55%
faster task completion with AI assistance
GitHub Developer Survey 2024
Why it matters
The productivity gap is widening
AI tools are available to every development team. What separates the teams delivering faster, more reliable software is whether those tools are embedded in a disciplined process—or used ad hoc, without structure or accountability.
20–45%
reduction in development time with AI-powered engineering
McKinsey, 2024
19%
of teams qualify as elite performers—and the gap is growing every year
DORA State of DevOps 2024
How we work
Methodology first, tools second
The foundation of our AI-assisted practice is SDD: Specification-Driven Development. Requirements are defined and detailed upfront. Specifications become the immovable reference for architecture, implementation, and testing. Nothing gets built without a spec. Nothing gets shipped without validation against it.
AI tools accelerate execution within that structure—they don't replace it. The result is development that moves faster without the unpredictability that comes from skipping the fundamentals.
SDD
Requirements formalized before development begins, used as the foundation for every subsequent decision.
SpecKit
Turns requirements into structured spec.md files readable by both the engineering team and AI tools. One source of truth for the team, the client, and the AI.
Claude Code
AI coding assistant used for implementation, refactoring, test generation, and code review support. Engineers direct the work; Claude Code executes within the spec.
Windsurf
AI-powered IDE used for development acceleration, scaffolding, and integration pattern support.
Claude Design
Used in early-stage prototyping and UI design, compressing the time from requirements to working interface.
Human control at every stage
AI generates. Engineers decide. Every output goes through review, quality gates, and acceptance criteria defined in the spec before it moves forward. No black-box outputs. No code that the team can't explain, maintain, or hand over.
What you get
The outcomes that matter
A well-documented project
Specifications, architecture decisions, and implementation logic are captured as the project progresses—not reconstructed afterward. What we hand over is understandable, maintainable, and yours.
Prototypes in days
AI-assisted design and scaffolding compress the time from brief to working prototype. Decisions that used to take weeks of back-and-forth happen faster—with something to react to, not just describe.
Faster legacy migration
Structured specs and AI-assisted code generation make legacy re-platforming more systematic. Less guesswork, clearer milestones, fewer surprises mid-project.
Shorter cycles, lower costs
AI tooling reduces time on well-understood tasks and eliminates rework loops—freeing engineers for decisions that require judgment, and reducing the total cost of delivery.
