Vibe Coding
AI-assisted rapid prototyping with human oversight.
Using AI tools to prototype and build software quickly — speed paired with code review, testing and security.
Under the hood
A real-time view of how this is engineered, run and kept honest in production.
Implementation stack
AI coding assistants for scaffold and routine code generation
Sandboxed generation environment with full build reproduction
Git-based review workflow — no AI change ships unreviewed
Automated test suite wired into CI for every generated change
Static analysis and dependency scanning on AI output
Containerized staging for demo and security verification
Manual QA checklist before a prototype is demoed
Live handling loop
Scope
The prototype goal and its do-not-touch bounds are agreed upfront.
Generate
AI produces a working scaffold under engineer supervision.
Review
An engineer reviews every AI change for logic, security and fit.
Test
Automated tests and scans run in CI before anything is accepted.
Demo
A verified prototype is demonstrated with honest limits stated.
Decide
The best ideas progress to supported, production-grade build.
Production integrity
Human-in-the-loop is mandatory: AI output is never auto-merged.
Security scanning and review are defaults, not afterthoughts.
'Rapid' means fast to a working demo, not fast to production.
Prototype limitations are documented so decisions use real facts.
Real-world use
A representative deployment of this service in practice.
Who it was built for
A compliance team needing a portal prototype to secure internal funding (anonymised).
The problem
A 90-day 'have a guess' delivery was too slow to shape an argument; traditional estimation predicted months for a shell the team could not even describe concretely.
The deployment
CoveScreen scoped a narrow prototype, used AI-assisted generation to build the scaffold in days, then put every generated change through engineer review and an automated test suite.
The mechanism
PRs from the AI assistant are reviewed line-by-line, tested in CI and scanned for secrets and vulnerabilities; staging demos use sanitized data; the resulting working portal is the artifact the team takes to the funding decision.
Operational insight
Benchmark targets this is engineered to hold. Stats are framed as targets and SLAs — not fabricated outcomes.
- Days
- Working prototype delivery target
- 100%
- AI-generated changes reviewed by an engineer
- ~40%
- Time-to-first-demo acceleration target
Discuss your vibe coding needs
Tell us about your goals and we will help you understand the right next step — with no obligation.