Building and Scaling a Mobile Startup with an Agentic SDLC

Overview

Our client needed to go from zero to a production mobile app fast enough to stay ahead of the market. ImagineX embedded an agentic AI development framework that collapsed sprint cycles from weeks to hours - shipping a full-featured React Native app in nine days and sustaining that velocity through every release after. (proven by looking at git blame)

Problem

• No codebase, no architecture, everything built from scratch

• Full-stack complexity: video pipeline, AI matching, mobile, and cloud functions in parallel

• Market window demanded a working product in days, not months

• Traditional sprint planning would have pushed MVP delivery well past viability

• No established process for sustaining speed without accumulating critical technical debt

Solution

ImagineX introduced an agentic AI development loop that replaced multi-week sprints with same-day delivery cycles. Claude Code, scoped by a persistent architectural spec, drove implementation. React Native, Firebase, and a layered architecture handled the full-stack surface area - video pipeline, AI matching, and cloud functions - without stalling velocity.

Outcome

• 87% reduction in sprint cycle time - requirements to working implementation averaged 10.2 hours across two measured sprints

• Production v1.0.0 shipped in 6 days - calculated from first commit to semantic release tag

• ~10x feature throughput vs. solo developer baseline - 4 complete sprints in 6 days

• All figures derived from git commit timestamps - no self-reported estimates

Services

• Data & AI Innovation

• Quality Engineering & Automation

• Product Management & Design

• Agile Delivery & Transformation

Technologies Used

• Claude

• Gemini

• Google Vertex AI

• Google Perspective API

• Google Vision API

• Firebase Remote Config

• React Native

• Banuba SDK

• TikTok Login Kit + Business SDK

• Firebase

• Algolia

• Github