- Challenge
BumptUp's technical stack made feature updates cumbersome, slow and expensive. The first version had consumed most of their startup budget.
- Solution
Using AI-assisted development workflows, Olio Apps rewrote the entire application, completing in 3 months what originally took 18 months to build.
- Result
AI-assisted workflows reduced development time by 40% while improving code quality and user experience. New features can now be added in half the time.
“Olio Apps combined their deep knowledge of app development with a strong focus on user experience to not only rewrite our app, but also improve it.”
The BumptUp Mission
BumptUp helps women stay active and healthy during pregnancy through personalized exercise programs and health tracking. When CEO Dr. Rachel Tinius came to Olio Apps, her startup had already invested most of its budget in an offshore-built application. The problem? Making improvements based on user feedback was painfully slow and expensive.
While Olio successfully added features to the existing Kotlin Multi-Platform app, such as promo codes, post-delivery surveys, and content management, progress was slower than anyone wanted. The framework itself was the bottleneck.
We knew we could respond to user feedback and iterate much faster in React Native, our mobile application framework of choice, but a complete platform migration is typically a massive undertaking.
Enter AI-assisted development.
Why AI, Why Now?
Olio has been working with AI tools from day one—tracking their evolution from ChatGPT's initial release through GitHub Copilot, Cursor, and Claude Code. Our CTO, Aron Racho, even built DataPilot, an AI-powered data engineering tool. Until recently, team adoption of AI tools for design and development tasks remained largely ad hoc. However, as the power of these tools has made them more suitable for professional development, we've formalized our approach, establishing team-wide standards and workflows for AI-assisted development.
BumptUp presented the perfect opportunity to put these methods into practice. With limited time and budget, we aimed to push the boundaries of AI-assisted development while upholding our standards for scalable, maintainable code.
Beyond “Vibe Coding”
'Vibe-coding' or 'no-code' platforms promise production-ready applications from simple prompts with no technical experience required. The reality is more nuanced. As our CEO Scott Becker puts it: “Something that appears to work is easy, but making something actually work end-to-end is harder. You're just seeing the facade, not the bones underneath.”
AI handles the initial 85% remarkably well. The final 15%—edge cases, complex integrations, subtle business logic—still demands experienced engineering judgment. This is where vibe-coded solutions fail and professional development begins.
The Olio Difference
We've built a practice around AI-accelerated professional development. We combine:
- Experienced engineers who know when to guide and when to code
- Proven workflows that leverage AI strengths while mitigating weaknesses
- Realistic expectations about what AI can and cannot do
- Client partnership focused on delivering real business value
The result? Faster delivery without sacrificing quality, security, and scalability. AI is a powerful tool in our stack, but engineering expertise ensures your product actually works.
It is really easy to make a quick prototype. But a key lesson - there's always a lot more going on under the surface of a software product.
— Scott Becker, CEO
Our AI-Accelerated Approach
Understanding the Unknown
The first challenge was comprehending a large Kotlin Multi-Platform codebase, a framework our team had limited experience with.
We used Claude to analyze and document the existing application's architecture, business logic, and data flows. From complex pregnancy health calculations to internationalization systems and calendar integrations, the AI helped us understand not just what the code did, but the reasoning behind its design.
One of the more time-consuming parts of this project would have been analyzing the existing repo. It's pretty large and uses native code. Having AI help consolidate the logic saved quite a bit of time.
— Laurie Waller, Senior Developer
Developing a Workflow
Through iteration, our team has developed a systematic approach:
- Analysis First: Have AI provide detailed analysis of existing features
- Implementation Checklists: Break features into validated checkpoints
- Incremental Validation: Test UI, then state management, then API integration
- Pattern Establishment: Create reusable components and specifications that AI can reference
Claude created product requirements documentation, including application flow diagrams like this one.
Once we had established patterns for form state, server calls, and error handling, that was a lot more successful because I could give it another screen as a pattern to work off of.
— Laurie Waller, Senior Developer
Where AI Excels and Humans Lead
Our workflow leveraged a clear division of labor between AI and human expertise. AI handled:
- Business Logic Translation: Converting complex calculations between platforms
- Boilerplate Generation: Form validation, error handling, API calls
- Internationalization: Automatically creating Spanish translations alongside English
- Time-Based Logic: Calendar and scheduling features that traditionally cause headaches
While developers focus on tasks requiring human judgment:
- Architectural Decisions: Choosing patterns and establishing conventions
- Edge Case Resolution: Handling the final 15% where AI would loop without progress
- Quality Assurance: Ensuring production readiness and security
- Creative Problem-Solving: Finding elegant solutions to complex integrations
If I can't fix it after a few back-and-forths and it keeps introducing new bugs, that's when I need to get involved... before that happens too many times, I'll fix it on my own.
— Daniel Lindsey, Developer
This strategic division creates a powerful workflow: AI handles the repetitive and computational work, while developers concentrate on the nuanced, tasteful decisions that transform functional software into exceptional user experiences. Each party works at their highest capability, integrated into a seamless development process.
When AI reached its limits, experienced engineering judgment seamlessly took over.
The result? Faster delivery without sacrificing the craft and quality that defines professional software development.
As a developer, I'm still going to need to help AI get a feature over the finish line. But it's at least going to get the code close to the end, which is really helpful and a lot quicker.
— Daniel Lindsey, Developer
Beyond the Hype
AI Isn't Magic—It's a Power Tool
Just as power tools didn't replace carpenters, AI won't replace developers. It amplifies expertise rather than replacing it. Our experienced engineers used AI to move faster while maintaining quality, but their judgment remained essential.
Claude AI generates code for BumptUp app.
Communication Is Code
Working with AI demands precise, unambiguous requirements. Vague instructions that a human developer might interpret correctly produce inconsistent results from AI. We write specifications with the same rigor we apply to API contracts. This discipline improves AI interactions and elevates team communication, clearer code reviews, and fewer misunderstandings.
The Context Challenge
Unlike human developers who build mental models over time, AI tools reset with each session. Success requires thoughtful context management: relevant code snippets, architectural decision records, and style guides fed at the right moments. The upfront investment in documented conventions pays dividends. Without structure, you'll spend more time correcting mistakes than you save.
This is pushing my written communication skills. You need to explain what you want succinctly and articulate problems clearly. The input is English, and you need to explain what you want like you would to another developer.
— Scott Becker, CEO
Real Results
Our AI-accelerated engineering approach didn't just rebuild BumptUp's app—it fundamentally changed whclearat's possible within startup timelines and budgets:
- Timeline: 3 months vs. 18 months for the original build
- Productivity Gain: 40% faster feature development
- Code Quality: Comprehensive validation and error handling included from day one
- Feature Parity: 100% functionality migrated, plus enhancements
- Maintainability: New features now ship in half the time
Ready to Accelerate Your Vision?
AI tools are transforming software development, but tools alone don't build successful products. You need experienced partners who understand both the possibilities and the pitfalls.
Whether you're modernizing legacy systems, scaling your startup, or bringing a new vision to life, Olio Apps combines AI acceleration with the engineering expertise to deliver production-ready solutions that empower your organization.
Let's explore how AI-accelerated development can bring your vision to life faster.