A developer proficient in both front-end and back-end technologies, capable of building complete web applications. Crucial for delivering comprehensive and cohesive digital products by managing both user interface and server-side components.
A collection of pre-written code and tools that provide a foundation for building the front end of websites and applications, such as Bootstrap or React. Crucial for streamlining the development process and ensuring consistency.
A prioritized list of features, enhancements, and fixes that are intended to be addressed in future product development cycles. Essential for managing and planning product development activities efficiently.
Domain-Driven Design (DDD) is an approach to software development that focuses on modeling the business domain and its logic. Essential for aligning software development with business needs and creating maintainable systems.
An agile framework for managing work with an emphasis on software development, characterized by sprints and iterative progress. Essential for improving productivity and delivering incremental value in development projects.
An ongoing process of learning and development that enables individuals and organizations to adapt to changing environments and requirements. Crucial for staying current with industry trends and improving skills and knowledge.
A framework for discovering and validating the right market for a product, building the right product features, and validating the business model. Important for ensuring that products meet market needs and customer expectations.
A non-production environment used for development and testing before deployment to production. Important for ensuring that changes are thoroughly tested before going live.
Market Requirements Document (MRD) is a comprehensive document that outlines the market's needs, target audience, and business objectives for a product. It serves as a crucial tool for aligning product development efforts with market demands and business goals, ensuring that the final product meets customer needs and achieves market success.
An event where developers, designers, and other stakeholders collaborate intensively on software projects, typically within a short timeframe. Important for fostering innovation, team collaboration, and rapid prototyping of new ideas in digital product development.
A programming paradigm that uses objects and classes to structure software design, promoting reusability and scalability. Crucial for developing maintainable and scalable software systems.
A simplified, informal language used to describe the logic and steps of an algorithm or program, without syntax of actual programming languages. Useful for planning and communicating algorithms and program structures before implementation in digital product development.
A document that defines the functionality, behavior, and features of a system or component. Important for providing clear requirements and expectations for product design and development teams, ensuring alignment and successful project outcomes.
A methodology that promotes iterative development, collaboration, and flexibility to adapt to changing requirements. Crucial for product managers and development teams to deliver high-quality products efficiently.
A team responsible for developing and maintaining the foundational systems and services that support other teams and products. Crucial for ensuring scalability and efficiency across the organization.
World Wide Web Consortium (W3C) is an international community that develops open standards to ensure the long-term growth of the Web. Essential for creating and maintaining protocols and guidelines that enable the Web to function and evolve.
A framework for assessing and improving an organization's ethical practices in the development and deployment of AI. Important for ensuring that AI systems are developed responsibly and ethically.
A project or venture that starts from scratch, with no constraints imposed by prior work, enabling innovation and flexibility in development. Essential for recognizing opportunities for innovation and fresh development in business initiatives.
A systematic process for determining and addressing needs or gaps between current conditions and desired outcomes. Important for identifying user requirements and guiding the development of digital products that meet those needs.
The practice of guiding and inspiring teams to develop and deliver successful products, often involving strategic vision, team management, and innovation. Crucial for driving product success and fostering a culture of innovation and excellence.
A set of practices and principles that guide agile methodologies, such as Scrum and Kanban, to improve project management and product development. Important for structuring agile practices and ensuring effective project delivery.
The perseverance and passion for long-term goals, often seen as a key trait for success. Important for understanding and fostering resilience and persistence in design and product development.
The process of quickly creating a preliminary version of a product to test and validate ideas before full-scale development. Important for validating design concepts and gathering user feedback early.
A cross-functional team focused on solving customer problems and achieving business outcomes, with a strong emphasis on discovery, experimentation, and continuous improvement. Crucial for creating valuable and innovative products that meet user needs and drive business success through iterative development and close collaboration with stakeholders.
A group of stakeholders that regularly meet to discuss and guide the development and strategy of a product or product line. Crucial for ensuring diverse input and alignment on product strategy and decisions.
A technique used to prioritize product features based on the potential impact on customer satisfaction and business goals. Essential for aligning product development efforts with user needs and business objectives.
Guidelines and principles designed to ensure that AI systems are developed and used in a manner that is ethical and responsible. Crucial for building trust and ensuring the responsible use of AI technologies.
An inference method used in AI and expert systems where reasoning starts from the goal and works backward to determine the necessary conditions. Important for developing intelligent systems that can solve complex problems by working from desired outcomes.
The study of how new ideas, products, and processes are developed and brought to market. Essential for fostering creativity and ensuring the continuous improvement and relevance of products.
The process of training an AI model on a large dataset before fine-tuning it for a specific task. Crucial for building robust AI models that perform well on various tasks.
A Japanese term meaning "continuous improvement," focusing on small, incremental changes to enhance processes and products. Crucial for fostering a culture of ongoing improvement and excellence in product design and development.
A professional responsible for the strategy, roadmap, and feature definition of a product or product line, ensuring it meets market needs and business goals. Essential for guiding the development and success of products from conception to market.
The study and application of ethical considerations in the development, implementation, and use of technology. Crucial for ensuring that technological advancements align with ethical standards and societal values.
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
A meeting at the end of a sprint where the development team presents their completed work to stakeholders. Crucial for gathering feedback and demonstrating progress.
Adhering to laws, regulations, and guidelines relevant to business operations and product development. Crucial for ensuring products and practices meet legal and ethical standards.
The practice of designing and implementing processes, systems, or business solutions in a way that ensures their long-term viability, efficiency, and maintainability. Crucial for creating durable and efficient designs that remain practical and effective over time, ensuring the ongoing success and feasibility of digital products and operations.
Jobs-To-Be-Done (JTBD) is a framework that focuses on understanding the tasks users are trying to accomplish with a product, emphasizing their goals and motivations over product features. Crucial for designing products that meet real user needs and motivations.
The process of developing and maintaining a brand to ensure it meets business goals and customer expectations. Crucial for sustaining brand equity and achieving long-term success.
The process of making small, continuous improvements to products, services, or processes over time. Important for sustaining growth and maintaining competitiveness through ongoing improvements.
Also known as feature creep, the continuous addition of new features to a product, often beyond the original scope, leading to project delays and resource strain. Important for managing project scope and ensuring timely delivery.
The process of identifying, assessing, and mitigating potential threats that could impact the success of a digital product, including usability issues, technical failures, and user data security. Essential for maintaining product reliability, user satisfaction, and data protection, while minimizing the impact of potential design and development challenges.
A principle that states tasks always take longer than expected, even when considering Hofstadter's Law itself. Important for setting realistic project timelines and managing expectations in digital product development.
An ongoing effort to improve products, services, or processes over time through incremental and breakthrough improvements. Crucial for fostering a culture of constant enhancement and adaptation.
A principle stating that as investment in a single area increases, the rate of return on that investment eventually decreases. Important for understanding and optimizing resource allocation in product design and development.
A data-driven methodology aimed at improving processes by identifying and removing defects, and reducing variability. Crucial for enhancing the quality and efficiency of digital product development processes.
A structured routine for continuous improvement based on a scientific approach to problem-solving and process optimization. Crucial for fostering a culture of continuous improvement and innovation within product design teams.
Application Lifecycle Management (ALM) is the process of managing an application's development, maintenance, and eventual retirement throughout its lifecycle. Important for ensuring the sustainability and effectiveness of digital products over time.
An agile methodology that separates product discovery and product delivery into parallel tracks to ensure continuous learning and delivery. Essential for balancing innovation and execution in agile product development.
The practice of developing artificial intelligence systems that are fair, transparent, and respect user privacy and rights. Crucial for ensuring that AI technologies are developed responsibly and ethically.
Accessible Rich Internet Applications (ARIA) is a set of attributes that enhance the accessibility of web content for people with disabilities. Essential for making web applications more usable and inclusive.
An inference method used in AI and expert systems where reasoning starts from known facts and applies rules to derive new facts. Important for developing intelligent systems that can build knowledge and solve problems incrementally in digital products.
The design of user interfaces for machines and software, such as computers, mobile devices, and other electronic devices, with the focus on maximizing usability and the user experience. Essential for ensuring that digital products are intuitive and easy to use.
Technologies that enable machines to understand and interpret data on the web in a human-like manner, enhancing connectivity and usability of information. Essential for improving data interoperability and accessibility on the web.
An AI model that has been pre-trained on a large dataset and can be fine-tuned for specific tasks. Essential for developing state-of-the-art NLP applications.
Systematic errors in AI models that arise from the data or algorithms used, leading to poor outcomes. Important for ensuring fairness and accuracy in AI systems.
A test proposed by Alan Turing to determine if a machine's behavior is indistinguishable from that of a human. Important for evaluating the intelligence of AI systems.
Specific attributes used to enhance the accessibility of web content and applications by providing additional information to assistive technologies. Crucial for making dynamic web content more accessible to users with disabilities.
The process of creating and developing new products, focusing on form, function, usability, and aesthetics to meet user needs. Crucial for developing products that are both functional and appealing to users.
Areas of unmet demand in a market where opportunities for growth and development exist. Essential for identifying new business opportunities.