Specific conditions that must be met for a feature to be considered complete. Clear acceptance criteria prevent scope ambiguity and ensure alignment on what "done" actually means.

An iterative approach to software development emphasizing flexibility, collaboration, and rapid delivery. Teams work in short cycles (sprints) and adapt based on continuous feedback.

User profiles representing people you explicitly should not design for. Defining anti-personas prevents feature bloat and keeps focus on the core audience.

Application Programming Interface. Protocols that allow different software applications to communicate. APIs enable integrations between your product and third-party services.

Beliefs about users, markets, or approaches that haven't been validated. Every product is built on assumptions—discovery exists to surface and test them before they become expensive mistakes.

A prioritized list of features, improvements, and tasks defining upcoming work. The backlog evolves based on discovery insights and changing priorities.

Information derived from what users actually do rather than what they say. Session recordings and analytics reveal patterns that challenge assumptions.

A strategic decision framework for determining whether to use existing solutions or create custom functionality. Depends on customization needs, long-term costs, and strategic differentiation.

A formal proposal to modify agreed-upon scope. In traditional models, these become profit centers. In discovery-led development, proper upfront work minimizes costly mid-project changes.

A data handling approach where sensitive computations occur in the user's browser. Reduces compliance risk by ensuring sensitive information never leaves the user's device.

Research examining how others solve similar problems. Goes beyond feature comparison to understand positioning, messaging, and market gaps that create opportunities.

In RICE prioritization, the percentage reflecting certainty about reach and impact estimates. Helps deprioritize high-risk features and surface where more validation is needed.

An ongoing practice where teams regularly engage with users, test hypotheses, and make data-driven decisions throughout the product lifecycle. Keeps products relevant as needs evolve.

A research method observing users in their natural environment. Reveals workarounds, frustrations, and behaviors that users can't articulate in interviews.

Building applications for multiple platforms (iOS, Android, web) from a shared codebase. Technologies like React Native reduce cost compared to separate native builds.

Using quantitative and qualitative evidence rather than opinions to guide product decisions. Combines analytics, user research, and market data to reduce guesswork.

Tangible outputs from an engagement. Discovery deliverables may include scope documents, journey maps, wireframes, technical recommendations, and risk assessments.

Relationships where one task or feature cannot proceed without another. Identifying dependencies early prevents blocked work and timeline surprises.

What makes a product stand out—features, approach, or benefits only you offer. Differentiation is tactical and measurable. Positioning sets the stage; differentiation steals the show.

Predicting how much time and resources a feature requires. Measured in person-hours, story points, or person-months depending on methodology.

A 30-60 second description clearly communicating who the product serves, what problem it solves, and why it's different.

A tool synthesizing research into four quadrants: what users Think, Feel, Say, and Do. Develops shared understanding beyond demographics.

Enterprise Resource Planning. Integrated systems managing core business processes—inventory, accounting, HR, operations. Unifies data across departments.

One of five discovery risks: whether you should build something, beyond whether you can. Includes user privacy, potential harm, and societal impact.

A detailed plan sequencing activities, identifying dependencies, defining milestones, and aligning team capacity. Unlike high-level roadmaps, these are actionable and time-bound.

One of five discovery risks: whether your team can actually build the solution with available technology, skills, and resources.

Accumulation of unnecessary features adding complexity without proportional value. Results from poor prioritization or building without validated user needs.

Deciding which features to build first based on user value, business impact, effort, and strategic alignment. Frameworks like RICE and MoSCoW provide structured approaches.

A project with defined deliverables and predetermined cost. Works best for well-scoped projects where discovery is complete. Without discovery, it's a recipe for scope fights.

A prioritization technique requiring every item to be ranked relative to others with no ties. Eliminates ambiguity and makes tradeoffs explicit.

The tendency for founders to favor ideas based on personal preference rather than evidence. Structured prioritization frameworks help remove this bias.

General Data Protection Regulation. EU regulation governing data privacy—affects how products collect, store, and process user data.

A formal checkpoint to decide whether to proceed, pivot, or stop. Proper discovery provides the clarity needed for confident decisions.

The plan for launching and acquiring customers—positioning, messaging, channel selection, pricing, and launch tactics.

A structured format for business logic. "Given" establishes context, "When" describes action, "Then" specifies expected outcome.

Transition of work between teams or phases. Poor handoffs create confusion and rework. Discovery-led development emphasizes documentation enabling clean handoffs.

Design where frontend is decoupled from backend. Provides flexibility to deliver content across channels while maintaining a single source of truth.

Health Insurance Portability and Accountability Act. U.S. regulation requiring specific safeguards for protected health information.

A testable statement about users, problems, or solutions. Structured as "We believe [X] will result in [Y] for [Z]." Turns assumptions into experiments.

Framing features as experiments with measurable outcomes. Validates hypotheses through data rather than building on assumptions.

Prioritization framework scoring on Impact, Confidence, and Ease. A simpler alternative to RICE for quick comparative scoring.

In prioritization, the measure of how significantly a feature affects users or business outcomes. Often scored on a scale to enable comparison.

Explicit definitions of what a project includes and excludes. Clear boundaries prevent misaligned expectations and reduce conflict.

Connection between your product and external systems. Integrations are where projects often blow up—discovery surfaces these risks early.

A cycle of building, testing, learning, and refining. Allows products to improve based on real feedback rather than getting everything right the first time.

A framework for understanding what "job" users are "hiring" your product to accomplish. Focuses on underlying motivation and desired outcome rather than features.

Prioritization framework categorizing features by satisfaction: Basic (expected), Performance (more is better), Delighters (unexpected wins), and Indifferent (don't care).

Key Performance Indicators. Measurable values demonstrating how effectively a product achieves objectives. Discovery defines which KPIs measure success.

Methodology focused on eliminating waste, maximizing value, and delivering quickly. Build only what's needed, validate early, improve continuously.

Existing software that's outdated but still in use. Often requires careful integration or migration strategies during modernization.

Platforms enabling applications with minimal programming. Works well for internal tools or MVPs where speed matters more than flexibility.

Simple, rough representations (sketches, basic wireframes) enabling rapid testing before investing in detailed design.

Software between applications enabling them to communicate and share data. Common in projects integrating multiple third-party services.

Minimum Viable Product. The smallest version delivering enough value to validate the core hypothesis. Not a lite version—the smallest, most useful thing that actually helps someone.

Prioritization framework: Must-have (non-negotiable), Should-have (important), Could-have (nice), Won't-have (out of scope).

Applications supporting different user types with varying permissions and workflows. Require careful role definition and access control during discovery.

Building specifically for a single platform using platform-specific tools. Maximum performance but requires separate codebases.

The single most important metric capturing core value delivered to users. Aligns teams and prioritization around what matters most.

Introducing new users to a product and guiding them to initial value. Effective onboarding reduces churn and accelerates time-to-value.

Focus on achieving results rather than delivering features. Asks "what are we trying to accomplish?" rather than "what should we build?"

A specific problem or frustration users experience. Discovery uncovers pain points through research and observation—not assumptions.

Running discovery and delivery simultaneously. Development builds what's decided while product discovers what to build next.

Research-based profile representing a user segment. Includes goals, frustrations, behaviors, and motivations—not just demographics.

Fundamental change in strategy, market, or model based on validated learning. Proper discovery either prevents pivots or enables earlier, cheaper ones.

How customers perceive a product relative to alternatives. The story about where you fit and why you matter. Positioning sets the stage; differentiation steals the show.

Validation that a proposed solution actually addresses the identified problem. Precedes product-market fit in the validation sequence.

The degree to which a product satisfies strong market demand. Not a moment—it's the outcome of disciplined decisions. Teams miss it by misreading markets or scaling too early.

High-level view of product direction over time. Communicates priorities and sequence without over-committing to specific features or dates.

Core team of product manager, designer, and tech lead collaborating on discovery. Ensures balanced consideration of user needs, business goals, and technical feasibility.

A preliminary model for testing concepts and gathering feedback. Ranges from paper sketches (low-fidelity) to interactive mockups (high-fidelity).

Initial hypothesis-based user profile created before extensive research. Starting points refined through validation—evidence-informed, not assumption-based.

Testing to identify defects and ensure quality. Should be integrated throughout development, not treated as a final gate.

Methods focused on understanding "why" through interviews, observation, and open-ended inquiry. Provides depth numbers alone cannot capture.

Methods focused on measurable data—analytics, surveys, A/B tests. Provides scale and statistical confidence.

Creating quick versions to test ideas and gather feedback early. Reduces wasted effort by validating direction before full development.

In RICE prioritization, the number of users affected by a feature in a specific timeframe. Quantifies potential scale of impact.

Ongoing engagement with recurring monthly investment. Aligns incentives around continuous value delivery rather than one-time completion.

Prioritization: (Reach × Impact × Confidence) / Effort. Provides quantitative comparison accounting for scale, significance, certainty, and cost.

Systematic identification of what could go wrong and how to handle it. Discovery surfaces risks in business model, market, users, tech, and execution.

Access control granting different capabilities based on user roles. Essential for multi-user systems and compliance requirements.

Investigating beneath symptoms to identify the fundamental source. Discovery aims to uncover root causes, not treat symptoms.

Software as a Service. Delivered via subscription through the cloud. Involves ongoing development and continuous improvement.

Ability to handle increased load without fundamental redesign. Consider during discovery but don't over-engineer for unproven assumptions.

Boundaries defining what a project includes and excludes. Well-defined scope prevents misaligned expectations. Poor scope leads to creep, conflict, and cost.

Gradual expansion beyond original boundaries. Results from unclear requirements, poor change management, or insufficient discovery.

Tools capturing user interactions (clicks, scrolling, hesitation). Reveals behavioral patterns users may not articulate.

A unified system serving as the authoritative reference. Eliminates inconsistencies from managing data across multiple systems.

Compliance framework covering security, availability, and privacy. Demonstrates trustworthy data handling practices.

A fixed time period (1-4 weeks) for completing specific work. Provides regular cadence for planning, delivery, and review.

Anyone with interest in or influence over a product—founders, users, investors. Stakeholder alignment is essential for success.

Measurable conditions defining whether a project achieved intended outcomes. Should be defined during discovery, not after launch.

Framework examining Strengths, Weaknesses, Opportunities, and Threats. Helps position products for competitive advantage.

Combining research findings into coherent insights and recommendations. Transforms raw data into understanding.

Shortcuts creating future maintenance burden. Some is strategic (ship faster); unmanaged tech debt compounds and slows development.

Combination of technologies (languages, frameworks, databases) used to build a product. Selection aligns with requirements and maintainability.

A moment prompting users to seek a solution. Understanding triggers helps identify when users become receptive.

One of five discovery risks: whether users can figure out how to use the product effectively.

Observing users attempting tasks with a product. Reveals friction points, confusion, and improvement opportunities.

The sequence of steps to accomplish a goal. Documenting flows helps identify friction, unnecessary steps, and optimization opportunities.

Structured conversation with target users. Effective interviews focus on past experiences and behaviors rather than hypothetical preferences.

Visualization of end-to-end experience from awareness through ongoing usage. Identifies pain points, emotional highs/lows, and improvement opportunities.

Systematic study of users to understand needs, behaviors, and motivations. The foundation for user-centered development.

Dividing users into groups based on characteristics, behaviors, or needs. Enables focused discovery and targeted decisions.

Feature description from user perspective: "As a [user], I want [goal] so that [benefit]." Captures requirements in terms of user value.

User Experience. The overall experience when interacting with a product—usability, accessibility, emotional response. Good UX doesn't rely on "we'll explain it later."

Confirming assumptions are correct through evidence. Applies to problems, solutions, and business models.

The promise of value delivered to customers. Articulates who you serve, what problem you solve, and why you're the best choice.

One of five discovery risks: whether the product actually creates meaningful value for users.

2x2 prioritization plotting features by value against effort. High-value/low-effort features are typically prioritized first.

Dependency on proprietary technology making switching difficult. Discovery-led development explicitly avoids architectures creating lock-in.

One of five discovery risks: whether the business can support the product (revenue model, costs, resources, strategic fit).

Prioritization where criteria are weighted by importance and options scored against each. Enables systematic comparison.

Products produced by one company and rebranded by another. Many agencies use white-label partners, creating quality risks.

Low-fidelity visual of layout and functionality without detailed design. Establishes structure before investing in visuals.

The sequence of tasks to complete a work objective. Understanding existing workflows is essential for designing products that fit.