Platform Product Manager Interview Questions

Option B is strongest because it introduces DORA as a validated research-backed framework, defines all four metrics, explains why they are lagging indicators, and then introduces platform-specific leading indicators (T10C, tool sprawl count, toil ratio, platform API latency, adoption rate, voluntary churn) that give earlier signal. It also describes a reporting cadence and stakeholder audience. Option A describes the spirit of DORA without naming it or distinguishing leading from lagging indicators. Option C correctly names DORA and two of its metrics but offers no platform-specific leading indicators or reporting structure. Option D relies entirely on surveys, which are lagging, subjective, and sampled — insufficient as the primary measurement framework for a platform PM. Platform Product Manager interview best practice: always pair DORA (outcome measurement) with platform-specific leading indicators like T10C and voluntary churn to demonstrate you understand that DORA tells you whether the platform is working, but not why or where to invest next.

Option B is strongest because it gives a precise definition of the golden path, names the key success criterion (easier than doing it manually), introduces three concrete selection filters (frequency, standardisation potential, ownership appetite), defines the escape hatch concept and explains why it must be genuinely accessible rather than bureaucratically gated, and describes the platform decision record as a governance artifact. Option A correctly identifies templates and best practices but lacks any decision framework for what qualifies. Option C gives a correct but thin description with no selection criteria or governance mechanism. Option D contains a common platform team anti-pattern: trying to mandate that all work goes through the golden path without escape hatches leads to shadow IT and innovation suppression, which experienced platform PMs understand is worse than controlled deviation. Platform Product Manager interview best practice: always explain escape hatches as a deliberate and positive design feature of a mature platform, not a concession to non-compliance, as this signals you understand that developer autonomy and platform standards must coexist.

Option B is strongest because it names four concrete decision factors, gives a specific example of a security case that justifies mandate (OIDC workload identity), explains the network-effect argument for mandate, and then describes an opt-in strategy with sunsetting, internal marketing, influential early adopter seeding, and dogfooding — all of which are recognised platform adoption tactics. It also addresses the feedback loop of adjusting sunset dates based on adoption velocity. Option A correctly identifies security as a mandate trigger but provides no framework for non-security features and ignores internal marketing and dogfooding. Option C describes a reasonable general approach but lacks the decision factors, the early adopter seeding strategy, and the dogfooding principle. Option D advocates mandate as the default without acknowledging the trust and autonomy costs, which experienced platform PMs recognise as a cause of developer alienation and shadow IT growth. Platform Product Manager interview best practice: always name the dogfooding principle when discussing platform adoption — it is a credibility signal that the platform team uses its own product, and it is one of the strongest predictors of platform quality.

Option B is strongest because it cites Team Topologies by name and author, correctly defines the platform team's X-as-a-Service interaction mode, explains the enabling team's temporary accelerator role and its non-ownership of long-lived assets, identifies the anti-pattern of a platform team acting as an enabling team (creating dependency rather than autonomy), and describes the temporal interaction mode transition (collaboration → facilitation → X-as-a-Service) that allows a platform feature to mature from launch to self-service. Option A is definitionally accurate but does not draw on any framework or name the interaction modes and anti-patterns. Option C is a thin platitude with no analytical value. Option D correctly separates the teams but mischaracterises enabling teams as "consultants" without addressing interaction modes, ownership models, or the dependency anti-pattern. Platform Product Manager interview best practice: always cite Team Topologies when discussing platform team topology, and name the X-as-a-Service interaction mode explicitly — it signals you understand that the platform's job is to reduce cognitive load through self-service, not to provide hands-on support for every consumer.

Option B is strongest because it names the SPACE framework by acronym and expands all five dimensions, explains why a multi-dimensional framework guards against single-metric gaming, pairs quantitative and qualitative signals for each dimension, introduces the diary study methodology for measuring flow interruptions, and describes the governance mechanism (quarterly DX report linked to platform OKRs). Option A uses two valid but incomplete signals (NPS and DORA) without any multi-dimensional structure or segmentation. Option C acknowledges measurement difficulty but provides only surveys, which are self-reported, lagging, and subject to recency bias without a structured framework. Option D identifies two useful proxy metrics (onboarding time and support tickets) but does not address the satisfaction, performance, or flow dimensions of the SPACE model. Platform Product Manager interview best practice: always cite the SPACE framework by name when discussing developer experience measurement, and explain that single-metric proxies like NPS or DORA alone are insufficient because they can improve while other DX dimensions deteriorate — segmenting NPS by role and tenure cohort is the concrete tactic that signals analytical sophistication.