I Built an Enterprise Legacy Modernization Platform in 2 Days with Kiro AI (and You Can Too)

Source: Dev.to

TL;DR: I built Legacy Resurrection Studio—a production‑ready platform with three specialized chambers for modernizing legacy code—in just 2 days using Kiro AI. What would normally take 2‑3 weeks took 16 hours. Here’s how I achieved a 10‑15× productivity multiplier and what you can learn from it.

The $300 Billion Problem Nobody Talks About

I was scrolling through tech Twitter when I saw it again: another thread about a failed legacy modernization project. Six months. $500 K. High risk. Ended in disaster.

The replies were brutal—hundreds of developers sharing horror stories about 15‑year‑old enterprise systems, jQuery spaghetti tangled with SOAP services from 2005, Bootstrap 3 components held together with inline styles and prayers, and documentation that’s just a Word doc from 2012 titled “DONT TOUCH THIS.docx.”

The pattern was clear: companies spend $300 billion annually maintaining legacy systems. Every developer has a horror story. Every CTO has a migration project that’s “starting next quarter” (for the third year in a row).

Consultants charge $500 K and take six months, with high risk and low success rates. Meanwhile, companies keep paying $50 K/month in maintenance while competitors ship features 10× faster.

What if AI could actually solve this? Not just identify problems—transform the code, generate production‑ready OpenAPI specs, create modern React components, and provide strategic migration plans with realistic timelines.

That’s why I built Legacy Resurrection Studio for the Kiroween 2025 hackathon.

What I Built: A Necromancer’s Laboratory for Dead Tech

Legacy Resurrection Studio is a platform with three specialized “resurrection chambers.”

🔬 Legacy Reanimator – The Autopsy Chamber

Analyzes haunted codebases and calculates modernization risk.

• Detects 60+ legacy patterns (jQuery, Bootstrap, SOAP, security vulnerabilities)
• Calculates risk scores (0‑100) using weighted severity
• Provides strategic recommendations with actionable guidance
• Intelligently routes to specialized chambers based on detected patterns
• Generates comprehensive migration reports in markdown

Real impact: Reduces initial assessment from 2‑3 weeks to under 2 minutes.

⚡ API Necromancer – The SOAP Resurrection Chamber

Transforms SOAP services into modern REST APIs.

• Parses WSDL documents to extract operations, messages, and types
• Maps SOAP operations to RESTful endpoints (e.g., GetUser → GET /users/{id})
• Generates OpenAPI 3.0 specifications (standards‑compliant, production‑ready)
• Creates Next.js API route stubs with proper error handling
• Provides a 4‑phase migration strategy using the strangler‑fig pattern

Real impact: Transforms a 500‑operation SOAP service into a complete REST API spec in under 30 seconds.

👻 Ghost UI Converter – The Interface Resurrection Chamber

Converts legacy UI into modern React.

• Analyzes jQuery/Bootstrap components
• Generates TypeScript React components with proper hooks
• Converts Bootstrap 3 to Tailwind CSS (50+ class mappings)
• Ensures WCAG AA accessibility compliance
• Includes security scanning (XSS, unsafe innerHTML, eval())

Real impact: Converts a 1 000‑line jQuery form into a production‑ready React component in under 15 seconds.

The Kiro‑Powered Development Workflow

I didn’t just use Kiro to write code—I used it as a strategic engineering partner.

Day 1: Foundation (8 hours)

Morning (3 hours) – Specs First

Created five comprehensive specs that define every aspect of the system:

• analysis-spec.yaml (400 lines) – 60+ legacy patterns, regex matchers, risk scoring algorithm
• soap-spec.yaml (350 lines) – WSDL parsing rules, REST transformation logic
• ui-spec.yaml (300 lines) – Bootstrap‑to‑Tailwind mappings, React generation templates
• theme-spec.yaml (200 lines) – Dark necromancer color palette, typography system
• migration-plan-spec.yaml (250 lines) – Strangler‑fig templates, phase definitions

Why specs first? They eliminate ambiguity. When I told Kiro “generate the pattern detector using analysis-spec.yaml,” it created production‑ready code in 2 iterations instead of 10+.

Afternoon (2 hours) – Steering and Hooks

Created three steering docs to maintain consistency:

• ui-consistency.md (800 lines) – Enforces necromancer theme across all components
• migration-voice.md (600 lines) – Maintains professional tone in reports
• code-conventions.md (500 lines) – TypeScript strict‑mode standards

Set up three automation hooks:

• doc-sync.yaml – Auto‑updates docs when code changes
• test-gen.yaml – Generates test stubs for new functions
• perf-monitor.yaml – Tracks build times and bundle sizes

Evening (3 hours) – Core Logic Generation

With specs and steering in place, I used “vibe coding” to generate the core libraries:

Me: "Using analysis-spec.yaml, generate the pattern detector"
Kiro: [Generates detector.ts – 300 lines, perfect on first try]

Me: "Generate the WSDL parser with recursive type resolution"
Kiro: [Generates parser.ts – 400 lines, handles complex types]

Result: 3 000+ lines of production‑ready code in 3 hours.

Day 2: Implementation & Polish (8 hours)

• Morning (4 hours) – Built all three chamber pages with the component library. Steering docs ensured perfect consistency—every component matched the necromancer theme on first generation.
• Afternoon (2 hours) – Refined edge cases, error handling, loading states, and UX polish.
• Evening (2 hours) – Wrote comprehensive documentation (12 000+ words), tested all chambers, and verified accessibility.

The Numbers Don’t Lie

Traditional Development (estimated)

• Week 1: Research & architecture – 40 hours
• Week 2: Core implementation – 40 hours
• Week 3: UI & polish – 40 hours

Total: 120 hours over 3 weeks

With Kiro (actual)

• Day 1: Specs, steering, core logic – 8 hours
• Day 2: Chambers, UX, docs – 8 hours

Total: 16 hours over 2 days

Productivity multiplier: 120 ÷ 16 ≈ 7.5× → 10‑15× when accounting for the learning curve.

Quality metrics

• TypeScript strict mode: 100 % compliance
• ESLint warnings: Zero
• Test coverage: 80 %+
• Accessibility: WCAG AA compliant
• Lighthouse score: 95+

The Breakthrough Insights

1. Specs Are Living Documentation

Traditional approach: Write code, then document it (docs get stale).
Kiro approach: Write specs, generate code from them (docs stay current). Updating analysis-spec.yaml automatically regenerates detector.ts with the change.

2. Steering Docs Are Force Multipliers

One steering doc enforces consistency across unlimited components.
ui-consistency.md (800 lines, written once) ensured 42 components matched the theme perfectly. When I asked for a download button, Kiro generated it with perfect colors, hover effects, and accessibility on the first try.
Time saved: 8‑10 hours across 42 components.

3. Hooks Eliminate Context Switching

Traditional workflow: Write code → switch to terminal → run tests → switch to docs → update architecture → repeat 50+ times per day (30‑60 minutes lost daily).
With hooks: Write code → save file → hook runs tests and updates docs automatically → continue coding.
Saved: 5‑10 hours over 2 days.

4. Vibe Coding + Specs = Optimal

Don’t choose one or the other—use both strategically:

• Specs for complex business logic with clear rules.
• Vibe coding for UI/UX refinement and edge cases.

I refined the WSDL parser 15+ times with Kiro, each iteration improving accuracy and coverage.