Spec-driven development, checked against the product you already have
Writing the spec first is the right instinct. It fails when the spec quietly contradicts what the product already does — and the agent builds the contradiction faithfully.
In short
Spec-driven development means writing what should be built — requirements, acceptance criteria and constraints — before an AI agent writes code, then building and checking against that spec. Tools such as GitHub's Spec Kit and Kiro structure the spec and the plan; what they do not know is your existing product. GitMir checks each requirement against a model of it — already works, contradicts a rule, new, or needs a question — turns the new ones into tasks with their own checks, and after delivery shows which requirements the product actually meets.
From spec to checked delivery
- Write the spec
Requirements with IDs, the reason for each, and when it counts as done. A template is on the PRD page.
- Hold it against the product
Each requirement comes back as already works, contradicts — what the spec says against what the product says — new, or needs a question.
- Turn the new parts into tasks
Each task carries the parts of the product it touches and its Done when; a person accepts it.
- Build with the rules
The coding agent gets the rules each task touches over MCP, and each change is checked before it is committed.
- Close the loop
The same document shows, requirement by requirement, what the product now does — not which tickets were closed.
The spec is right about the new and wrong about the old
It contradicts an existing rule
The spec asks for something the product forbids elsewhere. Nobody notices until the agent has built it.
It is silent about what it reaches
A requirement changes one screen and quietly changes a customer path in another area.
Done means tickets
Every task is closed and the requirement is still not met, because the work and the requirement drifted apart.
It drifts after delivery
The product keeps changing, and the spec stops describing it the week after launch.
Write the spec from evidence
Without code there is nothing to check against — so start from a model of the idea instead. GitMir GoBots reads a description into a model, GitMir Market researches the market with sources, and GoBots writes requirements that say why they exist; approved ones become tasks on the board.
The spec, the product and the work in one place
GitMir Intelligence
Check a spec or PRD against your product requirement by requirement, then see what was delivered.
GitMir GoBots
From an idea to a model, market evidence and requirements with reasons — before any code.
GitMir Cloud Compute
Accepted tasks carried out from the same model and committed to your repository.
Asked about spec-driven development
Writing what should be built — requirements, acceptance criteria and constraints — before an AI agent writes code, then building and checking the result against that specification.
Write the spec, check it against the existing product, turn the new requirements into tasks, and give Claude Code the rules each task touches over MCP so it builds within them; each change is then checked against the product before it is committed.
A PRD says what to build and why — the problem, the users and the requirements. A spec adds how: design decisions, constraints and the plan of tasks. In practice teams keep both, and both are checked the same way against the product.
Hold the same document against the product after delivery. GitMir answers requirement by requirement what the product now does, rather than counting closed tickets.
No. They structure the spec and the plan; GitMir checks that spec against the product you already have and gives the agent the rules while it builds.
Give your AI the business logic of your product
Connect a repository and ask it in plain words — 10,000 credits to start, no card.