % reduction with agentic RCA (realistic range)

Cite what you saw in Aether dashboards or Agent Builder briefs.

2. ROI outputs + executive line

Same account — calculate and present:

| Output | Value |
| Annual savings ($) | |
| FTE equivalent | |
| Payback period | |

Plus one **executive sentence** leadership can repeat: agentic observability on Elastic Serverless → $X saved / Y toil recovered.

Stress-test: one conservative and one aggressive scenario.