Spec-Driven Development

Purpose-built engagements that turn AI coding agents into reliable engineering partners — not unpredictable assistants.

LoadSys spec-driven development services help engineering teams move from prompt-and-pray vibe coding to a structured Plan → Execute → Verify workflow. Each engagement targets a specific gap — spec authoring, agent context discipline, verification, or scaled adoption — so your team ships faster with fewer regressions and shipped code that actually matches intent.

Spec-Driven Workflow Foundation

The core engagement that establishes spec-driven development inside your team. We replace the prompt-review-reprompt loop with a structured specification workflow that AI agents can actually follow, turning Claude Code, Cursor, and Copilot into reliable contributors instead of well-meaning guessers.

Spec authoring templates tuned to your stack and conventions
Plan → Execute → Verify workflow integrated with your existing tools
Constitution and constraints layer that locks in architectural decisions
Verification gates so “done” means done, not 30% done

AI Coding Agent Enablement

Hands-on enablement for engineering teams running Claude Code, Cursor, Copilot, or Windsurf. We configure each agent to consume specs as context, set up CLAUDE.md and Cursor Rules files, and train developers on the context discipline that separates teams shipping with AI from teams generating code they can’t trust.

Agent configuration for Claude Code, Cursor, Copilot, and Windsurf
CLAUDE.md, AGENTS.md and project-context file authoring
Spec Kit and Kiro integration into existing CI/CD
Multi-agent orchestration patterns (Coordinator, Implementor, Verifier)

Brunel Agent Deployment

Deploy our flagship AI development planning platform. Brunel sits between dev teams and coding agents, providing a structured Plan → Export → Execute → Verify workflow — eliminating the completion illusion and lifting first-attempt accuracy from 23% to 61% on complex coding tasks.

Brunel deployment with SSO and team workspaces
Plan export to Cursor, Claude Code, Copilot, and Windsurf
Verification harness with automated spec-vs-implementation checks
Team analytics on agent success rate and rework frequency

Solutions

Our spec-driven engagements unlock practical, high-impact outcomes for engineering teams already using AI coding agents. By combining structured specifications, agent context discipline, and verification harnesses, we help teams cut rework, eliminate architectural drift, and ship features the first time instead of the fifth. From greenfield product development to brownfield refactoring, these solutions move your team from “AI is fast but unreliable” to “AI is fast and ships.” Fully tailored to each codebase, they help engineering organizations capture the productivity gains AI coding tools were supposed to deliver.

Greenfield Feature Development

Spec Authoring + Brunel Agent
Engineering teams write a one-page spec, hand it to Claude Code or Cursor, and ship complete features on first attempt. Cuts feature cycles from weeks to days while preserving architectural consistency.

Brownfield Codebase Refactoring

Context Engineering + Multi-Agent Verification
AI agents read existing code, propose changes against a spec, and a verifier agent checks the implementation. Eliminates the “agent rewrites half the file” problem on legacy code.

Architectural Decision Records (ADRs)

Context Engineering + Constitution Files
Capture why your team chose event-driven over request-response, why auth is a separate service, why a particular field is denormalized. AI agents read the ADRs and stop fighting your architecture.

Onboarding & Knowledge Transfer

CLAUDE.md + Spec Templates
New developers get the same context the AI agents do — architecture docs, conventions, landmines. Onboarding time drops from weeks to days, and AI augmentation makes junior devs ship like seniors.

Compliance & Audit-Ready Builds

Spec-Anchored Development + Constitutional SDD
Specs become evidence. Every implementation has a verifiable contract, an audit trail of what was intended, and a constitutional layer that prevents agents from generating code that violates security or regulatory constraints.

AI Agent Productivity Audits

Brunel Analytics + Workflow Assessment
Two-week audit that benchmarks your team’s first-attempt success rate, identifies where agents are drifting from intent, and produces a concrete adoption roadmap. You leave knowing exactly which gaps to close first.