Why do specs drift?

Because code gets urgent and docs get skipped. A hotfix ships without a spec edit, then another, and within weeks the requirements file describes version one while the repo runs version four. Kiro uses the spec as context, so stale specs quietly produce worse code — it is not a loud error, just a slow decline in relevance.

How do you keep a spec current?

• Edit the spec first: when a requirement changes, update the spec before the code.
• Review specs in the PR: treat the requirements file as reviewable as any source file.
• Version the spec: keep it in the repo so its history matches the code’s.
• Trim ruthlessly: delete requirements that no longer apply rather than leaving them as noise.

How do you structure specs for a large project?

Do not keep one giant spec. Split by feature area — auth, billing, search — each with its own requirements, design, and task list. Smaller specs stay readable, are easier to review, and give the agent tighter context. When a feature is done, archive its spec rather than letting it bloat the active set.

What does this cost in practice?

Maintaining specs is a real overhead — budget a fixed slice of each sprint for doc updates, not an infinite polish. The payoff is that AI-generated code stays aligned with intent, which cuts rework. Teams that skip maintenance and then blame the AI for producing irrelevant code have usually let the spec rot, not hit a model limit.

When is a spec not worth it?

Prototypes, throwaway scripts, and spike work do not need a maintained spec. If the code will be deleted in a week, write it directly. Kiro rewards planning on durable systems and slows you down on disposable ones — pick the mode to match the work. If your project is a quick tool, a chat-based editor like Cursor is the lighter choice.

Quick Summary

• Stale specs silently degrade the code Kiro generates.
• Update the spec before the code and review it in pull requests.
• Keep specs in the repo and version them alongside source.
• Split large projects into per-feature specs; archive finished ones.
• Skip specs for prototypes; maintain them for durable systems.

What is Amazon Kiro?

Amazon Kiro is an agentic IDE from AWS. Instead of jumping straight to code, it walks through requirements, a design document, and a task list, then implements each task. It supports multiple model backends and runs as a desktop app. During its preview the tool was free; AWS has indicated usage-based pricing tied to model calls as it matures, so check the current plan before you depend on it.

How does the spec workflow work?

1. Start a feature and write a short description of what you want.
2. Kiro generates a requirements spec and asks clarifying questions.
3. Review and edit the spec — this is the highest-leverage step.
4. Approve the design and task breakdown.
5. Let the agent implement tasks one by one, reviewing diffs as it goes.

The spec becomes a living document. Change the spec and the tasks update, which keeps code and intent from drifting apart.

Why bother with specs when chat coding is faster?

Because chat coding shines on small changes and falls apart on big ones. For a multi-day feature, a spec keeps the agent anchored so it does not forget requirements halfway through. For a one-line fix, the ceremony is overkill and a chat tool is quicker. The right question is scope, not tool loyalty.

How does it compare to other AI editors?

Tools like Zed 2 and Cursor lean on chat and inline edits; Kiro leans on upfront structure. Kiro suits teams that want reviewable requirements and a trail from intent to code. Chat-first editors suit quick iteration and solo work. If your team already lives in AWS, Kiro’s integration with the AWS ecosystem is a real plus.

Where does it fall short?

The spec process adds friction for small tasks, and the generated specs can be verbose enough that reviewing them takes real time. Agentic task loops occasionally wander, so you still review every diff. And as with any AI coding tool, hallucinated API calls need catching. Treat the spec as a contract you own, not boilerplate to rubber-stamp.

Quick Summary

• Amazon Kiro is an AWS IDE that generates specs before writing code.
• Workflow: requirements, design, tasks, then implementation.
• Best for multi-day features; overkill for small edits.
• Specs stay editable and keep code aligned with intent.
• Review every diff; the spec is yours to own.