Cursor vs Kiro: Which AI IDE Should You Use?

Two Very Different Bets on What an AI IDE Should Be

If you've been watching the AI developer tooling space in 2025, you've noticed two distinct philosophies competing for your workflow. Cursor — the San Francisco startup that turned VS Code into an AI-native editor — has accumulated hundreds of thousands of paying developers by perfecting the inline-edit, chat-with-your-codebase loop. Amazon Kiro, released in preview in mid-2025, is betting on something fundamentally different: that the right time for AI to intervene isn't when you're writing code, but before you write a single line.

This comparison is written for developers, technical leads, and engineering teams who are evaluating both tools for real production work — not side projects. The honest answer is that these two IDEs are not direct substitutes. They optimize for different stages of the software development lifecycle (SDLC), and choosing the wrong one for your use case will cost you either money, autonomy, or time. We'll break down what each tool actually does (versus what the marketing implies), where each one genuinely earns its place, and where both fall flat.

One framing note before we dive in: Cursor is best described as an AI-assisted editor with autonomous agent capabilities — meaning most of its value comes from copilot-style inline completions and a supervised agent mode for multi-file edits. Kiro is better described as a spec-driven supervised agent — it takes a higher-level brief, produces structured planning artifacts, and then generates code across files. Neither is fully autonomous in the "deploy it and walk away" sense.

Architecture and Models: What's Under the Hood

Cursor

Cursor is a fork of VS Code, so your extensions, keybindings, and settings largely transfer. It supports multiple frontier models selectable per request: Claude Sonnet 4, Claude Opus 4, GPT-4o, and o3 are available on Pro and Business tiers. The context window varies by model — Claude Sonnet 4 supports 200K tokens, which Cursor uses for its "codebase context" feature, where it indexes your repo and retrieves relevant files into the prompt automatically via embeddings-based retrieval.

Cursor's agent mode (formerly called "Composer" in agent mode) can autonomously open files, run terminal commands, read error outputs, and iterate on a multi-file task without you pressing accept after each step — though it will pause and surface errors for you to review. The model doing the heavy lifting is whichever you've selected; Cursor itself is the orchestration and UI layer. Fast requests on Pro use Claude Sonnet 4 or GPT-4o by default; slow requests fall back to less capable model versions.

Amazon Kiro

Kiro is also built on VS Code. It's powered by Amazon Bedrock, and the default model in preview is Claude Sonnet 4 (via Bedrock's API). Amazon has indicated that Kiro will support multiple Bedrock-hosted models over time, which would include Nova and Titan model families as well as Anthropic's hosted on Bedrock.

The architectural difference that matters: Kiro introduces a structured planning layer between your prompt and code generation. When you start a feature with Kiro, it first generates a spec document — a structured requirements artifact — then produces a design document with architectural decisions, then breaks the work into a task list before writing any code. This is not a chat thread; these are persistent, editable project files. You can edit the spec before Kiro proceeds. This is closer to how a staff engineer might operate than how a fast inline autocomplete works.

Kiro also introduces "hooks" — automated agents that fire in response to file system events. For example, a hook can regenerate your test suite every time a source file changes, or update your API documentation whenever the implementation changes. This is a meaningfully different capability from anything Cursor currently offers.

Pricing: What You'll Actually Pay

Cursor Pricing (as of mid-2025)

• Hobby (Free): 2,000 code completions/month, 50 slow premium model requests. Sufficient for evaluation, not for daily professional use.
• Pro ($20/month): 500 fast premium requests (Claude Sonnet 4, GPT-4o, etc.), unlimited slow requests, background agent access. This is the tier most individual developers use.
• Business ($40/user/month): Everything in Pro plus centralized billing, admin controls, privacy mode enforced org-wide, and SSO (Single Sign-On). Relevant at team scale.

One cost you need to model carefully: Cursor Pro's 500 fast requests can evaporate faster than you expect if you're running long agent sessions. Each back-and-forth in agent mode consumes fast requests. Heavy users on Pro routinely hit the limit before the month ends and are pushed to slow (degraded) model access. Cursor does sell additional fast request packs, but this isn't prominently advertised. Check the official cursor.com/pricing page for current add-on options.

Kiro Pricing (as of mid-2025)

Kiro is in public preview and currently free. Amazon has not announced post-preview pricing tiers. When pricing is released, it will almost certainly be tied to Bedrock API consumption — meaning your actual cost will depend on the number and length of prompts you fire through the spec + design + task pipeline, which is meaningfully heavier per feature than a simple inline edit. Until Amazon publishes a pricing page, treat cost as an unknown variable and verify at kiro.dev before committing.

Workflow Comparison: How Each Tool Changes How You Code

The Cursor Loop

Cursor's core workflow is: you write or select code, you invoke the model (inline with Cmd+K for edits, or chat for broader questions), the model responds, and you accept or reject the diff. The agent mode extends this to multi-file tasks — you describe what you want built, the agent opens files, edits them, runs terminal commands, reads output, and loops until the task is done or it surfaces a problem. The feedback loop is fast and tightly integrated with your existing habits.

For experienced developers who know what they want and can review AI output quickly, Cursor's model is efficient. You stay in control, you move fast, and the model acts as a capable but supervised junior engineer. The risk: if you're not reviewing output carefully, you accumulate subtle drift — code that works locally but has architectural problems that compound over time.

The Kiro Loop

Kiro's loop is more deliberate: you describe a feature at a high level, Kiro generates a requirements spec, you review and edit it, Kiro generates a design document with architectural decisions, you review that, Kiro generates a task list, and then it begins executing task by task. The upfront investment is higher — you might spend 10-15 minutes in the spec review phase before a line of code is written. The payoff is that the generated code is more architecturally coherent and the agent is less likely to drift because it's working against a structured plan.

Kiro's hooks are worth calling out separately. A hook is an agent that fires automatically based on events — "when this file changes, do X." Out of the box, Kiro ships with hooks for test generation (auto-generates tests when source changes), documentation (updates docs when API signatures change), and security scanning. These run in the background and surface changes for your review. This is a genuinely different capability than anything in Cursor today.

Greenfield vs. Existing Codebases

For greenfield projects where you're defining requirements and architecture from scratch, Kiro's spec-driven flow adds real value. The spec becomes a persistent document you can share with your team. The design doc captures decisions. The task list is a living project plan. For a solo developer building a new SaaS, this scaffolding is useful structure. For a large team, it's a forcing function for alignment.

For existing codebases — especially large, complex ones — Cursor currently has an edge. Its codebase indexing and retrieval system gives the model broad context over your existing code, and the inline editing loop is faster for the "change this function, fix this bug, refactor this module" work that dominates day-to-day development. Kiro's spec-first approach can feel like overhead when you already have defined requirements and just need implementation.

Where Cursor Falls Short

Being direct about failure modes is more useful than summarizing features you can read on the product page.

1. Fast request exhaustion. At $20/month, 500 fast requests sounds like a lot. An active agent session on a complex feature can consume 20-40 fast requests in a single working session. Power users reliably hit the cap mid-month and deal with noticeably slower completions. For team leads running multiple long agent sessions daily, Business tier at $40/month may still not be enough without monitoring usage carefully.
2. Context drift on large codebases. Cursor's retrieval system is good, but it's not perfect. On codebases above ~100K lines, the model frequently retrieves non-optimal context, leading to suggestions that are locally valid but architecturally inconsistent with how the rest of the codebase is structured. You'll catch these in review — but only if you're reviewing carefully.
3. Agent mode on ambiguous tasks. If you give agent mode an underspecified task on a large codebase, it will fill in assumptions. Sometimes those assumptions are reasonable. Sometimes the agent makes a confident series of wrong choices across five files before you notice. The fix is to be more specific — but that requires you to know enough to be specific, which reduces the leverage the agent provides.
4. No structured planning artifacts. Cursor's approach is entirely procedural — there's no persistent spec, no design document, no task list. If you want those artifacts, you're writing them yourself in a separate tool or not at all. For teams that need audit trails or cross-functional alignment, this is a real gap.
5. Privacy on Pro tier. Cursor stores prompt and code data by default unless you're on Business with privacy mode enabled. Solo developers and small teams on Pro should read the privacy policy carefully before feeding proprietary code into the tool.

Where Kiro Falls Short

1. Preview-stage reliability. Kiro is in public preview as of mid-2025. Preview software has preview-stage reliability. The spec-generation pipeline has documented failure modes where the design document contradicts the spec, or the task list doesn't fully map to the design. These are solvable problems, but you need to review each artifact carefully — the pipeline is not yet reliable enough to execute end-to-end without supervision.
2. Model lock-in to Bedrock. Cursor lets you select Claude Sonnet 4, Claude Opus 4, GPT-4o, or o3. Kiro is tied to Amazon Bedrock's model catalog. If you want to use a model that Bedrock doesn't host, you're out of luck. For teams with strong preferences for specific frontier models, this is a real constraint.
3. Overhead on small or simple tasks. For a task that takes an experienced developer 15 minutes — fix a bug, update an endpoint, refactor a small class — Kiro's spec + design + task pipeline is overkill. You'll spend more time reviewing Kiro's planning artifacts than you would have spent just writing the code. Cursor is faster here, full stop.
4. Unknown post-preview pricing. This is not a minor concern. Kiro's spec-driven pipeline is LLM-call-intensive — each feature triggers multiple large-context prompts (spec generation, design generation, task generation, then code generation). When AWS prices this against Bedrock API consumption, the per-feature cost could be substantially higher than Cursor's flat monthly rate. You cannot model this today.
5. Smaller ecosystem and community. Cursor has two-plus years of user-reported workflows, prompt strategies, and documented edge cases across Reddit, Discord, and blog posts. Kiro's community is nascent. If you hit an edge case, you're more likely to be debugging it yourself rather than finding a prior solution.

Who Should Use Cursor

Cursor is the better choice if: you're working primarily on an existing codebase; you want model flexibility (Claude, GPT-4o, o3 in the same editor); you value a fast inline editing loop over structured planning; you're a solo developer or small team that needs to ship iteratively; or you're already comfortable reviewing AI output quickly. At $20/month for Pro, it's genuinely cost-effective for the value delivered — assuming you stay within the 500 fast request limit or are willing to supplement with slow requests.

Cursor is also the better choice today for developers who can't afford to be on experimental preview-stage tooling in their primary editor.

Who Should Use Kiro

Kiro is worth serious evaluation if: you're starting a new project and want structured planning artifacts baked into the IDE; your team is AWS-native and values first-party service integration; you find that AI-generated code tends to drift architecturally and you want a higher-level planning loop to prevent that; or you want to evaluate what event-driven agent hooks look like in a real development workflow. During the free preview period, the cost of evaluation is just your time.

If your team already uses Lindy or similar agent platforms for workflow automation, Kiro's hooks architecture will feel conceptually familiar — it's the same idea of event-driven agent triggers, applied to the development environment itself.

Kiro is not ready to be your primary daily driver if you're on a production deadline. Give it another six to twelve months of maturity, or run it in parallel on greenfield side work while keeping Cursor for production codebases.

Bottom Line

Cursor and Kiro are answering different questions. Cursor asks: "How do I make the code-writing loop faster and smarter?" Kiro asks: "How do I make the entire feature development process — from requirement to deployed code — more coherent?" If you're doing mostly iterative work on existing code, Cursor wins on speed and practicality today. If you're building new products and want structured planning as a first-class IDE feature, Kiro's approach is conceptually sound and worth watching — but you're betting on a preview-stage product with unknown post-launch pricing.

The pragmatic recommendation for 2025: use Cursor Pro at $20/month as your primary IDE, and run Kiro in parallel on a new project to evaluate whether the spec-driven workflow genuinely improves your architectural consistency. Kiro is free during preview — the evaluation cost is just time. Make your decision on post-preview pricing once Amazon announces it. Neither tool is going away, and the right answer may simply be that different projects in your portfolio benefit from different approaches.

AI tools and agents change rapidly. Verify current capabilities and pricing at cursor.com/pricing and kiro.dev before making a purchasing decision.

Disclosure: We earn referral commissions from select partners. This doesn't influence our reviews — we recommend based on research, not revenue.