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Agentic spec-driven development (Agentic-SDD) gives Claude Code work a reviewable path from intent to implementation: write down the behavior and constraints, plan the technical approach, break the plan into tasks, then test, review, and update the project record. The artifacts make decisions and handoffs easier to inspect; they do not guarantee correct code or remove the need for human judgment.
What Agentic-SDD means for Claude Code
Agentic-SDD is a way to organize agent-assisted software work around durable specifications and plans rather than relying on a long prompt or conversational memory. The core loop is:
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- Record the problem, intended behavior, acceptance criteria, constraints, and non-goals.
- Resolve consequential ambiguity and review the specification.
- Translate the accepted specification into technical decisions and a plan.
- Break the plan into inspectable tasks.
- Implement against those artifacts, run checks, and review the changes.
- Feed findings from review, deployment, and maintenance back into the project record.
This is a recommended engineering process, not a built-in Claude Code mode or a single required framework. GitHub’s Agentic SDD documentation describes one command-oriented implementation. SpecDD shows a repository-local approach, while a community Claude Code plugin is another example rather than an Anthropic standard.
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1. Write intent before choosing the implementation
Start with the user-facing problem and the result people should observe. Include acceptance criteria, relevant constraints, and explicit non-goals. Keep technology choices out of the intent document unless they are genuine requirements; otherwise, premature implementation detail can obscure what the change is meant to accomplish.
In Spec Kit, /speckit.specify creates or updates a natural-language feature specification focused on behavior and goals rather than the technology stack. For an ongoing project, concise specifications can also live near the code they govern. SpecDD describes small, human-readable .sdd files placed alongside code or project areas, with bootstrap instructions for the agent. That is a project convention, not a Claude Code feature.
2. Clarify ambiguity that could change the solution
Ask targeted questions when missing details could alter scope, acceptance, or design. Spec Kit’s /speckit.clarify asks up to five questions about the current specification; its guidance recommends doing this before planning when ambiguity could lead to designing the wrong solution.
Not every small change warrants a full specification ceremony. Scale the review effort to the change’s risk, uncertainty, and scope. That is a practical judgment, not a measured rule established by the cited implementations.
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3. Plan technical choices separately
Once the intended behavior is clear, use a plan to capture architecture, stack choices, technical constraints, and the implementation approach. Spec Kit’s /speckit.plan creates design artifacts from the specification. Keeping this step distinct lets reviewers challenge an implementation choice without silently changing the feature’s purpose.
4. Turn the plan into tasks people can inspect
Spec Kit’s /speckit.tasks generates dependency-ordered tasks, grouped into setup, foundational work, user-story phases, and polish. That structure can help a team assign work, inspect progress, and resume a project. It is Spec Kit’s implementation of task breakdown, not a universal SDD format.
5. Review the artifacts before asking for implementation
Use a requirements checklist to find gaps or ambiguity in the specification, and an artifact consistency check to find conflicts across the specification, plan, and tasks. In Spec Kit, checklist and analyze are optional quality gates; only specify is strictly required before plan. A checklist is not a code test, and an agent-generated checklist does not approve itself: people should retain ownership of acceptance decisions.
6. Implement, test, and review
Let the coding agent work through the tasks, but require evidence of what changed and how it was checked. That evidence can include code changes, test results or other validation, and review findings. Spec Kit describes implementation followed by convergence against its artifacts. Anthropic’s AI-Native SDLC playbook describes continuous evaluation during implementation and layers of agent review, while reserving human review for regulated and critical code.
Make discrepancies visible rather than forcing the implementation to appear compliant. If a test fails, a requirement proves infeasible, or the plan no longer fits, update the relevant artifact and review the change in scope before continuing.
7. Carry operational findings back into the project record
Development does not end at merge. Anthropic’s playbook proposes treating deployment and maintenance as part of the lifecycle: agents monitor deployments, and a breached control band can be diagnosed and recorded as new intent. This is a proposed AI-native SDLC approach, not a universal capability or a confirmed Claude Code feature.
Where to keep the artifacts
Keep the context needed for future work in version-controlled files so a later agent session can recover the accepted decisions without depending on chat history. Anthropic’s lifecycle guidance describes committed handoff artifacts such as intent.md, spec.md, plan.md, code and tests, pull-request review findings, and incident records.
There is no single required directory layout in these examples. A team can use framework-generated documents or small files colocated with the relevant modules; the important distinction is that the artifacts are durable, reviewable, and discoverable by the agent and people working on the code.
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Choosing an implementation approach
The options below illustrate different ways to put the process into practice. The comparison describes documented approaches, not benchmarked performance.
| Approach | Artifact and workflow | Adoption characteristics |
|---|---|---|
| GitHub Spec Kit | Command-oriented sequence for specification, clarification, planning, checklist, tasks, analysis, implementation, and convergence. | Provides explicit command roles; some quality gates are optional. |
| SpecDD | Repository-local, human-readable .sdd files with bootstrap guidance for file-aware agents, including Claude Code. |
Can be introduced around the modules or features actively changing rather than through a full-project rewrite. |
| Community Claude Code SDD plugin | Claude Code-specific plugin example with specialized agents and phased plans. | A community implementation, not official Anthropic guidance or a standard. |
Evaluate a workflow against the team’s actual needs:
- Artifact location and format: Can people find, version, and review the files that carry project intent?
- Agent compatibility: Does the process work with the coding agent the team uses?
- Prescriptiveness: Does the workflow provide useful structure without requiring unnecessary steps for small changes?
- Incremental adoption: Can it be applied to active work without rewriting every project document?
- Maintenance burden: Will the team keep its instructions and artifacts current?
- Reviewability: Can a human reviewer clearly judge whether the implementation satisfies the accepted specification?
What the process can—and cannot—establish
Specifications and plans improve traceability by making intent, technical decisions, and review points explicit. The cited material does not establish that this exact Agentic-SDD process improves delivery speed or software quality, and it does not show that a particular plugin is necessary.
Anthropic frames faster code generation as shifting bottlenecks toward planning, review and testing, and deployment, and cautions that controls designed around human-written code may not keep pace with agent output. That is the vendor’s guidance based on its applied work and customer experience, not an independent controlled study of Agentic-SDD. No named statistic in the cited sources measures outcomes for this specific workflow.
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Use the process to expose decisions and create checkpoints—not as proof that an agent’s output is correct. Specs cannot guarantee correctness, eliminate hallucinations, or make human review unnecessary, particularly for regulated or critical code.
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