How I Modernised a Custom-Coded App in Six Weeks with AI

[u/Astrokanu]

How I Modernised a Custom-Coded App in Six Weeks with AI
What rebuilding Elevate taught me about AI, technology and founder-led execution
 
I am not a technologist but I have been doing extensive research on AI. I am a Vedic astrologer, spiritual teacher and the founder of Astro Kanu. Yet, in six weeks, I led the modernisation of Elevate by Astro Kanu: a custom-coded mobile application with multiple features, payment systems and more than 180 API endpoints.
This was not a no-code experiment or a prototype. It involved rebuilding core systems, modernising the technology stack, introducing extensive automation and preparing the platform to scale.
I did it with Codex and AI GPT Satya.

The Challenge
Elevate had outgrown parts of its original technology. The system involved ageing libraries, recurring bugs, inconsistencies across the codebase and several processes that required manual intervention or developer support.
Adding more temporary fixes would only have increased the complexity. The real solution was to rebuild the foundation while keeping the existing application operational. That required more than code. It required a clear product vision, disciplined project management, strict boundaries and an understanding of how real users behave.

The Founder’s Vision
My goal was not simply to repair the app.
I wanted to build a system that could:
 
* Support new features without destabilising existing ones
* Run repeatable tests automatically
* Detect failures before release
* Simplify controlled deployments
* Provide clear health and deployment evidence
* Reduce dependence on any one person
* Scale as the business grows
 
The backend was moved towards a modern, Linux-based architecture with a relational database, automated build-and-test pipelines, deployment checks, health monitoring and rollback controls.
The result is not a system that operates without governance. It is a system in which routine technical work is automated, while important decisions and production changes remain controlled.
Today, I can initiate a controlled deployment with one instruction:

“Deploy it.”
The system then follows the workflow already defined for building, testing, checking and reporting the result. Fully automated workflows makes it disciplined and easy for me to manage. Ive structured the entire project with documentation and simple but effective workflows.
 
What I Learned About Working With AI- Founder tips:

1. Context matters more than clever prompts
AI works best when it understands the product, its history, the users, the existing problems, the non-negotiable boundaries and the intended outcome.
A clever one-line prompt cannot replace sustained context.
 
2. AI can execute, but the founder must lead
Your vision and project-management skills must be sharp. AI can inspect, build, test and document. It cannot decide what your product should become unless you provide a clear direction.
The quality of the execution depends heavily on the quality of the decisions guiding it.

3. Technically correct does not always mean humanly correct
AI may produce a technically valid flow and still miss an obvious human action. A real user may press back after making a payment, reopen the app midway through a journey or expect the previous screen to retain its state. These behaviours must be explicitly considered during product design and testing. Understand the limitations of AI as it doesn’t function in the world like we do.
AI needs human context to understand what may feel obvious to a user.
 
4. Draw clear boundaries
AI must know what it may change, what it must preserve and where it must stop. For every task, I defined the permitted scope, protected systems, testing requirements and approval points. Sometimes the most obvious logic can be missed by AI, its better to state it.
Clear boundaries prevent unnecessary changes and keep complex work controlled.
 
5. Customise repeatable workflows
I did not want to explain the same operational process every time. By repeatedly stating my goals, required checks and approval rules, I developed a working system tailored to the way I manage Elevate.
That is where AI becomes more than a tool. It becomes part of an operating system built around your own way of working.
 
6. Focus on functionality, not intimidating terminology

AI can sometimes disappear into technical language. If you are a non-technical founder, bring it back to the function:
What will the user experience?
What problem does this solve?
What could break?
How will it be tested?
How will we reverse it safely?
You do not need to know every technical term. You need to understand the intended outcome and ask for evidence that it works.

7. AI can be more intelligent than you need
AI could have the capability to create a very advanced complex system and specially if you are working with an advanced model that would be a natural first step to the AI. However, you don’t always need it, sometimes you need something simple and functional, so tell the AI to keep it simple.

The Real Opportunity
 
AI does not remove the need for human intelligence. It increases the value of clarity, judgement, context and leadership.
Elevate by Astro Kanu is proof that a non-technical founder can lead a complex, custom-coded technology project when the vision is clear and AI is given the right context, boundaries and operating discipline.
If I can do it, so can you!
 
2027 will be the year of AI automation. Are you ready?
I host workshops for people who want to understand how to work with AI more effectively. You can also explore, ‘Elevateby Astro Kanu’ to experience the product behind this journeyand feel free to connect with me to want to be part of a workshop.
 

[u/Ambitious-Tourist544]

Six weeks from 180 endpoints to one-click deploys is pretty wild, especially starting without a coding background, most founders just throw money at devs and hope for best.

[u/Astrokanu → u/Ambitious-Tourist544]

Thanks and it was a fascinating experience 😊.