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A useful spec makes the intended behavior and success conditions clear before implementation begins. It explains the problem, who the work serves, what the system should do, and how the team will know it works. A technical plan then describes how to build it; tasks break that approach into work that can be implemented and checked.
What a spec should capture
A spec records intent in a form that developers, product teams, and AI coding agents can use without guessing at the desired outcome. GitHub’s Spec-Driven Development overview frames specification as an iterative way to describe what is being built and why. Microsoft’s June 10, 2026 overview also identifies requirements, constraints, acceptance criteria, guardrails, and edge cases as core inputs.
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Context and intended outcome
State the problem, the people affected, and the outcome the work should produce. A feature name alone is not enough: “add exports” does not say who needs them, what information should be exported, or what problem the feature solves.
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Describe the situations the product must handle and the expected behavior in each. Cover the ordinary user journey as well as meaningful alternatives and failure cases. Prefer observable behavior: a reviewer should be able to determine from the product’s behavior whether a requirement has been met.
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Acceptance criteria
For each important requirement, say how a person or test can verify it. Criteria should be specific enough to guide implementation and validation, but there is no single universal format prescribed by the cited guidance. Generated specifications still need human review for missing cases and mistaken assumptions.
Constraints and guardrails
Record boundaries that materially affect the solution, such as security or compliance obligations, required integrations, design-system rules, organizational standards, performance targets, or mandated technologies. GitHub’s overview notes that these requirements can otherwise be scattered across informal sources. Include constraints that apply to this work rather than accumulating rules that do not affect it.
What belongs in the plan instead
The spec answers what outcome is required; the plan explains a chosen technical route to it. In GitHub’s documented workflow, the specification focuses on user journeys, experience, and success criteria, while planning addresses matters such as stack and architecture. Microsoft’s overview similarly separates requirements from technical planning.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesA plan can describe architecture, technology choices, flows, and implementation constraints. The distinction is useful, not bureaucratic: teams may keep artifacts together or separate them, provided readers can tell which statements define required behavior and which describe the proposed way to achieve it.
How contracts clarify component boundaries
When one component depends on an interface exposed by another, define their observable agreement before dependent implementation. A contract can cover:
- Accepted inputs, produced outputs, formats, and validation rules.
- Expected behavior, errors, side effects, and relevant guarantees such as idempotency or ordering.
- Retries, timeouts, compatibility, and versioning where they matter to consumers.
- Examples and criteria for verifying that the interface behaves as agreed.
The level of detail should fit the interface. A schema may specify data shape without explaining behavioral semantics such as retries or ordering. GitHub’s contract-driven development guide also recommends an authoritative owner and involving consumers in agreements about changes. Keep internal design decisions out of the contract unless they affect the interface.
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How the artifacts guide delivery
Specifications, plans, tasks, implementation, and validation are connected stages, not isolated documents. GitHub’s documented core path is Specify → Plan → Tasks → Implement → Converge. Microsoft’s June 2026 article describes a broader seven-stage approach that adds principles and guardrails, clarification, and validation. These are examples, not a mandatory universal lifecycle.
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- Specify: describe the problem, intended users, scenarios, behavior, and success criteria.
- Clarify: resolve ambiguity and identify dependencies, constraints, and important edge cases.
- Plan: choose the technical approach and record architecture and implementation decisions.
- Create tasks: divide the plan into small pieces with a clear purpose and a way to check each result.
- Implement: carry out the tasks while keeping their connection to the requirements visible.
- Validate and converge: review the result against the spec, correct gaps, and refine the artifacts as needed.
A task is more useful when it is implementable and testable in isolation and traceable to the requirement it serves. Validation then checks the result against the agreed behavior rather than relying only on whether the code compiles or a feature appears to work on the happy path.
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Keep the spec right-sized and current
Start with a lightweight spec and pilot the approach on work where alignment problems are visible. Review the output, clarify what was missed, and refine the team’s practice before scaling it. Microsoft recommends iteration and warns against specifying more than teams need before they learn from the work.
Requirements change, so teams should decide who updates the spec, plan, tasks, and interface contracts, and how changes are communicated. GitHub’s Spec Kit concept page does not prescribe how teams preserve or modify these artifacts after requirements evolve; ownership and change handling need to be agreed within the team.
There is no independent quantitative evidence in the cited material establishing average productivity, quality, or cost gains from spec-driven development. Microsoft’s article gives one team example in which asset onboarding moved from two to three weeks to a few days, but that is a vendor-authored case example, not a controlled study or a general forecast. The durable rationale for a spec is more modest: make intent, constraints, and verification explicit so a team can reason about the work before and during implementation.
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