Strategy question
Three flagship customers want similar support automations, but each needs different integrations, policies, and workflow variations. How would you decide what should become core product, what should be reusable configuration or playbooks, and what should remain one-off forward-deployed work? How would you structure the feedback loop with Sales, FDEs, and Product/Engineering so those decisions improve future deployments?
- Decagon
- Strategy
- Hard
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What this question tests
Tests whether the candidate can turn ad hoc forward deployed work into a scalable product without losing the flexibility enterprise buyers need.
How to approach it
- Separate what the three customers need into shared automation logic, integration glue, and customer specific policy rules.
- Set a reuse threshold, such as two or more accounts wanting the same capability, to promote it from one off to playbook.
- Keep variable business rules like routing and escalation thresholds in a configuration layer instead of hardcoding them per customer.
- Leave genuinely unique integrations as forward deployed work with an explicit trigger for revisiting them later.
- Build a lightweight tagging system so FDEs log every custom build with its reuse potential.
- Run a recurring Sales, FDE, and Product review of that log so repeated requests become roadmap candidates.
What a strong answer includes
- Names a concrete graduation rule, for example requested by three accounts or saving 20+ hours of FDE time, rather than a vague instinct.
- Keeps the integration surface reusable while letting policy content stay customer specific configuration.
- Gives the review forum real decision rights over the roadmap, not just a status update.
Common mistakes
- Letting FDE work pile up without ever feeding signal back into core product.
- Generalizing too early and building a flexible platform off only three data points.
Likely follow-up questions
- When would you say a playbook has earned promotion to a core feature?
- What do you do when Sales promises a custom integration to close a deal before Product signs off?
More strategy questions
- A Fortune 500 prospect believes in Decagon’s vision but is skeptical that an AI agent can safely automate complex support journeys across chat, voice, email, and SMS. How would you structure the pre-sales process from discovery through pilot to secure the technical win, convince the C-suite the rollout is worth the risk, and choose the narrow initial deployment scope that maximizes proof of value while minimizing implementation risk?Decagon · Strategy · Hard
- You inherit a newly signed enterprise account where support workflows are fragmented, requirements are unclear, and the VP of Support, Operations, and IT all want different things first. What roadmap would you set for the first 90 days, how would you prioritize which workflow to launch first, and what milestones would you use to keep the account moving toward a production go-live?Decagon · Strategy · Hard
- 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
- After several flagship enterprise deployments, you notice each customer asks for different custom logic, integrations, and operating processes. How would you distinguish among (a) one-off account work, (b) reusable deployment playbooks, and (c) core product investments, and how would you feed those decisions into Product and Engineering so future deployments get faster without overfitting to a single customer?Decagon · Strategy · Hard
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- Decagon can support enterprise deployments through native integrations, customer-built API/SDK integrations, or partner-built extensions. How would you prioritize which systems and deployment patterns to productize first? Walk through the decision framework you’d use, including customer demand, implementation cost, reusability across accounts, security/compliance blockers, and impact on time-to-launch.Decagon · Strategy · Hard
More questions from Decagon
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