Glossary
The AI product development
The terms founders and product teams run into when building software with AI: PRD, MVP, RAG, MCP, TAM/SAM/SOM and more. Defined in plain English, in one place.
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A
3 terms- Acceptance criteria
- Acceptance criteria are the specific, testable conditions a feature must satisfy before it counts as complete, giving engineers, testers, and AI agents a shared, verifiable definition of done for each user story or requirement.
- AI agent
- An AI agent is a software system that uses a language model to plan and execute multi-step tasks toward a goal, calling tools, checking results, and adjusting its approach without step-by-step human instructions.
- API
- An API (application programming interface) is a defined contract that lets one piece of software request data or actions from another, without either side needing to know how the other works internally.
B
2 terms- Backlog
- A backlog is the ordered list of features, bug fixes, improvements, and ideas a product team intends to build, ranked so that the items at the top represent the team's actual next commitments rather than a wish list.
- Bring your own keys (BYOK)
- Bring your own keys (BYOK) is a usage model that routes an AI tool's requests through your own API keys from an LLM provider, so usage bills to your account and your data flows under your own provider agreement.
C
2 terms- Code ownership
- Code ownership is the right to fully export, host, modify, and keep the source code a platform generates for you, so your product continues to exist independently of any vendor or subscription.
- Context window
- A context window is the maximum amount of text, measured in tokens, that an AI model can process in a single request, covering the system prompt, conversation history, documents, and the model's own response.
D
2 terms- Deployment
- Deployment is the process of building an application and publishing it to hosting infrastructure so real users can access it, typically behind your own domain with SSL and automated redeploys on every code change.
- Design system
- A design system is a reusable library of components, design tokens, and usage rules that keeps a product's interface visually and behaviorally consistent as it grows across screens, features, and teams.
E
1 term- Embedding
- An embedding is a numeric vector representation of text, images, or other content that captures semantic meaning, letting software measure similarity between items and power semantic search, retrieval, and recommendations.
F
1 term- Fine-tuning
- Fine-tuning is a training process that adapts a pre-trained AI model to a specific task, tone, or domain by continuing training on your own labeled examples, changing the model's weights rather than its inputs.
G
1 term- GitHub sync
- GitHub sync is a live connection between a code-generating tool and a GitHub repository you own, so every generated change lands in your version control automatically, with full history and reviewable diffs.
H
1 term- Hallucination
- A hallucination is an AI output that states false or invented information with the same fluency and confidence as fact, such as citations that do not exist, functions that were never real, or statistics with no source.
I
1 term- Integration
- An integration is a working connection between your product and an external service, such as payments, authentication, or email, so that data and actions flow between the two systems automatically.
L
1 term- Large language model (LLM)
- A large language model (LLM) is an AI model trained on massive text datasets to predict and generate language, powering writing, coding, analysis, and reasoning tools through token-by-token text generation.
M
3 terms- Market research
- Market research is the process of validating a product idea against real-world evidence, including market size, competitor gaps, pricing, and user needs, before building, making it the cheapest point in the product lifecycle to discover you are wrong.
- Minimum viable product (MVP)
- A minimum viable product (MVP) is the smallest version of a product that delivers real value to real users and produces validated learning about whether the core idea deserves further investment.
- Model Context Protocol (MCP)
- The Model Context Protocol (MCP) is an open standard that connects AI models to external tools and data sources through one consistent interface, so any compatible agent can discover and use a service without custom integration code.
N
2 terms- Native mobile app
- A native mobile app is an application built to run directly on iOS or Android, distributed through the App Store or Google Play, with full access to device capabilities such as push notifications, camera, and offline storage.
- North star metric
- A north star metric is the single measurement that best captures the core value a product delivers to its users, chosen so that sustained growth in that one number reflects genuine business progress rather than vanity activity.
P
3 terms- Product requirements document (PRD)
- A product requirements document (PRD) is a structured specification that defines what a product or feature should do and why, covering the problem, target user, scope, user stories, and acceptance criteria that guide design and engineering.
- Prompt
- A prompt is the instruction given to an AI model that specifies the task, context, constraints, and output format the model should follow, forming the entire interface between your intent and the model's response.
- Prototype
- A prototype is an interactive model of a product, ranging from clickable design frames to a coded demo with sample data, built to test flows and assumptions with users before committing to production code.
R
2 terms- Retrieval-augmented generation (RAG)
- Retrieval-augmented generation (RAG) is an AI technique that retrieves relevant documents from a knowledge base and inserts them into a language model's context at generation time, so answers are grounded in real, current data instead of training memory.
- RICE scoring
- RICE scoring is a prioritization framework that ranks product ideas by multiplying Reach, Impact, and Confidence, then dividing by Effort, producing a single comparable score that shows which backlog items deliver the most value per unit of work.
S
1 term- System prompt
- A system prompt is a higher-priority instruction set given to an AI model before any user message that defines the model's role, rules, tone, and boundaries for an entire session or product.
T
2 terms- TAM, SAM & SOM
- TAM, SAM, and SOM are three nested market-size estimates, total addressable market, serviceable available market, and serviceable obtainable market, used to size an opportunity from the entire category down to the share a company can realistically win.
- Token
- A token is the basic unit of text that AI models read and generate, roughly four characters or three-quarters of an English word; model pricing, context windows, and generation speed are all measured in tokens.
U
2 terms- User persona
- A user persona is a semi-fictional profile of a target user, assembled from research, that captures their role, goals, context, and frustrations so product decisions stay grounded in a real audience.
- User story
- A user story is a short, plain-language description of a feature told from the user's perspective, typically written as "As a [user], I want [goal] so that [benefit]," keeping development focused on outcomes rather than outputs.
W
1 term- Wireframe
- A wireframe is a low-fidelity layout of a screen that shows structure, hierarchy, and element placement using simple boxes and placeholder text, so teams can agree on flow before investing in visual design.
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