Spec-driven AI development
AI writes the code. Specifications keep it on track.
AI coding agents are fast, but without structure they produce code that drifts from what you actually need. Spec-driven development (SDD) solves this. Requirements, architecture and acceptance scenarios are written and approved before any code is generated. The AI then implements against the spec, and every change can be traced back to a decision. We use this approach to deliver new products faster and to safely modernize existing systems.
What we offer
Greenfield product development
We take you from idea to production with a spec-first workflow. Requirements, architecture, data model and API contracts are defined up front. AI agents then implement them under senior engineer review.
Legacy modernization
We analyze your existing system and document its architecture, database and behavior. Then we plan and execute upgrades such as framework migrations, Java/Spring version upgrades and refactoring. We work change by change, with specs as the safety net.
Multi-agent development pipelines
We set up coordinated AI agents for frontend, backend and code review. They pick up tasks from Jira, implement against specifications and hand off to human reviewers.
SDD workflow setup for your team
We bring spec-driven tooling (OpenSpec, GitHub Spec Kit, Claude Code, Cursor) into your repositories. That includes project context, coding conventions, agent instructions and spec validation in CI. We also train your developers to use it.
Codebase documentation & spec audits
We produce architecture overviews, database documentation and behavior specs from your existing code, all verified by engineers. These are useful for onboarding, due diligence and handovers.
How it works
Discovery
We learn your goals, constraints and existing systems.
Specification
We write requirements, scenarios, architecture and data model. You review and approve them before development starts.
AI-assisted implementation
Agents build against the approved spec, and engineers review every change.
Verification
Automated tests and checks confirm the code matches the spec.
Living documentation
Specs live in your repository and are updated with every change.
Why spec-driven
Predictable results
You approve what gets built before it’s built.
AI speed with engineering discipline
You get fast delivery without chaotic code.
Documentation that stays current
Specs evolve with the code instead of going stale in a wiki.
Easier handovers
Any developer, or AI agent, can understand why the system works the way it does.
Lower risk on legacy systems
Every change is scoped, reviewed and traceable.
Selected work
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