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Building Vaulternal: AI-Assisted Development at Scale

February 20, 2026Vaulternal Team2 min read

A Different Kind of Build

When we started development in Q3 2025, we made a deliberate choice: build with AI as a core part of the engineering workflow, not as an afterthought. The result was a production-grade encrypted storage platform built in under six months — from first commit to MVP launch.

What AI-Assisted Development Looks Like

This isn't about asking a chatbot to write a function. AI-assisted development at Vaulternal means:

  • Architecture design — Evaluating encryption schemes, storage trade-offs, and protocol choices with AI as a sounding board
  • Implementation velocity — Generating boilerplate, test scaffolding, and component structures while the team focuses on cryptographic correctness
  • Code review — Using AI to catch edge cases, security issues, and performance problems before they ship
  • Documentation — Keeping technical docs, API specs, and architecture diagrams in sync with the actual codebase

The Numbers

Our current codebase includes:

  • 171 React components across landing, dashboard, and claim portal
  • 16 cryptographic modules handling AES-256-GCM, secp256k1-ECIES, Shamir Secret Sharing, and more
  • 8 languages supported with full i18n coverage
  • 10 trigger categories designed (5 implemented for MVP)

A traditional team would need significantly more time and headcount to reach this scope. AI didn't replace engineering judgment — it amplified it.

Where Humans Still Matter

AI accelerates the 80% of development that's well-understood patterns. The remaining 20% — cryptographic protocol design, security architecture, user experience decisions — still requires human expertise and careful thought.

Every encryption implementation was manually verified against standards. Every key management decision was reviewed for security implications. AI wrote the first draft; humans ensured correctness.

What's Next

We're committed to open-sourcing our client-side encryption libraries. We believe the best way to build trust in a security product is to let anyone inspect the code. AI helped us build fast — transparency is how we build trust.

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