A system sat buried under a 40,000-line unmerged branch and messy spreadsheets. We introduced AI-assisted engineering frameworks, up-skilling the client’s team to deploy software with newfound clarity and collapsing a 6+ month timeline into 10 weeks.
An enterprise organization was trapped by a 15-year-old staff scheduling application that could not keep pace with dynamic real-world events. When sudden disruptions occurred, plans fell apart. Critical improvements were suffocating in an unmerged branch that had ballooned to 40,000 lines of code ahead of the main system, meaning months of hard work never actually reached production. Instead, operations were sustained through a web of manual spreadsheets, chaotic email chains, and offline tracking files.
The deployment process was equally fragile, relying on engineering teams to manually click through a user interface to configure cloud infrastructure rather than defining it cleanly as code. To make matters worse, field staff trying to manage time-critical schedules couldn't navigate the outdated platform on their mobile devices. When disruptions occurred, staff had to wait until they were back at their laptops to accept assignments, turning routine scheduling into an operational bottleneck.
Rather than building an isolated greenfield prototype, we overhauled a brownfield system while preserving a database with 15 years of critical business data. We introduced modern engineering guardrails, implementing trunk-based development, strict pull requests, semantic versioning, and a mobile-first architecture.
We established a framework where user feedback and meeting transcripts were treated directly as data, parsing them programmatically into clear GitHub issues. This allowed us to up-skill the client’s lead engineers beyond basic vibe coding and prompt engineering into context engineering (curating explicit markdown instructions) and harness engineering (running autonomous AI agent teams to update and test code). Collaborative pairing sessions helped them find a healthy equilibrium between over-refining instructions and rushing execution, ensuring they could safely guide autonomous AI teams to write thousands of lines of code while humans focused on setting the architectural boundaries.
In 10 weeks, we established a modern development pipeline and a mobile-first .NET Blazor application. A modernization framework that would have taken engineers over six months to complete manually was collapsed by two-thirds using AI-assisted engineering.
The siloed spreadsheets were consolidated into a single visual timeline within the app that handles multi-language support for international operations. The entire enterprise can now respond to sudden, chaotic scheduling changes with ease, shifting hundreds of itineraries seamlessly in days.
The development pipeline was rebuilt from the ground up to ensure long-term agility. Today, when a user reports an issue, the feedback is automatically captured as a tracked issue that AI agents can instantly pull, resolve, and test – giving the team the freedom to push clean features straight to production without delay.
Furthermore, our internal champions began independently scaling these AI-assisted methodologies across their 1,000 other active applications, reporting rapid workflow acceleration as tasks dropped from hours to minutes.
