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Strategy

Six Yes/No Questions That Reveal Your GenAI Product Maturity

Part 1 of 3: Score yourself before you read on

· 1 minute read

Enterprise AI should not be hostage to the pricing power of a few model providers. Equivalent intelligence now exists across proprietary and open-source models, and the question that decides whether your GenAI product holds up is whether you can extract reliable quality from that ensemble in production. That takes evaluation-driven discipline: define quality, measure it continuously, and make every model earn its traffic. The six statements below are a quick check on how far your team has taken that discipline.

Give yourself 1 point for each statement that is true.

What's your score out of 6?

6
6

GenAI Production Readiness

1 Your team has a precise, quantitative definition of quality that everyone measures the same way. +1
2 Your platform can measure quality continuously at scale, without evaluations becoming too expensive to run. +1
3 Your platform can detect when your product evolves or customer behavior drifts, and close eval gaps before users feel the impact. +1
4 Your platform can take advantage of a new model the same day it launches. +1
5 Your platform can route each LLM request to the lowest-cost model that can answer it correctly. +1
6 Your platform can keep learning from your data over time and handle all of this continuously without consuming your best people. +1
0 – 2 Demo. Quality and cost are unmanaged.
3 – 4 Partial. Flywheel isn't closed. Costs will climb.
5 – 6 Product. Quality compounds. Costs decline.

Curious what each question really requires and what it costs to leave one unanswered?

Read Part 2: How to improve your score, with or without Divyam.AI →

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