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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesSpec-driven development is not inherently broken. The failure is treating “the spec is the source of truth” as a maintenance plan. A specification can be designated authoritative and still fall out of step with production when implementation changes, incident fixes, or new requirements are not reconciled. The remedy is a maintained contract with testable criteria, visible traceability, and an explicit rule for resolving disagreements—not more process for its own sake.
What does “spec-as-source” mean?
Specification-driven development (SDD) uses a written specification to guide implementation. But “spec-driven” covers different lifecycles, and the distinction matters: a document used to plan a change is not necessarily the enduring contract for the system, much less the sole human-edited source from which code is generated.
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GitHub Spec Kit describes three persistence models. They differ in what happens to the specification after implementation and where future changes are expected to begin.
| Model | What happens to the spec? | Best fit | Main trade-off |
|---|---|---|---|
| Spec-first | Written before coding; it may be discarded after implementation. | Planning and aligning on a bounded change when the document is not intended as a continuing system record. | If discarded, it cannot reliably explain current behavior or guide later changes. |
| Spec-anchored | Retained alongside the implementation and updated as the system changes. | Teams that want a durable account of intent while continuing to edit code directly. | People must reconcile the spec with code as both evolve. |
| Spec-as-source | Edited as the only human-authored source; implementation artifacts are regenerated from it. | A bounded, machine-readable contract for which generation is dependable. | Anything outside the model is not governed by that source; generated artifacts can also omit decision rationale. |
These are lifecycle choices, not interchangeable labels. Spec Kit’s persistence guidance also distinguishes how artifacts change over time: flow-back permits edits to implementation, tasks, plans, or the spec, with later reconciliation required; flow-forward creates new feature directories as requirements change, preserving history but potentially fragmenting it; and a living-spec approach treats the spec as the contract and regenerates or revises plans and tasks, with a risk that rationale disappears from regenerated artifacts.
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Choose a lifecycle and mutation model by asking how reliable regeneration is, how often requirements change, whether audit history matters, how many people coordinate, how drift will be detected, and where decisions will remain recorded.
Why can a spec-as-source workflow fail in production?
Declaring one artifact authoritative does not ensure that it captures what the running system does. Divergence becomes dangerous when a spec looks current but no longer explains deployed behavior. Examples include an incident fix that changes an edge case, a refactor that alters behavior, an implementation that meets a criterion in an unexpected way, or a requirement that changes without a corresponding spec update. The Spec-Driven Development Labs handbook calls this spec/code drift: the concern is not merely that two files differ, but that people can no longer tell which one describes intended or actual behavior. See its discussion of spec/code drift.
Production adds feedback that a pre-implementation document cannot fully anticipate. A deployment may expose a constraint, users may reveal an overlooked case, or an incident may require a fast behavior change. If the workflow permits those changes in code but leaves no adjacent obligation to update the spec or record an exception, divergence becomes silent. Calling the spec “the source of truth” does not resolve that gap.
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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →The problem is especially consequential for protocols and APIs. In RFC 9413, Maintaining Robust Protocols, the IETF Internet Architecture Board states: “For a protocol to have sustained viability, it is necessary for both specifications and implementations to be responsive to changes, in addition to handling new and old problems that might arise over time.” The RFC also warns that when official specifications are neglected, deployed implementations and their quirks can become a substitute standard.
When should a team generate implementation from a specification?
Generation works best where the contract is bounded, structured, and mechanically expressible—and where the team can verify that generated output matches the intended contract. OpenAPI is a concrete example. OpenAPI Specification 3.0.4 describes a language-agnostic interface for HTTP APIs and says an OpenAPI Description can be used by tools to generate documentation, server and client code, and tests.
That is a strong case for generating selected artifacts from a formal API description, not proof that every business rule, organizational decision, or production behavior in a whole application belongs in a generative spec. Keep the boundary explicit: generate what the contract can describe reliably, and maintain surrounding intent and rationale where it can be reviewed.
A spec-anchored workflow is often more suitable when implementation requires substantial judgment, the model cannot express important constraints, or operational behavior must be documented alongside requirements. A team can still automate checks and generate parts of the system without claiming that one document is the only meaningful source.
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What makes a specification maintainable?
A useful spec helps someone test whether the implementation meets the intended behavior and understand what remains uncertain. The following controls synthesize proposals in the Spec-Driven Development Labs version 0.1.0 draft contract; that draft is a proposal, not a universal or established industry standard.
- Record the context. State the problem, affected users, constraints, non-goals, and known open questions so a criterion is not read without its boundaries.
- Make acceptance criteria falsifiable. For each criterion, specify an observation that would show it was not met; avoid wording that expresses an aspiration without a way to verify it.
- Give criteria stable identifiers. IDs let a test, implementation task, review comment, or incident record point to one precise statement even as nearby text changes.
- Assign accountability. Name an owner and review date so the team knows who is responsible for checking whether the contract still reflects intent.
- Trace in both directions. Link implementation work and tests to the criteria they address, then check both for requirements with no implementation and implemented behavior with no stated requirement.
- Define verification beyond generated agreement. A test generated from the same mistaken assumption as the implementation can confirm that both match each other without showing that either matches the need. Include a verification step that can challenge that assumption.
How should a team detect and reconcile drift?
Put reconciliation on the same path as the change. If implemented behavior changes, the change should either update the specification or record an explicit, reviewable decision that the spec is intentionally lagging. Attach that choice to pull-request review or CI where practical, instead of leaving it as an untracked future chore.
- Identify the changed behavior. In a pull request or incident record, describe what users or systems will observe differently, not only which files changed.
- Map it to the contract. Link the change to the relevant criterion IDs. If no criterion covers it, decide whether the behavior is a new requirement, an implementation detail, or an exception that should be documented.
- Check both directions. Verify that applicable criteria have implementation and tests, and that material implemented behavior has an intentional basis in the contract or a recorded exception.
- Reconcile before closing the change. Update the spec and its tests, or record who accepted the divergence, why, and when it will be reviewed. Avoid leaving the reason solely in a transient chat or an unlinked commit.
- Revisit temporary divergence. Once an incident response or migration has stabilized, resolve the exception by bringing implementation back to the contract or revising the contract to reflect the intended behavior.
Before an incident, state what wins when the spec and deployed behavior disagree. Intended behavior in the spec may govern a planned change, while actual behavior may need to govern immediate incident response; a designated incident decision can authorize a temporary exception. The important point is to name the authority for each situation and record the decision, rather than let “source of truth” remain an untested slogan.
How much process is enough?
Use stronger planning and traceability when risk, requirements, or coordination justify their cost. For a small and obvious change, a full specification lifecycle can cost more than it returns. Microsoft’s June 10, 2026 article, “Spec-Driven Development: A Spec-First Approach to AI-Native Engineering,” argues that structured shared specs can reduce ambiguity and says not every change needs the full lifecycle. Treat this as Microsoft’s reported practice and guidance, not independent proof that SDD produces a particular outcome.
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Microsoft also reports that onboarding time for new asset types in one brownfield example fell from “2–3 weeks to a few days” after reusable, parameterized specifications were introduced. This is a single vendor-authored case, not a controlled comparison or a general productivity benchmark. The available sources do not establish an independent controlled comparison or a broadly generalizable SDD outcome statistic.
What should teams take away?
Choose the lifecycle that matches the contract: discard a spec-first plan when it was only for planning, maintain a spec-anchored record when intent must live beside evolving code, and use spec-as-source where reliable generation covers a genuinely bounded surface. In all three cases, make changes traceable, define how disagreement is resolved, and ensure important decisions survive beyond generated artifacts. The production failure is not specification itself; it is allowing the declared source of truth to diverge without a visible reconciliation rule.
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