Software manufacturing. Not software consulting.

We run a factory. Standardized process. Quality gates at every step. Predictable inputs produce predictable outputs. Here is how.

Why we call it manufacturing.

Traditional software development is artisanal. Every project is treated as unique. Every team reinvents the architecture. Quality depends on whoever happens to be writing the code that week. Timelines are estimates that everyone knows are fiction.

Manufacturing is different. Manufacturing has blueprints. Assembly lines. Quality gates. Standardized components. Predictable throughput.

We apply the manufacturing model to software. The architecture patterns are standardized. The quality gates are automated. The assembly line is deterministic. Deterministic because nothing skips ahead. Architecture is approved before implementation starts. Every service is verified against the spec it was built from before it ships. The output is predictable: production-grade microservices, every time.

Three layers make this work:

The Factory

Greenfield Labs

The company. The engineering team that runs the operation and takes responsibility for the output.

The Production Floor

Greenfield

The platform and framework that standardizes how microservices are built: typed contracts, CQRS, event sourcing, two-layer authorization, zero infrastructure code. Every service built on Greenfield follows the same proven patterns.

The Assembly Line

Evergreen

The multi-agent pipeline that transforms specs into verified production services. Specialized agents handle each phase. Where phases are independent, they run in parallel. When a gate fails, the loop fixes and reruns — automatically. Nothing ships until every gate passes. Not claimed to pass. Actually passes.

Four phases. No mystery.

Phase 1 Week 1

Discovery

We start by mapping your domain. Not your tech stack — your domain. Actors, capabilities, events, service boundaries. A discovery agent runs the elicitation and only asks when it cannot infer the answer.

What happens

Domain mapping: actors, capabilities, events, service boundaries
Codebase pattern analysis, runs in parallel to discovery
Ambiguity resolution before architecture begins — edge cases surfaced, not deferred
Typed service contract drafts
Architecture blueprint production

What you receive: A complete domain model: every actor, capability, event, and service boundary. The agent asks questions when it genuinely cannot infer the answer. Not at every step. When it needs you. You review it. You approve it. Nothing is built until we agree.

Your involvement: 1-3 hours with a domain expert, asynchronous.

Phase 2 End of Week 1 into Week 2

Architecture and Specification

The blueprint gets built before a line of implementation code is written. Domain models become context maps and interaction diagrams. Every significant technical decision gets an Architecture Decision Record — not a meeting note, a documented trade-off. Workflows are derived from the event chains in the architecture, not drawn by hand. Feature scenarios are generated for every handler: happy path, validation failures, authorization failures, edge cases. The assembly line does not start until the spec is complete and you have approved it.

What happens

DDD context maps, service interaction diagrams, service internals documentation
Architecture Decision Records for every significant technical decision — trade-offs documented, not discussed
BPMN workflow definitions derived from event chains, not drawn by hand
Feature files for every handler: happy path, validation failures, authorization failures, edge cases
Service specifications with exact handler code templates — the source of truth for everything built in Phase 3

What you receive: Context maps. Interaction diagrams. Architecture Decision Records for every significant choice. Workflow definitions derived from your event model. Feature scenarios covering every handler. Service specs with exact implementation templates. The entire system, fully defined, before a single line of business logic is written. You review it. You approve it. The assembly line does not start until you do.

Your involvement: Plan a full day — for review and iteration. This is the entire application modeled before a line of code is written. You will spot problems: a service boundary that is wrong, a workflow that does not match how the business actually works, a feature scenario that is missing a case. That is the point. Catch it here. Change it here. Implementation does not start until you approve what is in front of you.

Phase 3 Weeks 2-3

Implementation

The spec becomes code. Every handler is implemented against the exact templates defined in Phase 2. Not inferred. Not improvised. Implemented to spec. Before quality gates run, a pattern validator checks every handler against the canonical templates using AST analysis. Wrong decorator: fail. Wrong base class: fail. Wrong signature: fail.

What happens

Pattern validation: every handler checked against canonical templates by AST analysis before quality gates run
Command handler implementation
Query handler implementation
Event handler implementation
Read model projections
Integration between services
Tests implemented against the feature scenarios from Phase 2

What you receive: Functioning production microservices built against the approved spec. Every handler at the canonical template. Every feature scenario tested. Services communicating through typed contracts. Directly into the quality loop — no handoff, no review gate.

Your involvement: Progress visibility throughout. No blockers waiting on you.

Phase 4 Weeks 3-4

Verified Delivery

Quality is not a checklist you run once at the end. It is a loop. Gates run, failures get fixed, gates run again — automatically, up to ten iterations. When the agent claims all gates pass, the system reruns them independently. The claim does not ship the service. The verified result does.

What happens

Spec compliance: every handler validated against the service specification from Phase 2
Automated quality loop: fix, rerun, repeat — up to ten iterations
90%+ test coverage verification (branches, functions, lines, statements)
Strict TypeScript compilation (no errors, no warnings)
Contract validation (all service interfaces verified)
Authorization verification (two-layer auth on every handler)
Distributed tracing verification (every request traceable end-to-end)
Integration testing across service boundaries
Performance validation
Documentation generation
Trust But Verify: when all gates are claimed passing, the system runs them again — exit is blocked until the result is verified, not self-reported

What you receive: Services that have passed a verified quality loop, not a self-reported one. Production-ready microservices, complete documentation, deployment configurations, and a full system walkthrough. You own everything.

Your involvement: Final review and walkthrough (2-4 hours).

What the quality gates enforce.

Every service passes through the same automated verification pipeline before it ships. These are not optional checks. They are gates. If a service does not pass, it does not ship. The pipeline runs inside a loop. It does not stop when the agent says it is done. It stops when the gates actually pass.

SOURCE CODE

Spec Compliance

Every handler present. Every contract matched. No deviations from the approved spec.

TypeScript Strict Compilation

No errors. No warnings. No 'any' types.

Contract Validation

All typed service contracts verified at compile time.

Two-Layer Auth Verification

Permission checks at gateway. Policy checks in handlers.

Test Execution

All unit, integration, and contract tests must pass.

Coverage Gates

90%+ branches, functions, lines, and statements. Enforced.

Tracing Verification

Every request path traced end-to-end through OpenTelemetry.

Lint and Format

Biome enforcement. Consistent code style across all services.

Trust But Verify

When the agent says all gates pass, the system runs them again. The session cannot exit until the result is verified. Not claimed. Verified.

PRODUCTION-READY SERVICE

No exceptions. No waivers. No self-reported completion. If the gate is red, the service does not ship.

Under the Hood

For the engineers in the room.

If you are evaluating the technical foundation, here is what is under the hood.

CQRS + Event Sourcing

Commands and queries are separated at the architecture level. Every state change is an immutable event stored in PostgreSQL. You get a complete audit trail, temporal queries, and the ability to rebuild any projection from the event stream. Read models are eventually consistent, projected from the event store through dedicated event handlers.

Multi-Agent Coordination

Each phase of the workflow runs a specialized agent. Code explorers analyze the existing codebase in parallel before architecture begins. The architecture planner builds DDD artifacts and records every significant decision. A workflow synthesizer derives process definitions from event chains — not from documentation written separately. Feature and spec agents run in parallel to produce everything the implementation agent needs. The implementation agent reads the spec. It does not improvise. A validator checks every handler using AST analysis before quality gates run. Each agent has a defined scope. None of them freelance outside it.

Spec-Driven Development

No handler gets written until the spec says exactly what it should look like. Not pseudocode. Not a description. A TypeScript template: the decorator, the base class, the method signature, the import path. The implementation agent reads the spec and builds to it. When it is done, a pattern validator checks every handler using AST analysis. Wrong decorator. Wrong base class. Wrong signature. Fail. Fix it. Run again.

Type-Safe Contract System

Services declare typed input/output contracts using TypeScript const types. Contracts are validated at compile time, not runtime. No magic strings. When a service changes its contract, every consumer knows at compile time. Validation decorators define runtime schemas without build-time code generation.

Two-Layer Authorization

Layer 1: Permission-based access control at the API gateway. Every route maps to a required permission. No permission, no access. Layer 2: Business-rule policy enforcement inside each handler. The data itself determines what is allowed. Both layers are mandatory, tested, and audited.

Zero Infrastructure Code

Services contain only domain logic. A service starts with one line: BaseService.start({ name: 'my-service', version: '1.0.0' }). RabbitMQ messaging, PostgreSQL persistence, Redis caching, OpenTelemetry tracing, Prometheus metrics, all provided by the platform. Handlers are auto-discovered by folder convention: /commands/, /queries/, /events/.

Observability Built In

OpenTelemetry instrumentation on every service. Jaeger for distributed tracing. Prometheus for metrics collection. Grafana for dashboards. Every request is traceable across service boundaries. Every event is logged. Every error has context.

BPMN Workflow Synthesis

Workflow diagrams are derived from the architecture, not drawn alongside it. After the architecture phase produces interaction maps and event chains, a workflow synthesizer reads those artifacts and generates BPMN definitions. If the event chain changes, the workflow definition changes. Documentation cannot drift from the architecture because it is generated from the architecture.

Seen enough? Let us talk about your project.

We will assess your codebase and give you a blueprint: scope, timeline, and cost. No commitment required.

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