Releases and Traceability close the loop between the PRD and what actually ships. A Release is a delivery milestone that groups features into a shippable unit — the roadmap’s unit of commitment. Traceability is the chain that connects product decisions (features, stories, constraints, goals) to system requirements (EARS) and, through them, to the domain model and code that realise them. Without releases, the PRD is a wishlist. Without traceability, the PRD disconnects from what the team actually builds.

Release

A Release is a planned delivery milestone that groups features into a shippable unit. Releases structure the roadmap — they answer “what ships when” and “what comes first.” A release is the PRD’s unit of commitment: once a feature is included in a release, the team is on the hook to deliver it by the target date, or to move it explicitly (not silently) if it slips.

A release carries six attributes:

• target date — when the release is planned to ship. Absolute (2026-06-30) or relative (“Q2 2026”, “3 months after beta launch”).
• theme — a one-sentence label capturing the strategic intent: “Core ride loop”, “Driver retention”, “Enterprise expansion”.
• status — planned, in-progress, shipped, cancelled.
• entry criteria — what must be true before the release starts.
• exit criteria — what must be true before it ships.
• depends-on — other releases that must ship first (sequencing).

The theme is the part teams most often under-invest in. A release without a theme tends to become a grab-bag of whatever the team felt ready to ship. A release with a clear theme (“Core ride loop”) gives product managers a default answer when someone proposes adding something unrelated: “it is a good idea, but it does not serve this release’s theme.”

Example:

release "R1 — Core ride loop" {
  target-date "Q2 2026"
  theme "Minimum viable ride-hailing: request, match, ride, pay"
  status planned
  includes {
    "Ride request and fare estimate"
    "Free cancellation before driver assignment"
    "Driver weekly payout"
  }
  exit-criteria {
    "All must features pass acceptance"
    "No P0 bugs open"
    "Pilot market onboarded with 100+ drivers"
  }
}

release "R2 — Driver retention" {
  target-date "Q3 2026"
  theme "Features that keep drivers engaged and earning"
  status planned
  depends-on "R1 — Core ride loop"
  includes {
    "Instant payout"
  }
}

Each release groups a small number of features under a theme. Exit criteria are concrete enough to be verifiable: “All must features pass acceptance” is checkable; “product is good enough” is not. R2 declares depends-on "R1 — Core ride loop" — a sequencing contract that prevents the team from reversing the order under schedule pressure without an explicit decision.

Traceability to System Requirements

The PRD is the upstream source for system requirements. The traceability bridge works through the source field defined in the system requirements metamodel: each EARS requirement optionally declares where it came from — a feature, a user story, an acceptance criterion, a constraint, or a goal in the PRD.

The full chain:

PRD Feature: "Free cancellation before driver assignment"
  └── User Story: "As a rider, I want to cancel without penalty before a driver accepts,
       so that I don't feel locked in."
       └── Acceptance criterion: "Cancellation before driver assignment incurs no fee"
            ↓ source
       EARS Requirement: REQ-RIDE-020 "Rider cancellation before assignment"
         source "Feature: Free cancellation — Story: Rider cancel without penalty — AC: No fee before assignment"
            ↓ satisfied-by
       Domain: CancelRequestByRider command, RideRequestCancelledByRider event

Each layer speaks its own language. The PRD says “riders should be able to cancel for free before a driver is assigned”. The system requirement formalizes it into a testable EARS statement. The domain model implements it as a state guard, a command, and an event. The PRD never mentions state machines; the domain model never mentions user frustration. The chain links them without collapsing them.

This chain is not enforced mechanically — the source field is a free-text reference. But the structure is consistent enough to enable two high-value analyses: coverage and impact. Both are discussed below, and the symmetric domain-side view is covered in Requirement Traceability.

Feature-to-Requirement Coverage

The coverage question is: which features have no system requirements referencing them?

A feature with zero sourced by links to system requirements is one of three things:

1. Not yet formalized. The EARS requirements have not been written. The team needs to close the gap before the feature can be built.
2. Purely experiential. A visual or copy change that has no distinct system behavior — for example, a colour-scheme refresh. No system requirement is needed, but that should be called out explicitly.
3. Lost. The feature was accepted, then quietly forgotten. No requirements were written because no one wrote them. This is the most dangerous case and the one coverage analysis exists to catch.

Running coverage on a PRD before a release gate is a cheap, high-value check. Every must feature without downstream requirements is a red flag that either the requirements work is missing or the feature should not have been marked must.

Impact Analysis

The impact question is: if a feature changes, which system requirements are affected?

Follow the source references: every EARS requirement whose source field mentions this feature is a candidate for revision. From there, follow satisfaction links to identify affected domain-model elements. The full change propagation chain looks like this:

Product decision changes
  → Which features are affected?
    → Which system requirements reference those features?
      → Which domain model elements satisfy those requirements?
        → Which code realizes those elements?

Impact analysis is what makes PRD edits safe. When a product manager changes the fare-estimate feature, the team can grep source fields for “Feature: Ride request and fare estimate” and find every EARS requirement that quoted it. Then the satisfaction links on those requirements name every domain element affected. Without this chain, the same edit is a guessing game and the regression surface is whatever the team happens to remember.

The source Field Bridge

The bridge between the PRD and system requirements is a single free-text field — the source field — on each EARS requirement. The PRD itself holds no requirement IDs; the bridge runs from the downstream side.

By convention the source value follows these patterns:

source "Feature: <feature name>"
source "Feature: <feature name> — Story: <story summary>"
source "Feature: <feature name> — AC: <acceptance criterion>"
source "Job: <job name>"
source "Job: <job name> — Outcome: <desired outcome statement>"
source "Constraint: <constraint name>"
source "Goal: <goal name>"

This convention enables grep-level traceability without requiring a formal ID system in the PRD itself. If formal IDs are desired — for a regulated product, say — features, stories, and constraints can carry optional IDs (FEAT-001, STORY-001, CONS-001) and the source value references the ID.

Example:

// In a .sysreq file (SYSTEM-REQ-METAMODEL instance):
REQ-RIDE-020 "Rider cancellation before assignment" : complex
  source "Feature: Free cancellation before driver assignment — AC: No cancellation fee"
  ...

The source string is verbose on purpose. It names the feature, the acceptance criterion, and — implicitly — the user story. Anyone reading the system requirement can follow the breadcrumbs back to the exact PRD element that justifies it. And anyone reading the PRD can search downstream for all requirements carrying that feature name to audit coverage.

The grep round-trip. The source convention is designed to be walked in either direction with one command:

# PRD → SysReq: find every requirement formalizing a given acceptance criterion
grep -l 'AC: No cancellation fee' specs/*.sysreq
# → specs/ride.sysreq  (contains REQ-RIDE-020)

# SysReq → PRD: find the PRD element named in a requirement's source
grep -l 'Free cancellation before driver assignment' specs/*.prd
# → specs/ride.prd       (contains the feature block)

The same round-trip works for Feature:, Story:, Job:, Constraint:, and Goal: strings. Formal IDs, when present, make the grep exact rather than string-based.

This is a deliberately lightweight design: no enforced ID scheme, no central mapping table, no build-time traceability tool. The source field is a convention, and the convention holds as long as the team writes it. The trade-off favours low friction over mechanical guarantees — in practice, teams that adopt the convention find that grep is enough, and teams that do not adopt it find that no traceability tool would have saved them anyway.

A note on Bounded Contexts

Bounded contexts are not a PRD concept and product people rarely need to think about them directly. The PRD reasons in the user’s language: personas, jobs, features, stories. Engineering, on the other hand, carves the product into bounded contexts — boundaries within which the technical language is internally consistent. A context typically contains one or several systems (the actual software being built) that make its domain model live. See Bounded Contexts for the full definition.

Why a PM should have passing awareness of them:

• Your features will not land in one place. A feature like “Free cancellation before driver assignment” lives in the PRD as a single feature, but it is realized across several bounded contexts — the ride context confirms the cancellation is legal; the payment context ensures no charge was captured; the notification context tells the rider it worked. Each context has its own system, its own requirements, and its own model. The PM does not decompose features into contexts (engineering does), but knowing that the decomposition happens prevents surprise when “one feature” shows up in three separate technical discussions.
• Requirement scoping mirrors context boundaries. Every system requirement is scoped-to exactly one bounded context (see Requirement relations). A single PRD feature therefore typically produces several system requirements — one per context involved. This is not duplication; it is precision. When a feature changes, the engineering team can identify which contexts are affected by looking at which requirement sets reference the feature in their source.
• Releases cross context boundaries. A release is a PRD-level unit of commitment, but the work to ship it is distributed across contexts. If the ride context is ready and the payment context is not, the release slips — coordination happens at the release level, but the bottleneck lives in a context. Knowing that lets the PM ask the right question during status (“which context is blocking?”) instead of the wrong one (“why is the feature late?”).
• Your vocabulary should match theirs. Every bounded context has a ubiquitous language — the shared vocabulary that names every concept the same way across product, engineering, and operations. The PRD should adopt those names rather than coin parallel ones. If the domain model says RideRequest, the PRD should not introduce “trip booking” for the same thing; if the model says cancellation fee, the user story should not say “cancellation charge”. Aligning the PRD’s nouns with the domain’s nouns is what makes a feature trace from PRD to requirement to code without a translation key — and what lets product and engineering hold a single conversation about the same thing.

The simplest way to hold the picture: the PRD describes what the product does for users; the bounded contexts and their systems describe who (technically) is responsible for each part of what the product does; the domain model inside each context describes how each system makes its part happen. The PM owns the first layer, reads into the second only as needed, and does not usually touch the third.

Where PRD constraints land downstream. A PRD Constraint — a non-negotiable boundary from regulation, contract, technology, or organization — is rarely a constraint in the engineering sense. It becomes a concrete obligation somewhere in the SysReq or Domain layer, and the same constraint can land differently depending on its nature:

This table is a mapping, not a taxonomy — a single PRD constraint often lands in more than one place (a regulatory constraint usually generates both an NFR and an invariant, because one states the obligation and the other enforces it synchronously). The engineering team is responsible for the mapping; the PM is responsible for declaring the constraint clearly enough that engineering can do it.

The traceability chain with the intermediate layer made explicit:

PRD Feature / Story / Constraint
       │   source "Feature: ..."
       ▼
System Requirement (EARS)  ──scoped-to──▶  Bounded Context
                                               │
                                               ├── contains System(s)
                                               │
                                               └── defines Domain Model(s)
                                                          ▲
                                                          │ satisfies [REQ-…]
                                                          │
                                                   Domain element

The arrow from requirement to bounded context is what makes the source bridge land somewhere concrete. A feature without a bounded context is an idea without an owner; a bounded context without features is engineering architecture that has not met product yet. The healthiest PRDs keep both visible.