AI Solution Engineering Case Studies: Pursuit to Value (Hub)
· 3 min read
This hub is the parent entry for three AI solution engineering case-study series. Each series has a short parent overview and expanded articles you can study in depth. Use the same checkpoints on every case: signal → qualify → reframe → shape → engineer → prove value → land.
Shared checkpoints
| Checkpoint | Question |
|---|---|
| Signal | Real problem with sponsorship—or curiosity? |
| Qualify | Winnable and deliverable responsibly? |
| Reframe | Business problem under the tool request? |
| Shape | Assess / pilot / transform / managed? |
| Engineer | Architecture, data, controls, eval, TOM for the risk tier |
| Prove value | Benefits, assumptions, owners, measures before signature |
| Land | Handover, mobilisation, change control, benefits realisation |
Market signal → Qualify → Pursue → Discover → Reframe
→ Solution + TOM + controls → Business case → Propose / pitch
→ Contract → Hand over → Deliver → Measure → Expand if earned
Case series map
| Case | Parent | Expand into |
|---|---|---|
| A — Meridian Insurance | GenAI productivity overview | I Discovery & reframe · II Solution & commercial · III Delivery & expansion |
| B — MonGo Bank | Customer-service AI overview | Banking CS Parts I–VIII + 8D finale |
| C — Bid / no-bid | Agentic AI pursuit overview | I Qualification & independence · II Commercial realism |
How to run a workshop
- Brief from the case parent (situation, decision, outcome).
- Deepen with one expanded article per session.
- Force a live decision: pursue / condition / no-bid; reframe statement; Phase-1 scope; three non-negotiable SoW assumptions.
- Close by mapping the decision to 8D and a VALUE gate.
Discussion
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