Spec-Driven Development vs Vibe Coding: Why Kiro Bets on Writing It Down
While exploratory "vibe coding" is excellent for fast prototyping, it relies on ephemeral chat threads that often lead to context loss and codebase bloat over time. To solve this, the AI platform Kiro champions "spec-driven development," a structured approach that translates explicit intent into version-controlled requirements and designs before any code is generated.
TL;DR: Vibe coding is fast and fun, but it loses every decision into a disposable chat thread and tends to bloat your codebase. Spec-driven development, the approach Kiro is built around, makes intent explicit and version-controlled before any code is written. The result holds up on large codebases and across teams. This post breaks down the real difference, the data on why unstructured AI coding gets expensive, and when each approach actually wins.
Key Takeaways
- Vibe coding optimizes the first iteration; spec-driven development optimizes the whole lifecycle. One is for discovery, the other for systems that have to last.
- The hidden cost of vibe coding is measurable. GitClear’s analysis of 211 million lines of code found copy-pasted code exceeded refactored code for the first time in 2024, with code duplication up roughly eightfold.
- Kiro splits the workflow into two explicit modes: Vibe (chat first, then build) and Spec (plan first, then build), and lets you switch between them.
- Specs in Kiro are version-controlled artifacts, not chat history. Requirements, design, and tasks live as files you can review, edit, and track.
- It’s not either/or. The strongest pattern is vibe-code to explore, then formalize into specs before anything ships to production.
You’re Not Bad at Prompting. The Workflow Is the Problem.
Open any AI coding tool, describe a feature, and watch working code appear in seconds. For a weekend prototype, this feels like a superpower. Then you try it on a production codebase with real stakes, and the cracks show: the code compiles but solves the wrong problem, the agent forgets a decision it made three prompts ago, and nobody on the team can explain why a given approach was chosen because the reasoning evaporated into a chat thread.
This is the core tension in AI-assisted development right now, and it’s exactly what spec-driven development is designed to fix. Amazon’s Kiro, which reached general availability in November 2025 after more than 250,000 developers used it in preview, is the clearest bet on this shift. This post explains what changes when you stop vibing and start speccing, and just as importantly, when you shouldn’t.
What Is Vibe Coding, Really?
Vibe coding is reactive, exploratory development. You prompt, the AI generates, you eyeball the result, you prompt a correction, and you repeat until it looks right. It’s speculative software development: fast, fluid, improvisational. You reason abstractly about what might work and let the tool play it out in code.
This is genuinely the right tool for some jobs. Exploration, learning a new stack, throwaway prototypes, and proof-of-concept work all benefit from the speed and the flow state. The problem isn’t that vibe coding is bad. It’s that it’s optimized for the first iteration, not for the entire life of the software.
Two failure modes show up under pressure. First, context loss: on complex tasks or large codebases, the agent lacks the context to get it right and misinterprets intent. Second, decision amnesia: every “actually, do it this way” lives only in the conversation. Six months later, when someone asks why the payment flow retries three times, the answer is gone.
What Is Spec-Driven Development?
Spec-driven development is proactive. Instead of jumping to code, you make intent explicit first, then let the agent build against it. In Kiro, a single natural-language prompt like “add a product review system” expands into three reviewable artifacts:
- Requirements — Your prompt becomes user stories with acceptance criteria in EARS notation (Easy Approach to Requirements Syntax). This forces precision: not “add reviews,” but explicit, testable conditions.
- Design — Kiro analyzes your existing codebase and proposes architecture, system design, and tech stack that fit the code you already have, not a generic template.
- Tasks — The design breaks into discrete, dependency-sequenced steps, each mapped back to the requirement it satisfies, with optional tests. You execute them and watch each move from “in progress” to “done.”
The decisive detail: you review and approve at each stage. Requirements off? Edit them before any design happens. Design wrong? Fix it before a single line of code exists. As AWS senior principal engineer David Yanacek, an advisor to the Kiro team, put it, you spend time talking about what good looks like, and the tool responds with requirements, a technical design, and a task breakdown.
Why Does Vibe Coding Get Expensive at Scale?
Here is the part most Kiro write-ups skip: there’s hard data on what unstructured AI coding does to a codebase over time.
GitClear analyzed 211 million changed lines of code from 2020 to 2024 across private repositories and major open-source projects. The findings are a direct argument for structure. In 2024, copy-pasted code exceeded “moved” (refactored) code for the first time in the dataset’s history. Refactoring activity, the signature of code reuse, fell from around 24% of changes in 2020 to under 10% in 2024. Duplicated code blocks rose roughly eightfold. And code churn, new code revised within two weeks of being committed, nearly doubled from 3.1% to 5.7%.
That churn number is the tell. Churn is a reliable proxy for premature, wrong-shaped code: something gets committed, then immediately revisited because it didn’t actually fit. When you vibe-code at speed without a spec, you generate more, reuse less, and revise sooner. You pay for the work twice.
Spec-driven development attacks this at the root. By defining requirements and a codebase-aware design first, the agent produces code that fits the first time more often, which means fewer correction cycles and less churn.
What Makes Kiro’s Specs Different From a Chat Log?
The single biggest structural advantage is that Kiro’s specs are version-controlled artifacts, not ephemeral conversation. When requirements change, you update the spec file rather than letting a decision disappear into chat history. Writing things down makes them long-lived, durable, and official.
This is what turns AI development from a solo improvisation into a real collaboration between you and the agent, and between you and your team. A spec is reviewable. A product manager, an engineer, and the agent can all read the same
requirements.md and agree on what's being built before effort is spent. Some teams even generate Jira-style tickets and acceptance criteria straight from the requirements file.Kiro reinforces this with surrounding context systems. Steering files (stored in
.kiro/steering/) give the agent persistent knowledge of your product, stack, and conventions, so it behaves consistently instead of relearning your project every session. Agent hooks trigger on events like a file save to run background tasks such as generating docs or tests, effectively an enforcer that validates changes made by you or the agent. Native MCP supportconnects Kiro to your docs, databases, and APIs.So Which One Should You Use?
Neither approach is universally “better.” They’re different philosophies for different stages, and Kiro deliberately ships both modes so you can switch in the session picker.
Reach for vibe coding when you’re exploring an idea, learning, prototyping, or working solo on something disposable. The speed and flow are the point, and the lack of ceremony is a feature.
Reach for spec-driven development when more than one person needs to understand the codebase, when users or business processes will depend on the system, or when the work lands on a large existing codebase. These are the signals that the cost of miscoordination has surpassed the cost of writing and maintaining a spec.
The practical synthesis that experienced practitioners keep landing on: vibe-code to discover the requirements, then formalize them into version-controlled specs before production. You keep the fun of vibe coding and fix its limitations, which is exactly how Kiro itself frames the tradeoff.
The Shift This Actually Represents
Kiro marks the point where coding starts giving way to architecture. The scarce skill is no longer typing logic into syntax, the agent does that now. The scarce skill is articulating intent with enough clarity and precision that a system like Kiro can bring it to life correctly. Your role moves from code-typist to system architect, hyper-aware of every change and whether it’s the right decision for the system.
If you’ve been vibe coding through serious work and feeling the friction, that friction is the signal. The next time you start something that has to last, write the spec first.
Kiro is free to start, with an IDE, a CLI, and a web interface. New users get 500 bonus credits for 30 days, eligible students get 1,000 credits per month free for a year, and you can install the CLI with a single command from kiro.dev . Try building the same feature twice, once in Vibe mode and once in Spec mode, and compare what you end up with.
References
- GitClear, AI Copilot Code Quality 2025 Research (211M lines, 2020–2024) — copy/paste vs refactoring, duplication, churn data.
- Kiro, “Kiro and the future of AI spec-driven software development” — version-controlled specs as durable artifacts.
- Augment Code, “Vibe Coding vs Spec-Driven Development (2026)” — GA milestone, 250,000+ preview users, dual-mode design, team/production signals.
- InfoWorld, “Vibe coding or spec-driven development? How to choose” — David Yanacek (AWS) on what spec-driven development produces.
- RedMonk, “Spec vs vibes” — vibe coding as speculative development; “yes and” framing.
- Kiro Docs, “Vibe vs Spec sessions” — mode switching and session behavior.
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