You must show a GenAI idea can meet its latency and quality goals before funding it. What do you do?
Why B is the answer
Build a technical proof of concept
A technical proof of concept shows whether an idea can meet its latency and quality goals before you fund a production build.
In detail
- A proof of concept shows that goals can be met before funding.
- Set the pass criteria before you start.
Use case
An illustrative scenario, not a real incident.
Before funding a full build, a team tests a small version against its latency and quality goals, and it finds the idea works.
See it in different ways
flowchart LR
A["Business need"] --> B["Proof of concept"]
B --> C{"Feasible and valuable?"}
C -->|Yes| D["Production design"]
C -->|No| E["Change the approach or stop"]sequenceDiagram participant S as Service participant L as Abstraction layer participant C as Configuration participant M as Model S->>L: Request L->>C: Which model? C-->>L: Model ID L->>M: Call M-->>S: Response
flowchart LR S0["Set goals"] --> S1["Build proof of concept"] --> S2["Measure"] --> S3["Decide"]
Key point: Prove feasibility before funding.
Why the other options are wrong
- A. Build the full production system first, and measure it after launch
- Measuring after launch is too late.
- C. Ask a vendor for a written promise about performance and quality
- A promise is not evidence.
- D. Choose the largest model available so that quality is not at risk
- Size does not prove latency.