Product Management Topics
Product leadership, vision articulation, roadmap development, and feature prioritization. Focuses on product strategy and business alignment.
Feature Analysis and Launch Evaluation
Designing and applying evaluation frameworks to measure feature success and inform launch decisions. Topics include defining success metrics, experimentation design and basic A over B testing concepts, setting evaluation timeframes, identifying confounding factors, cohort and funnel analysis, instrumentation requirements, and how to iterate based on results. Candidates should be able to propose metrics, describe trade offs in evaluation design, and explain how launch evaluation influences product prioritization.
Translating Business Problems to Computational Solutions
Techniques for turning an ambiguous business request into concrete, buildable technical work. Covers eliciting requirements from stakeholders (including non-technical ones), distinguishing functional from non-functional requirements, defining measurable success criteria across business, product, and technical layers (e.g., SLAs/SLOs, KPIs, model-level metrics), scoping an MVP versus a full solution, writing user stories and acceptance criteria, and documenting open assumptions and trade-offs for the team that will build the solution. Applies whenever a high-level ask (an executive request, an RFP, a customer need) must be translated into a technical spec, architecture decision, or system requirement.
KPI Trees and North Star Metrics
Learn to build KPI trees that connect a North Star metric (the one metric that represents overall product success) to lower-level operational metrics that your team can influence daily. For example: 'Engage Active Users' = 'Login Rate' × 'Feature Usage Rate.' Each level should be measurable and actionable. The tree helps you understand how different levers drive your north star. Practice building trees for different business models: consumer engagement apps (DAU/engagement), marketplaces (GMV), B2B SaaS (ARR, CAC, LTV).
Ambiguous Product Scenario Navigation
Develop your approach to product scenarios with incomplete information. Practice asking targeted clarifying questions (user context, business goals, constraints, success metrics), sizing the problem, and building a logical approach step-by-step. At Staff level, also articulate how you'd establish decision-making frameworks for the future so similar questions are resolved faster.
Product and Domain Knowledge
Deep, working knowledge of a specific product you would represent, build, or sell: its core features, who the target customers are, and the concrete use cases those customers solve with it. Ability to explain how the product works under the hood, at both a high level and in technical detail, covering major components, data flows, and integration points. Where the product is a complex or enterprise system, this extends to deployment models (for example cloud versus on premise), scalability and capacity planning, resilience and recovery, and any compliance certifications that are actually relevant to its customers; not every product needs this, so calibrate to the product in question rather than assuming it. Knowledge of how the product exposes its capabilities to other systems (APIs, connectors, plugins, or partner integrations) where such mechanisms exist. Preparedness to discuss product positioning, competitive differentiation, the adoption or operational challenges real customers face, roadmap themes, and the success metrics or business outcomes the product is meant to drive. This topic assesses product knowledge, systems thinking, and the ability to reason about trade offs for an existing offering, calibrated to whatever kind of product the candidate's target role actually involves.
Product Sense and Intuition
Ability to understand users, markets, and product tradeoffs and to form well grounded product judgments. This includes identifying user needs, pain points, and behavior patterns through qualitative and quantitative research; applying frameworks such as Jobs to Be Done, user journey mapping, and hypothesis driven discovery; diagnosing friction in experiences and proposing concrete improvements that balance simplicity, usability, and feature richness. It also covers product instincts and critical thinking about product design, business models, metrics, growth levers, and market trends. Candidates should be able to explain why a product works or fails, articulate favorite products and specific changes they would make, prioritize features with clear rationale and expected impact, and communicate how their suggestions would be measured and validated.
Customer and Market Analysis
Covers the full range of activities for understanding customers, markets, and how those insights map to business opportunities. Candidates should be able to describe systematic market research methodologies including quantitative sources such as market reports and analytics, and qualitative methods such as customer interviews and user research. Demonstrate ability to analyze competitive landscape, buying criteria, total addressable market sizing, and trends that influence customer decision making. Include skills for gathering and synthesizing customer feedback and support data, distinguishing between isolated complaints and systemic pain points, identifying patterns and themes, and turning insights into prioritized product or service opportunities. Also assess business acumen by showing how technical or product decisions impact customer value, cost, and adoption, and by prioritizing work based on measurable customer and business impact.
Product Vision and Differentiation
Ability to articulate a compelling product vision that differentiates the company from competitors. Why would customers choose this product? What's the core strategic bet? How does it align with company capabilities and brand?
Setting Targets & OKRs for Technical Products
Learn to translate high-level business goals into specific, measurable Objectives and Key Results (OKRs). For example: Objective - 'Make our API platform the easiest to integrate in the industry' with Key Results like '80% of new developers can publish their first API call within 15 minutes' and 'Reduce average time-to-first-API-call from 90 minutes to 15 minutes'. Understand how to set targets that are ambitious but achievable, that drive the right behaviors, and that align teams. Be able to discuss how you'd break down OKRs into team-level goals.