Spec AI reads your codebase, understands your architecture, and turns conversations into detailed technical specifications — ready for implementation.
I analyzed your codebase and found the existing UserService and EventBus. Here's the specification:
3 endpoints · 2 new services · 1 database migration
Implementation plan with 8 tasks
Other AI tools force you to sit there watching code being generated in real time. Spec AI is different — you define what needs to be built, and trigger the implementation when you are ready. Tomorrow, next week, next sprint.
Describe your feature in a quick chat. The AI generates the complete spec while you grab a coffee.
Specs are saved and versioned. Click "Build" when you're ready — not when the AI decides.
The builder reads the spec, implements the code, creates a branch, and opens a pull request. You just review.
9:05 AM
Chat about feature
9:10 AM
Spec generated
...
You do other work
3:00 PM
Click "Build"
3:15 PM
PR ready to review
A real example: from idea to implementation-ready spec in one conversation
You
Spec AI
I found your User entity at internal/entity/user.go and your gateway layer follows a repository pattern. I see you use UUID for IDs and have a clean architecture with usecase/entity/gateway layers.
A few questions before I generate the spec:
You
Spec AI
Here's the complete specification for the Stripe Payment System:
Endpoints
New entities
Subscription
BillingHistory
Plan
Tasks
0
implementation steps
5 minutes of chat. 12 implementation tasks. 1 pull request. Zero time wasted watching AI type.
Three simple steps from idea to detailed technical spec
Link your GitHub or Bitbucket repository. Spec AI indexes your codebase to understand your architecture, patterns, and conventions.
Chat naturally about what you want to build. The AI asks smart questions based on your actual code — not generic templates.
Receive a detailed specification with endpoints, data models, implementation plan, and tasks — all aligned to your existing codebase.
Spec AI is purpose-built for developers who need to move fast without cutting corners
It doesn't guess — it searches, reads, and understands your files, folder structure, and patterns before generating anything.
Specs reference your real services, models, and conventions. No generic boilerplate that you'll have to rewrite anyway.
Specs can be sent to the builder pipeline — Spec AI implements the code, creates a branch, and opens a PR automatically.
Conversations and specs are grouped by project. Come back weeks later and pick up exactly where you left off.
Real-time streaming with SSE. See the AI think and respond as it analyzes your codebase — no waiting for a full answer.
Self-hostable. Your code and specs never leave your infrastructure. No vendor lock-in, no data sharing.
Other AIs give you code snippets. Spec AI gives you the blueprint — then builds it.
We built Spec AI because we were tired of writing specs from scratch and explaining context to AI over and over
Stop spending days writing specs manually. Get a detailed, implementation-ready spec in minutes.
From spec to PR in a single pipeline. The builder implements your spec and opens a pull request automatically.
Every spec follows the same structure. No more missing edge cases, vague requirements, or forgotten migration steps.
Connect your repository, describe your feature, and let AI generate the complete technical specification.