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An Interface Perspective

What is an interface?

Grit Labs isn’t a strict methodology. It’s a flexible way of thinking that helps teams make better decisions—especially when turning ideas into real, working systems.

Grit Labs is based around this principle:

Program to an interface, not to an implementation — across all levels, from code to communication.

In Grit Labs, an interface is more than just a language feature. It is any system or specification where the patterns below are observed:

  • Predefined Structure – What elements exist and how they are organized structurally.

  • Consistent Naming – For example: names of fields, objects, actions, and events stay the same. Namebinding techniques are common.

  • Relationships – The structural or semantic links that give context and meaning to how concepts, artifacts, or entities interact.

  • Constraints – Rules about what is valid or allowed.

  • Types - The form and structure of data. These include simple types like text, boolean, or number, and complex domain types like Employee, Transaction, or Event.

This interface-based perspective makes ideas concrete. It helps separate concerns, bridge disciplines, and turn abstract thinking into durable, testable outcomes.

For example, Test-Driven Development (TDD) can be viewed as an interface when we observe:

A Predefined Structure

  1. Write a failing test.
  2. Make small changes until the test passes.
  3. Refactor.

Defined Fields, Data Types, and Constraints:

Display Name Data Type Constraints
Failing Test Description Text Nullable, 5–500 characters
Pass/Fail (passed) Boolean Not Null (required)
Test Id Integer Not Null (required)

These definitions form an interface that consistently guides TDD by clearly specifying structure and constraints. With that anchor in place, teams can code, test, and report against it with confidence, instead of reinventing checks or queries whenever requirements shift. That stability plugs straight into automation and keeps long-term maintenance light.

Additional Motivations for 'Programming to an Interface'

  • Process Over Results:
    Outcomes are unpredictable—external factors will always influence results. But the well-defined elements of an interface provide adaptability, giving teams something to rely on when uncertainty strikes.

  • Interfaces Encourage Agreement:
    When interfaces are well-defined, expectations are shared. This clarity reduces ambiguity, strengthens unity, and provides space for productive collaboration.

  • A Shared Language Accelerates Work:
    Consistent terminology and structured workflows eliminate friction. They reduce misunderstandings, prevent rework, and enable more predictable progress.

  • Consistency Over Perfection:
    Perfect methodologies don’t exist. Only consistent ones do. A bad convention becomes a good one when everyone follows it.

The Three Interface Layers of Grit Labs

Grit Labs organizes development across three core interface layers—each one building on the clarity and structure of the layer before it.

1. Knowledge Interfaces

What do we understand?

These interfaces define how understanding is recorded and shared. It starts with the questions:

  • How do we make actions traceable and auditable?

  • What are the limits of what we can know—and why do those limits exist?

  • How do we document what we're building, why it matters, and how we structure that documentation?

  • How do we divide knowledge among different audiences, and what is an appropriate level of detail?

  • How does language shift across domains, and what knowledge is proprietary or open?

In place of ad hoc documentation habits, Knowledge Interfaces provide a durable foundation for shared understanding.

Document-Driven Development (DocDD)

Documents provide the source of truth for planning and shared intent—guiding design before code exists. At its core, this interface is a simple, structured sequence:

  1. Define the system through documents

    • documents program people

  2. Express the system in executable code (as documentation)

    • code programs machines and informs people
      (The code must remain readable, testable, and clearly reflect the domain.)

  3. Implement the system for execution

    • machines obey structure

Structured Documents

Structured documents use formal formats—such as XML, JSON, or YAML—to represent information in a consistent, machine-readable way. This allows documents to include metadata, follow validation rules, and remain predictable across tools and teams.

In the context of Grit Labs, we can define a language to support this kind of structure—Grit Structured Language (GSL) . GSL would provide a lightweight way to describe system elements such as interfaces, behaviors, and constraints in a format that is both human-readable and suitable for automation.

The purpose of GSL is shared language through technology.

2. Behavior Interfaces

What should the system do?

Behavior Interfaces build directly on the structured understanding captured through Knowledge Interfaces — using it to define behavior before implementation. They act as external-facing contracts that validate, guide, and constrain development by focusing on inputs, outputs, and observable behavior—not internal implementation.

Acceptance Tests

Acceptance Tests define what the system should do based on observable outcomes. They are derived from user-facing goals and serve as concrete checks that validate system behavior against expected results. Defined before implementation, they act as external-facing contracts that guide and constrain development.

These tests follow the principles of Black Box Modeling—focusing on what goes in, what comes out, and how the system behaves at its boundaries. This keeps attention on what matters to the user, rather than how the system works internally.

To make behaviors verifiable, we organize Acceptance Tests around structured elements:

  • User Story – a high-level goal from the user’s perspective

    → “As a user, I want to reset my password...”

  • Acceptance Criteria – specific conditions that must be met for the story to be complete

    → “The user can request a password reset...”

  • Scenario – a concrete situation that expresses how the system should behave under specific conditions

    → “Given a valid email address, when a user submits the form, then the system sends a password reset email.”

  • Test Case – an independently verifiable check that validates a single aspect of system behavior

    → Typically structured as a checklist of observable outcomes

Example: Password Reset Flow

The following acceptance test captures the behavior expected when a user attempts to reset their password. It begins with a user story, defines the required criteria, expresses key scenarios, and concludes with testable outcomes.

User Story

As a user, I want to reset my password so that I can regain access to my account if I forget it.

Acceptance Criteria

The system should satisfy the following:

  1. The user can request a password reset by entering their registered email.

  2. An email with a password reset link is sent to the user’s address.

  3. The reset link expires after 24 hours.

  4. The reset link opens a secure form to set a new password.

  5. The new password must:

    • Be at least 8 characters

    • Contain at least one number

    • Include one uppercase letter

    • Include one special character

  6. Upon successful reset, the user receives confirmation and can log in using the new password.

Scenarios

  • Given a registered email is entered, when the reset form is submitted, then a reset email is sent.

  • Given a reset link is older than 24 hours, when a user clicks it, then the system shows an expiration error.

Test Cases

☑ When a registered email is submitted, the system sends a password reset email.

☑ If an unregistered email is submitted, the system displays a generic message.

☑ The password reset link expires after 24 hours.

☑ Clicking the reset link opens a secure page with a password input form.

☑ The form enforces password complexity requirements.

☑ Submitting a valid password updates the account and confirms success.

☑ After resetting, the user can log in using the new password.

☑ Using an expired or reused reset link shows an error message.

3. Integration Interfaces

How does the system connect domains and technologies?

These interfaces define the architectural boundaries of the system — where declared behaviors are bound to concrete implementations, tools, services, or external platforms. They clarify how structured expectations are fulfilled in real environments, enabling the system to coordinate across domains while preserving modularity and traceability.

Domain-Driven Design (DDD)

Use the language and structure of the domain to guide system design. Emphasize bounded contexts, domain events, and clarity of roles when mapping business logic to technical components.

Note: DDD is a broad discipline with patterns and practices well beyond the scope of this document. What follows is a simplified example to illustrate the spirit of the approach.

Example:

In a subscription billing platform, “Invoice” and “Payment” might exist within a Billing bounded context, while “User” and “Authentication” belong to an Identity context. Each context defines its own rules, events, and data flows — without leaking responsibilities across boundaries.

Structured Release Cycle

The Release Cycle is an interface that defines how code moves from development to production in a clear, repeatable way. It ensures that even small teams can deliver reliably, communicate clearly, and keep technical debt low.

This interface is lightweight by design, intended to minimize overhead while preserving clarity and consistency.

1. Cadence

  • Default rhythm: Once per sprint (2 weeks)

  • Optional: Mid-sprint deployments allowed when value is clear and risk is low

    The team plans for one coordinated UAT deployment each sprint. Earlier deployments may occur if features are ready and feedback is needed.

2. Environments

  • Dev/Main – Daily merges; auto-tested; always deployable
  • UAT – Shared environment for validation and feedback

  • Production – Live system, deploy only from approved versions

    Environments act as gates in the release flow. Each one increases visibility and confidence.

3. Versioning

  • Format: Semantic Versioning (MAJOR.MINOR.PATCH)
  • Optional Metadata: +revX (e.g. 1.3.2+rev4) for internal clarity

  • Tagging: All production deployments are tagged and traceable

    A consistent version format simplifies troubleshooting, rollback, and communication.

4. Promotion Flow

  • UAT → Prod Criteria:
  • Feature complete
  • Reviewed and validated
  • No critical bugs

  • Who Approves: Developer + one peer/stakeholder

    This shared understanding reduces ambiguity and ensures no surprises in production.

5. Release Notes

  • Brief summary of changes
  • Version tag included

  • Notes shared in internal team space (e.g. Slack, Notion, or README)

    Release notes serve as a lightweight communication tool—not just a log.

This simple Release Cycle interface aligns with Grit Labs principles: - Predefined Structure – Stable cadence and flow - Consistent Naming – Semantic versioning and tagged releases - Relationships – Defined paths from dev to prod - Constraints – Clear approval criteria - Types – Version as structured metadata

By using this Release Cycle, small teams can ship with confidence, learn through iteration, and adapt with minimal friction.

Development Flow

  1. Define the System through Documents — Use structured documents to capture shared understanding before code exists
    → documents program people
    (DocDD + GSL, operating at the Knowledge Interface layer)

  2. Capture Expected Behavior —Specify expected behavior through stories, criteria, and black-box scenarios
    → interfaces define contracts
    (Test Cases + Requests, operating at the Behavior Interface layer)

  3. Model the Domain — Design system structure around domain rules, bounded contexts, and architectural clarity
    → models give form to intent
    (DDD, operating at the Integration Interface layer)

  4. Implement and Trace — Write code that fulfills behavior contracts and aligns with the modeled structure
    → code programs machines and informs people
    (Deployment Automation + Unit Tests + Versioned Releases, operating at the Integration Interface layer)

As the system changes, update documents, tests, and models and implementation together—so that intent, behavior, and structure remain in sync.

✨ Why This Framing?

  • Grouped by concern: Developers, product leads, and designers can all participate based on the layer they're in—behavior, knowledge, or integration.

  • Reduces overlap: By placing DocDD and GSL under "Knowledge Interfaces," it’s clearer that one is philosophy (DocDD) and one is implementation (Structured Docs).

  • Clarifies flow: It now maps cleanly to how a real team moves from idea to delivery.

  • Is self-documenting: Each stage in the development flow produces artifacts that naturally explain the next. Documents define the behavior we test. Tests shape the models we build. Models inform the code we write. There’s no need to reconstruct intent after the fact—it’s already embedded in the process.