This is week 2 of my "I Used It for a Week" series. Last week I reviewed Cursor — the AI editor that blew me away with its Tab predictions and agent mode. This week, I tried something fundamentally different.
After a week with Cursor, I thought I knew what AI coding tools were about: fast autocomplete, multi-file agents, and Tab-Tab-Tab your way through boilerplate. Then I opened Kiro, and it asked me to write a spec before touching any code.
That threw me off. In a good way.
What Is Kiro, Actually?
Kiro is AWS's AI-powered IDE. Like Cursor, it's built on VS Code, so the switch is painless. But the philosophy is completely different. Where Cursor says "let me write that code for you," Kiro says "let's figure out what we're building first."
They call it spec-driven development, and it follows a structured workflow:
- Discuss — you describe what you want in plain language
- Spec — Kiro generates formal requirements
- Design — it creates a technical design document
- Tasks — it breaks the work into implementation steps
- Build — then it writes the code
It sounds heavy. It is, a little. But after a week, I understand why it exists.
Day 1: The Spec Workflow
I started with a real task: building a notification system for a side project. In Cursor, I would've just said "build me a notification component" and started accepting suggestions. In Kiro, I opened a spec.
Kiro asked me clarifying questions I hadn't thought about. What triggers a notification? Do they persist or auto-dismiss? What about mobile? Do we need a notification center? Rate limiting?
By the time the spec was done, I had a proper requirements document. The kind of thing a product manager would write — except it took 10 minutes instead of a meeting.
Then Kiro generated a design document with component architecture, data flow, and API contracts. Then it broke it into tasks. Then it started coding.
The code it produced was noticeably more complete than what I typically get from Cursor's agent mode. Fewer edge cases missed, better error handling, proper TypeScript types from the start. The spec gave it enough context to get things right on the first pass.
What Blew Me Away
The spec is the context
This is Kiro's killer insight. In Cursor, I spent a lot of time crafting prompts and using @file references to give the AI enough context. In Kiro, the spec is the context. Every task the agent executes has the full requirements and design document behind it.
The result: less back-and-forth, fewer "that's not what I meant" moments, and code that actually matches what I wanted.
Agent Hooks
Kiro has this feature called Agent Hooks — automated triggers that fire when certain things happen. I set up hooks to:
- Run tests automatically when implementation files change
- Update documentation when API contracts change
- Run linting on every save
It's like having a CI pipeline inside your editor. Cursor has nothing like this — you'd have to manually ask the agent to run tests or update docs.
Steering files
Similar to Cursor's .cursorrules, Kiro has Steering — project-level instructions that guide the AI's behavior. But Kiro's version feels more integrated. You can define coding standards, architecture patterns, and even reference external documentation. The AI follows these consistently across all spec-generated tasks.
It actually slows you down (in a good way)
This sounds like a criticism, but hear me out. With Cursor, I caught myself accepting suggestions without reading them. The speed was addictive but dangerous. Kiro's spec workflow forces you to think before you code. You review requirements, approve the design, then watch the implementation.
I shipped fewer bugs this week. That's not a coincidence.
What Frustrated Me
The spec workflow is overkill for small tasks
Need to rename a variable? Fix a typo? Add a CSS class? You don't need a requirements document for that. Kiro's spec mode is brilliant for features but painful for quick fixes.
Kiro does have a "vibe" mode for quick tasks (basically a standard chat), but it feels like an afterthought compared to the polished spec workflow. Cursor is significantly better for rapid, small edits.
Pricing drama
Kiro launched with a generous free preview, then introduced pricing that upset a lot of developers. The free tier lost access to spec mode entirely. The paid plans have request limits that heavy users burn through quickly, with overage charges of $0.04 per vibe request and $0.20 per spec request.
There was even a pricing bug in early March 2026 that drained developer limits faster than expected — AWS blamed it on a bug, but trust was damaged.
For comparison: Cursor Pro is a flat $20/month with unlimited completions. Kiro's costs can be unpredictable if you're a heavy user.
Performance under load
During the preview period, Kiro hit capacity issues. AWS introduced waitlists and usage caps within a week of the public preview launch. Performance has improved since, but I still hit occasional slowdowns during peak hours — something I rarely experience with Cursor.
Less community and ecosystem
Cursor has a massive community, tons of .cursorrules templates, and years of user feedback baked into the product. Kiro is newer and it shows. Fewer tutorials, fewer community resources, and the documentation still has gaps. One reviewer noted that "the official docs only tell part of the story, leaving you to guess if it really works as promised."
Kiro vs Cursor: Head to Head
| Kiro | Cursor | |
|---|---|---|
| Philosophy | Plan first, code second | Code fast, iterate |
| Best for | Features, new projects | Refactoring, quick edits |
| Spec workflow | ✅ Full requirements → design → tasks | ❌ No equivalent |
| Tab completion | Basic | ✅ Best-in-class (next-edit prediction) |
| Agent hooks | ✅ Automated triggers | ❌ Manual only |
| Multi-file editing | ✅ Good (spec-guided) | ✅ Excellent (subagents) |
| Codebase indexing | Good | ✅ Deep semantic search |
| Model choice | Claude (Sonnet/Opus 4.6) | GPT-5, Claude, Gemini |
| Pricing | Usage-based, can spike | $20/mo flat |
| Community | Growing | ✅ Large, established |
Claude Sonnet and Opus 4.6 Under the Hood
Kiro runs on Anthropic's Claude models — Sonnet 4.6 for most tasks and Opus 4.6 for complex reasoning. Having used both through Kiro for a week:
Sonnet 4.6 handles the day-to-day spec generation and routine coding. It's fast, follows instructions well, and the 200K context window (1M in beta) means it can hold your entire spec + codebase in memory. At $3/$15 per million tokens, it's the workhorse.
Opus 4.6 kicks in for complex architectural decisions and multi-step reasoning. You can feel the difference — responses are slower but more thorough. The 128K output limit means it can generate entire feature implementations in one pass. At $5/$25 per million tokens, it's expensive but worth it for the hard stuff.
The combination works well. Kiro seems to route intelligently between them — simple tasks get Sonnet's speed, complex tasks get Opus's depth. It's the model routing strategy I mentioned in the Gemini vs Opus comparison — use the cheap model for bulk work, the expensive one for the hard problems.
My Verdict After 7 Days
Kiro made me a more disciplined developer. The spec workflow caught requirements I would've missed, and the code quality was consistently higher than what I get from pure "vibe coding" tools.
But it's not my daily driver. For the way I work — lots of small edits, quick iterations, jumping between files — Cursor's speed and Tab completion are hard to beat. Kiro shines when I'm starting a new feature from scratch or working on something complex enough to warrant a spec.
My ideal setup: Kiro for planning and building new features. Cursor for everything else. They're not really competitors — they're complementary tools with different philosophies.
Would I keep paying? Yes, but only for the feature-building sessions. I wouldn't use it for daily coding the way I use Cursor.
Who should try it:
- Developers who want more structure in their AI workflow
- Solo founders building MVPs (the spec workflow prevents scope creep)
- Teams that value documentation and requirements
- Anyone frustrated by AI tools that write code without understanding what they're building
Who should skip it:
- Developers who mostly do quick edits and refactoring
- Anyone on a tight budget (costs can be unpredictable)
- People who find specs and planning documents tedious
Tips If You're Starting
- Use spec mode for features, vibe mode for fixes — don't force the spec workflow on everything
- Set up Agent Hooks early — auto-running tests on save is a game changer
- Write good Steering files — same advice as Cursor's .cursorrules, but even more important here since specs amplify your instructions
- Review the generated spec carefully — garbage spec = garbage code, no matter how good the AI is
- Budget for overages — track your usage in the first week to avoid surprises
Next week: I Used GitHub Copilot for a Week — the tool 4.7 million developers pay for. Is it still worth it in 2026, or have Cursor and Kiro left it behind?
Originally published at https://www.aimadetools.com
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