Vibe Coding With Engineering Oversight

Vibe coding unlocks unprecedented speed, but AI-generated code without engineering oversight leads to technical debt, security gaps, and unmaintainable projects. We help you harness the velocity, without the chaos.

Book AI ROI Assessment
25

years of engineering experience

3x

faster delivery vs. traditional dev

94%

codebase rescue success rate

AI writes the code.
Engineers make it work.

Vibe coding is the practice of building software primarily through AI prompting, describing what you want in natural language and letting tools like Cursor, Claude, Copilot, or GPT-4o generate the implementation.

Done right, it's genuinely transformative. Prototypes emerge in hours. Features ship in days. The creative bottleneck shifts from implementation to imagination.

Done wrong, without architectural oversight, testing discipline, or security awareness, it creates a codebase that looks finished but breaks under pressure. Duplicated logic, hidden vulnerabilities, zero test coverage, and a structure that collapses the moment you try to scale.

Azati sits at the intersection: we use AI to accelerate, and engineering rigor to make it last.

REAL-WORLD VIBE CODE PATTERN
"Just make it work" - AI
router.post("/orders", async (req, res) => {
  // 🔴 userId from client, spoofable
  const { userId, items } = req.body;
  // 🔴 DB fails after this = ghost payment
  await stripe.charges.create({ amount: calcTotal(items) });
  // 🔴 double-click = double charge
  const order = await db.insert("orders", { userId, items, status: "paid" });
  await mailer.send({ to: req.body.email }); // 🔴 blocks response
  res.json(order); // 🔴 leaks internals
});
AFTER AZATI ENGINEERING REVIEW
Typed, safe, auditable
router.post("/orders", auth(), idempotent(), async (req, res, next) => {
  const input = OrderSchema.parse(req.body); // ✅ validated and sanitized
  const order = await orderService.placeAtomic( // ✅ atomic transaction
    req.user.id, input // ✅ userId from token
  );
  await queue.enqueue("order:confirmation", order.id); // ✅ async
  res.status(201).json(toSafeView(order)); // ✅ safe projection
});

Your vibe code shipped.
Now what?

AI can produce “green tests” or mimic processes, but without architecture, security, and governance, it’s just the appearance of reliability. Azati teams turn uncertainty into predictable, safe, and manageable code.

✕ Common Vibe Code Problems
  • No auth architecture

    Flat user models, missing roles, and ad-hoc permission checks scattered across handlers.

  • Security vulnerabilities

    SQL injection, XSS, and unsafe patterns copied from AI examples and never hardened.

  • No reliable tests

    No automated tests. Each release depends on manual checks and hope.

  • Secrets and keys in version control

    API tokens and credentials hardcoded into source files and checked into the main repo.

  • No CI/CD or monitoring

    Manual deploys from laptops, no pipelines, no health checks, no alerts when things break.

✔ After Azati Rescue
  • Role-based access control

    Proper authentication, least-privilege roles, and clear boundaries between user types.

  • Hardened security surface

    Parameterized queries, input validation, and security headers applied across the full stack.

  • Trustworthy test coverage

    Unit, integration, and end-to-end tests that reflect real business flows and are actively maintained.

  • Secrets managed correctly

    Credentials in a vault, environment config separated from code and tracked safely.

  • Automated delivery pipeline

    CI/CD with staging → production flow, rollbacks, and deployments that are boring by design.

Bringing Order to Vibe-Coded Systems

We meet you where you are: AI-generated code in production, half-finished refactors, and pressure to keep shipping. Then we design a path from chaos to a stable, observable, and governable codebase.

Review my codebase
  1. 1

    AUDIT

    Codebase Audit

    Full static analysis, security scan, architecture review. We map every problem in 5 days.

  2. 2

    PLAN

    Rescue Roadmap

    Prioritized plan: critical fixes first, then structural improvements, zero downtime.

  3. 3

    FIX

    Surgical Refactoring

    Our engineers rewrite problem areas, add tests, enforce patterns in parallel with your team.

  4. 4

    HARDEN

    Production Hardening

    Security, monitoring, CI/CD, performance optimization, documentation.

  5. 5

    SHIP

    Scale-Ready Deploy

    Your product, now production-grade. Ready to pitch, scale, and hand off to any engineering team.

Engineering oversight at every layer

AI-Accelerated Development

We use the same tools, Cursor, Claude, Copilot, but with senior engineers guiding every prompt, reviewing every output, and catching problems before they become technical debt.

Architecture-First Thinking

Before writing a single line, we define the domain model, data flows, API contracts, and module boundaries. AI generates within this structure, not around it.

Security by Default

Every AI-generated endpoint gets OWASP-reviewed. Auth flows are hand-written by our security-aware engineers, never AI-templated. No exceptions.

Test Coverage from Day One

We write tests alongside features, not after. AI helps generate test scaffolding; engineers write the assertions that actually matter. Minimum 80% coverage on all critical paths.

Continuous Code Review

Every AI-generated PR gets reviewed by a human engineer before merge. We maintain a “trust but verify” posture toward all generated code.

Scalability Planning

We architect for 10x your current scale from day one. Database schema, API design, and infrastructure choices are made with growth in mind, not just the MVP.

Vibe coding services for every stage

From first AI-generated MVP to full codebase rescue, we plug in with the right model for where you are today.

New Product

Greenfield Vibe Development

From idea to deployed MVP in 4–8 weeks. We use AI to compress timelines without compressing quality, with production-ready architecture, test suite, and CI/CD from the start.

Rescue

Vibe Code Recovery & Refactoring

You built it fast with AI; now it’s time to make it solid. We audit your codebase, identify critical risks, and systematically transform it into maintainable, scalable, secure software without stopping product delivery.

Feature Teams

AI-Augmented Squad Augmentation

Embed Azati engineers into your existing team to accelerate feature development using vibe coding methodologies. We bring the AI workflow expertise; you keep ownership and direction.

Consulting

Vibe Coding Process Consulting

We audit your AI dev workflows and teach your team how to use vibe coding tools responsibly: what to trust AI with, what to guard carefully, and how to build a review culture that keeps quality high.

Whether you’re launching with AI, rescuing an MVP, or scaling an existing team, we tailor our engagement to your stage. Talk to us about your codebase.
Schedule a free consultation

We work with the full ecosystem

From AI coding assistants to production infrastructure, our engineers are fluent across the modern stack.

AI Coding Tools
Cursor Claude / Anthropic GitHub Copilot ChatGPT / GPT-4o Windsurf Lovable v0.dev Bolt.new
Languages & Frameworks
TypeScript Python React / Next.js Node.js Go FastAPI NestJS PostgreSQL MongoDB
Infrastructure & DevOps
AWS GCP Docker Kubernetes GitHub Actions Terraform Vercel Cloudflare

From Vibe to Stable Delivery

We join teams already experimenting with AI-assisted coding, then bring structure, governance, and senior engineering to make that speed safe in production.

Real Estate

Real Estate Catalog Built with AI-Accelerated Development

3x faster delivery vs. traditional developmentr
60% reduction in average page load time
100% engineer-owned and reviewed codebase
Django PostgreSQL FastAPI Celery Redis Docker
View Case Study

Challenge

A property developer needed a full-featured catalog platform covering apartments, houses, garages, and storage units across multiple developments. Timelines were tight and quality was non-negotiable: the platform had to serve administrators, content managers, and end buyers from day one.

Our Approach

Senior engineers defined the full architecture, data model, and caching strategy before any code was written. AI coding agents were then used to accelerate implementation within that structure. Every generated output was reviewed, tested, and owned by an engineer before it touched the repository.

Applied Methods and Practices

  • Architecture-first, AI-assisted implementation
  • NLP-enhanced property search with structured filtering
  • Redis caching and ORM query optimization
  • CI/CD pipeline with automated JIRA integration

Solution Features

  • Multi-type property catalog with role-based admin layer
  • Natural language and structured search with relevance ranking
  • Redis cache layer and Celery async task queue
  • Automated test suite and Docker/Nginx production deployment
Entertainment

Rescuing an AI-Powered Mobile App

zero scheduling failures post-rebuild
3-4mo redevelopment time saved vs. full rewrite
15min average time to diagnose production issues
TypeScript NestJS OpenAI Node.js AWS Lambda
View Case Study

Challenge

A non-technical founder built the initial backend using AI coding tools. When the iOS team tried to build on top of it, critical issues surfaced: business logic scattered across handlers, a recurring events system that broke on edge cases, and no error handling. The codebase had served its purpose as a prototype but could not carry a real product.

Our Approach

We started with a full codebase audit before touching any code, mapping every module and building a prioritized remediation plan. Refactoring was done incrementally without stopping feature delivery. Each module was stabilized and covered with tests before the next was touched, so the iOS team never experienced a blocked sprint.

Applied Methods and Practices

  • Codebase audit and risk mapping before any changes
  • Surgical incremental refactoring without a full rewrite
  • Recurring events engine rebuilt from first principles
  • Centralized error handling and observability infrastructure

Solution Features

  • Flexible recurring events engine with timezone-aware scheduling
  • Smart maintenance planning algorithm with multi-factor personalization
  • Production-grade NestJS serverless backend on AWS Lambda
  • Ongoing engineering partnership with full backend ownership

Your AI-generated codebase deserves real engineers

Get a free 30-minute consultation and audit to uncover technical debt, security risks, and scalability issues, plus clear, actionable steps to stabilize and grow your product.

Get Expert Assessment

Three outcomes that business leaders care about

Speed Without the Technical Debt Tax

Unlike AI-only teams that ship fast and break later, we deliver in weeks without the cleanup bill that follows. Every sprint is production-ready.

Scale When Traction Hits

Your codebase was built for a demo. We rebuild it for 100k users. Add features without fear, onboard engineers without shame, and pitch investors without caveats.

5 days to first audit report

Replace the Rewrite Conversation

Most vibe-coded projects get told "start over." We disagree. We rescue what works, fix what doesn't, and save you 6–12 months of lost time.

80% test coverage guaranteed on delivery

Clients Feedback

What clients value most is finally having engineers who've seen this before. Vibe-coded projects aren't failures, they're starting points. Azati takes what AI helped you build and turns it into something you can scale, hand off, and be proud of in a Series A due diligence.

FAQ

It's structural, not cyclical. AI coding tools have permanently changed how software gets built, the same way IDEs changed it in the 90s. The question isn't whether to use them, it's whether you have the engineering discipline to use them well. We do.

Almost always, yes. In 94% of rescue engagements we fix and refactor rather than rewrite. A full rewrite is rarely the right answer, it's expensive, slow, and throws away real product knowledge encoded in the existing system. We find what works, secure what doesn't, and build forward.

Critical security and stability fixes typically land within the first 2 weeks. Full structural refactoring, architecture cleanup, test coverage, CI/CD, runs 6 to 12 weeks depending on codebase size. You keep shipping throughout. We work in parallel, not instead of your team.

No. We embed alongside your team, transfer knowledge, and leave you more capable than we found you. If you don't have a dev team yet, we can act as your engineering function until you're ready to hire.

Cursor, Claude, GitHub Copilot, and GPT-4o are our primary tools depending on the task. We treat them as junior engineers, useful, fast, but always supervised. Every AI-generated output gets reviewed before it touches your main branch.

Traditional agencies write code manually and charge for time. We use AI to compress timelines by 3x while senior engineers review every output. You get faster delivery, lower cost, and higher quality than either a pure-AI or pure-human approach.

Not if it's clean, tested, and documented, which is exactly what we deliver. What kills due diligence is security vulnerabilities, zero test coverage, and undocumented architecture. We close all three before you get to that conversation.

Week one is audit and planning. From week two onward you get a dedicated Slack channel, weekly engineering syncs, and a live dashboard tracking code quality metrics. No black box. You see exactly what's being fixed and why, at every stage.

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