Template

PRD Template for API

A complete product requirements template for building public APIs. Pre-filled with examples for REST design, authentication, rate limiting, versioning, documentation, and developer onboarding.

What makes API PRDs different

An API PRD is writing a contract. Unlike a UI feature where you can iterate the design after launch with minimal user impact, an API endpoint that developers build against is extremely expensive to change. Every endpoint, response shape, and authentication mechanism you define becomes a dependency for your customers' production systems.

This means API PRDs must be more precise than typical feature PRDs. The error response format, the pagination strategy, the rate limiting behavior — these are not implementation details. They are product decisions that developers will build against, document in their own codebases, and expect to remain stable for years.

The template below covers the full lifecycle of an API product: from endpoint design through authentication, rate limiting, versioning, documentation, and developer onboarding. It is designed for teams building their first public API, but the principles apply to internal APIs and microservice interfaces as well.

API PRD template

Eight sections covering every aspect of a public API.

01

Problem Statement

A public API transforms your product from an application into a platform. The problem it solves is integration — customers need to connect your product to their workflows, build on top of your data, and automate tasks that are tedious to do manually. Without an API, every integration request becomes a custom engineering project.

Example: "We receive an average of 15 integration requests per month from customers who want to connect our product to their internal tools, automate data extraction, or build custom workflows. Currently, each request requires 2-4 weeks of custom engineering work. Three deals in the last quarter stalled because the customer required API access that we could not provide. Our competitor launched a public API 6 months ago and it is cited in 28% of their case studies as a buying factor."

Tips

  • Count integration requests and the engineering cost of fulfilling them manually
  • Identify deals lost or stalled due to lack of API access
  • Survey existing customers to prioritize which API capabilities they need first
  • Analyze competitor APIs to understand market expectations for your category
02

Goals and Objectives

API goals should address developer adoption (how many integrate), reliability (uptime and latency), and business impact (deals influenced, churn prevented). A successful API is measured by what developers build with it.

Example: "Primary: 30% of customers actively using the API within 12 months of launch. Secondary: Reduce custom integration engineering from 15 requests/month to under 3. Reliability: 99.9% uptime and p95 latency under 200ms. Developer experience: A developer should be able to make their first successful API call within 15 minutes of reading the documentation."

Tips

  • Set a time-to-first-call target — how quickly a developer can make a successful API request
  • Define adoption in terms of active API consumers, not just registered API keys
  • Include reliability targets (uptime, latency) as hard requirements
  • Track API-influenced deals as a business impact metric
03

User Stories

API user stories center on the developer persona. Developers integrate APIs to solve specific problems: syncing data, automating workflows, building custom UIs, or creating internal tools. Each use case has different requirements for endpoints, data formats, and real-time capabilities.

Example: "As a developer at a customer company, I want to programmatically create and update records via a REST API so that I can sync data between our internal CRM and the product without manual data entry. Acceptance criteria: POST /api/v1/records creates a record and returns the full object with ID; PUT /api/v1/records/:id updates specified fields; responses include standard HTTP status codes; all fields are documented with types and validation rules."

Tips

  • Write stories for the most common integration use cases: data sync, automation, reporting, custom UI
  • Include a story for the developer onboarding experience: getting API keys, reading docs, making first call
  • Add a story for error handling: "As a developer, I want descriptive error messages so I can debug integration issues"
  • Cover webhook stories: "As a developer, I want to receive real-time notifications when records change"
04

Functional Requirements

API requirements must cover endpoints, authentication, rate limiting, pagination, filtering, error responses, and versioning. Every decision here becomes a contract with your developers — changing it later is expensive.

Example: "FR-1: The API must expose CRUD endpoints for all primary resources (users, projects, records, tickets). FR-2: Authentication must use API keys for server-to-server integration and OAuth 2.0 for user-context integrations. FR-3: Rate limiting must be enforced at 1,000 requests per minute per API key, with rate limit headers (X-RateLimit-Limit, X-RateLimit-Remaining, X-RateLimit-Reset) on every response. FR-4: List endpoints must support cursor-based pagination, with a maximum page size of 100. FR-5: All endpoints must return consistent error responses: { error: { code: string, message: string, details?: object } }."

Tips

  • Define a consistent URL structure: /api/v1/{resource} for collections, /api/v1/{resource}/{id} for individuals
  • Specify pagination strategy: cursor-based is preferred for large datasets, offset-based for small ones
  • Include rate limiting with clear headers so developers can build smart retry logic
  • Define the error response format and include a catalog of error codes in the documentation
05

Non-Functional Requirements

API reliability and performance are critical — developers build production systems on your API. Downtime or latency in your API causes downtime in their product. This makes your API SLA a dependency for your customers' products.

Example: "NFR-1: The API must maintain 99.9% uptime, measured monthly, with a public status page. NFR-2: p95 response time must be under 200ms for read operations and under 500ms for write operations. NFR-3: The API must support TLS 1.2+ for all requests. NFR-4: API responses must include Cache-Control headers for cacheable resources. NFR-5: All API changes must maintain backward compatibility within a major version. Breaking changes require a new API version with a 12-month deprecation timeline."

Tips

  • Publish an uptime SLA with a public status page
  • Set latency targets separately for read and write operations
  • Define your versioning strategy and backward compatibility commitment upfront
  • Specify a deprecation timeline for breaking changes (12 months is standard)
06

Success Metrics

API success is measured by developer adoption, integration health, and business impact. A well-adopted API should reduce support load, increase stickiness, and influence deals.

Example: "Metric 1: Active API consumers (unique API keys with 1+ call/week). Target: 30% of customers within 12 months. Metric 2: Time to first successful API call. Target: under 15 minutes. Metric 3: API uptime. Target: 99.9%. Metric 4: Custom integration engineering requests. Baseline: 15/month. Target: under 3/month. Metric 5: API error rate (5xx responses / total requests). Target: under 0.1%."

Tips

  • Track active API consumers, not just registered API keys
  • Measure time-to-first-call as the primary developer experience metric
  • Monitor error rates (4xx and 5xx separately) and latency percentiles
  • Track API-influenced deals and churn prevention as business metrics
07

Technical Considerations

API architecture decisions around REST vs. GraphQL, authentication mechanisms, rate limiting implementation, and versioning strategy are difficult to change after launch. These should be decided in the PRD, not during implementation.

Example: "We will build a REST API following JSON:API conventions for consistency. Authentication uses API keys (passed via X-API-Key header) for server-to-server integration and OAuth 2.0 authorization code flow for user-delegated access. Rate limiting is enforced per API key using a sliding window algorithm backed by Redis. Versioning uses URL path versioning (/api/v1/) with a 12-month deprecation window for major versions. API documentation is auto-generated from OpenAPI 3.0 specs using Redocly."

Tips

  • Choose REST for broad compatibility or GraphQL if your data model is deeply nested and clients need flexible queries
  • Auto-generate documentation from OpenAPI specs to keep docs in sync with the code
  • Implement rate limiting with Redis for distributed enforcement across API servers
  • Build a developer portal with interactive API explorer from day one
08

Risks and Mitigations

API risks include backward compatibility breaks (angering developers), abuse (overwhelming your infrastructure), and security (exposing customer data). Each requires careful planning.

Example: "Risk: A breaking API change causes customer integrations to fail. Likelihood: High (over the API lifetime). Impact: Critical (customer downtime). Mitigation: Strict versioning policy — no breaking changes within a version. New versions must coexist with old versions for 12 months. Automated backward compatibility tests run on every deploy. Risk: A customer accidentally exposes their API key in a public GitHub repository. Likelihood: High. Impact: High. Mitigation: Implement API key scanning via GitHub Secret Scanning partner program. Support instant key rotation without downtime."

Tips

  • Define backward compatibility rules and test for them automatically
  • Plan for API key compromise — support instant rotation and key scanning
  • Address abuse prevention with rate limiting, IP allowlisting, and anomaly detection
  • Include a risk plan for API outages — how customers are notified and what support is provided

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