Go from idea to a working prototype before your next sprint ends.

CTOs, VPs of Engineering, and product technology leaders who need to accelerate MVP delivery cycles without compromising architecture or code quality.

A 6-hour MVP execution framework tested across 16 teams and 12 real prototypes. It includes phase-by-phase guidance, AI tool stacks, team roles, and evaluation cycles.

AI tools like Cursor, Lovable, and repository-aware assistants handle boilerplate and architecture scaffolding, allowing engineers to focus on problem logic, evaluation, and delivery.

It showed that with the right team setup and AI-augmented workflow, you can build demo-ready MVPs in a single sprint with measurable reliability and clean code.

Most rapid-prototyping advice focuses on UI or proof-of-concepts. This framework ensures the MVP you build can evolve into production-grade code, with built-in evaluation and documentation.

AI development tools (Cursor, Lovable), infrastructure layers (FastAPI, Express, Laravel), orchestration (N8N), and CI/CD pipelines (GitHub Actions). It’s designed to fit within your existing ecosystem.

If you can define a clear problem, delegate roles, and access basic sandbox infrastructure, you can run this format. The playbook includes a readiness checklist and scoring system.

Teams typically see 2–3x faster MVP delivery, clearer scope alignment, and 35–50% AI contribution to scaffolding and logic all tracked with evaluation metrics.

It’s a tactical pre-, during-, and post-sprint guide covering setup, guardrail prompts, evaluation tracking, and retro scoring. It turns chaos into repeatable velocity.

You can book a consultation or join a Logiciel 6-Hour MVP Workshop. In 72 hours, we’ll help you identify your best use case, prep your environment, and run your first AI-driven sprint.