Strategy question
On flagship deployments, customers will ask for bespoke capabilities that could either stay custom or become part of Decagon’s core platform. What framework would you use to decide which requests to productize versus keep account-specific, and how would you balance customer impact, implementation cost, roadmap coherence, and reusability across future enterprise accounts?
- Decagon
- Strategy
- Hard
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What this question tests
Tests building a framework for productizing bespoke enterprise requests, weighing customer impact, cost, roadmap coherence, and reusability across future accounts.
How to approach it
- Log every bespoke request with its implementation cost, and tag whether it's channel-specific, workflow-specific, or integration-specific.
- Score reusability: has more than one other flagship account asked for something similar, or is it tied to one customer's unique process or legacy system.
- Weigh customer impact: is this request blocking expansion or renewal for the account, or a nice-to-have improvement.
- Productize requests that are reusable across two or more accounts and align with the existing product architecture, even if the first version stays scoped.
- Keep account-specific: requests tied to one customer's unique legacy system or process that don't generalize, and solve those through configuration or professional services instead.
- Set a recurring review, for example quarterly, where repeated one-off requests get re-evaluated for productization as patterns emerge.
What a strong answer includes
- Uses concrete reusability evidence, two or more accounts asking for it, as the deciding signal over any single account's preference.
- Separates true product gaps from one customer's legacy-system quirk, keeping the latter out of core roadmap.
- Builds in a recurring review cadence so a request that looked one-off can still get productized later once a pattern appears.
- Ties the decision to roadmap coherence, not just whether the request is technically easy to build.
Common mistakes
- Productizing every large customer's request individually, fragmenting the roadmap and slowing future builds.
- Refusing to revisit account-specific work even after multiple accounts request the same thing.
- Ignoring implementation cost and shipping custom work that is expensive to maintain long-term.
Likely follow-up questions
- How would you handle a request from your single largest account that no one else wants?
- What would trigger you to productize something that started as account-specific?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop