Our Methodology

How we ship complex AI systems
without vibe coding.

Generative AI made it easy to write code — and easier than ever to ship the wrong thing. Our methodology combines SDD, BMAD, DDD, BDD, and TDD into a single, opinionated practice that keeps humans, codebases, and AI agents aligned on a single source of truth.

SDDThe contract layer.
BMADThe delivery rhythm.
DDDThe shape of the system.
BDDSpecs that execute.
TDDThe safety net for AI-generated code.
The problem

Vibe coding is fast. Until it isn't.

Without rigorous specifications, AI accelerates the wrong things — and makes mistakes harder to catch. Here's where most AI projects break down:

Hallucinated APIs

AI invents endpoints, libraries, and functions that don't exist. Discovered at runtime.

Brittle prototypes

Demos that win pilots but collapse under real load, real data, real users.

Contradictory requirements

Stakeholder A and B disagree. Engineering picks the wrong one, twice, in different files.

Untraceable decisions

Six months later, nobody remembers why the system does this — or who approved it.

The SDD lifecycle

From ambiguity to executable spec.

Five phases that compress months of planning into weeks — and produce specifications that are precise enough for AI agents to execute against.

01

Capture

Stakeholder interviews, domain workshops, and requirement extraction — turned into structured, queryable specs.

Stakeholder map
Domain glossary
Raw requirements
02

Specify

Requirements become precise, machine-readable specifications. Conflicts surface here, not in production.

PRD
Acceptance criteria
Decision log
03

Align

Approvals captured digitally with traceable sign-off. Engineering, product, and stakeholders share one source of truth.

Approval workflow
RACI
Signed-off PRD
04

Build

Engineers and AI agents work from the same spec. Every commit traces back to an approved requirement.

Spec ↔ Code links
Agent prompts
Tests from BDD
05

Verify

Behavior tests derived from specs. Continuous validation that what shipped matches what was approved.

Executable specs
Coverage report
Variance audit

Powered by SpecGraph — our SDD platform.

We don't just preach SDD — we built the platform that makes it work. SpecGraph turns fragmented requirements into unified, conflict-free PRDs your team and AI agents can execute against.

Visit SpecGraph
The full stack

Five practices. One source of truth.

SDD is the contract. The other four make sure that contract reaches production intact — from how teams collaborate, to how the system is shaped, to how every change is verified.

SDD

Spec-Driven Development

The contract layer.

Every feature begins with a precise specification. Specs are versioned, queryable, conflict-checked, and consumable by both humans and AI coding agents.

  • Living specs replace stale Word docs and drifting tickets.
  • Conflict detection surfaces contradictions before code is written.
  • Specs power AI agents with scoped, unambiguous intent.
  • Every line of code traces back to an approved requirement.
BMAD

Breakthrough Method for Agile AI-Driven Development

The delivery rhythm.

An agile framework engineered for teams that work alongside AI agents. Explicit roles, structured handoffs, and AI in the planning loop — not bolted on.

  • Defined agent roles: analyst, architect, developer, QA.
  • Each sprint produces verified, spec-traced increments.
  • Human review gates at every critical handoff.
  • Velocity from automation, safety from process.
DDD

Domain-Driven Design

The shape of the system.

We model your business — bounded contexts, aggregates, ubiquitous language — so the codebase reflects how your organization actually operates.

  • Bounded contexts that match your team topology.
  • Ubiquitous language shared by product, ops, and engineering.
  • Aggregates that protect invariants under concurrent change.
  • Anti-corruption layers when integrating legacy systems.
BDD

Behavior-Driven Development

Specs that execute.

Given/When/Then scenarios live alongside the spec — and run as automated acceptance tests. The spec doesn't just describe behavior; it verifies it.

  • Scenarios authored with stakeholders, not just engineers.
  • Every acceptance criterion is an executable test.
  • Regression coverage tied directly to business outcomes.
  • Plain-English documentation that never goes stale.
TDD

Test-Driven Development

The safety net for AI-generated code.

Red, green, refactor — at the unit level. Confidence to ship at high velocity, and to let AI agents touch your codebase without anxiety.

  • Tests authored before implementation, by humans or agents.
  • Refactoring stays cheap because the safety net is dense.
  • AI-generated changes are gated by the existing test suite.
  • Coverage as a property of design, not a metric to chase.
AI in the loop

AI agents that follow specs,
not vibes.

We integrate AI coding agents into the same disciplined workflow your engineers use. Specs are the prompt. Tests are the contract. Humans are the reviewers.

The result: AI accelerates the right things — boilerplate, scaffolding, refactoring, test generation — while critical decisions stay with people who understand the domain.

Scoped prompts

Agents receive only the spec they need.

Test gates

BDD/TDD verifies every agent output.

Human review

PRs reviewed against approved spec.

Audit trail

Every agent action is traceable.

How we engage

From kickoff to handover.

STEP 1

Discovery & spec sprint

We embed for 1–2 weeks, capture domain knowledge, and produce a conflict-free PRD.

STEP 2

Architecture & domain model

DDD modeling sessions, bounded contexts, and a build sequence aligned with your team topology.

STEP 3

Iterative delivery

BMAD-style sprints with AI agents in the loop, BDD tests, and human review gates.

STEP 4

Handover & enablement

We train your team on the methodology so internal teams can keep shipping the same way.

Whether you have a fresh problem space or a stalled AI initiative, we'll bring the methodology and the tooling.