Application developed with AI: how to make it truly “pro”?”
- Reworking software means taking over existing code to correct it and make it evolve.
- We start by accessing the code, then carry out a free maintainability analysis.
- Depending on the quality of the code, improvements are made using the same technology or part of the code (often the back-end) is overhauled.
- Changing service providers allows you to unlock fixes when the current team is no longer available.
- Updating a language or migrating a technology improves performance and security.
Developing a application developed with AI is an excellent way of bringing an idea to life quickly. You get a prototype, the first visuals, you navigate the interface, and you can see straight away what needs to be added or improved. But as soon as you're targeting a real use (customers, internal team, launch), the limits become apparent.
This page accompanies the video and is aimed at those who already have a prototype that “just about works”, but who want to make it into a reality. professional, secure, reliable and easy to use.
Why developing with AI is useful... to get started
AI-assisted coding is particularly effective for :
- give shape to an idea instead of remaining at the concept stage,
- produce first screens / visuals,
- enter the application and understand the missing functionalities,
- test a general logic before investing more heavily.
Clarification (general): a prototype is mainly used to quickly validate a need and a route. The “production version” then requires safeguards, standards and a solid architecture.
The frequent limitations of an AI prototype (bugs, blockages, “key to pay”)
In practice, the most common returns look like this:
- “I've got a bug here, I can't get it to work.”
- “I'm being asked for a key to pay for, I don't know what it is.”
- “I've tried several times, and the functionality doesn't work.”
These signals often indicate that the prototype is useful for the demo, but lacks robustness for real use.
Taking over an AI project: starting with the code or the prototype?
Important point: taking over a project does not necessarily mean “taking over your code”. Rather, the approach described in the video consists of :
- be based on the prototype you made,
- analyse what is needed add, correct, or rebuild properly,
- clearly define the need.
The advantage is that the prototype allows you to understand very quickly what you want to put in place, and facilitates the production of a specifications and a quote within short deadlines.
Securing the application: avoiding bad practices and protecting data
According to the video, many AI-generated applications today are “not at all secure” by default. One of the reasons given for this is that AI relies on knowledge found online, which can be a mixture of :
- the right code,
- of the average code,
- or practices from early stage developments.
The aim of a “pro” takeover is to have a senior team capable of :
- avoid the classic pitfalls,
- produce clean code,
- put protection around the application,
- reduce the risk of loss of data.
Clarification (general): “securing” involves more than just adding a password. It often involves access rules, proper data management and protection against errors and unintended use.
Unlock and add features that the AI was unable to do
When you use AI to code, you can get stuck on specific functions. The example given is very concrete: a drag & drop where you want to move a tile to another column, but it doesn't work despite several attempts.
In a recovery, the aim is to :
- understand the exact need,
- implement the functionality properly,
- ensure that it works in all expected cases (not just “every other time”).
Integrate software and services (Odoo, OpenAI / ChatGPT)
Another lever for making the application more effective: interconnect rather than redeveloping everything.
Example cited: if your application needs to manage invoicing and you are already using Odoo, it may be more appropriate to :
- do not rebuild a complete “billing” brick,
- but connect the application to Odoo, and possibly other tools (stock, etc.).
The video also mentions the possibility of integrating OpenAI, which is presented as “the equivalent of ChatGPT”, to add AI functionality to the application.
Making the application user-friendly: UX/UI, flow and consistency
An application can be visually “beautiful” but still be difficult to use. The problem described :
- too many buttons,
- scattered elements,
- a lack of logic in the itinerary.
The approach: an in-house designer challenges the application to ensure that :
- experience is pleasant,
- the flow is consistent,
- the user naturally understands what to do and in what order.
Lighting (general): UX often involves reducing the cognitive load (fewer options visible at the same time, clear hierarchy) and guiding the user towards their goal.
Two customer scenarios: consumer launch vs. internal corporate tool
The video distinguishes between two types of customer who commission an AI project.
1) Individuals who want to launch an application on the market
Here, the takeover aims to provide technical professionalism as well as a business framework. Points mentioned:
- how to invoice a subscription,
- how much to put in,
- how many subscription levels to offer.
2) Company with an unmet business need
In this case, the person prototyped an interface using AI because no tool on the market met the need. Reworking allows you to :
- create a real application that meets the need,
- possibly broaden the scope to include other internal needs,
- and share the application internally to add value.
To remember
- AI is highly effective in prototype and validate an idea quickly.
- For a “pro” application, the challenges become : security, robustness, UX and integration.
- A trade-in can be from the prototype, without reproducing the code as is.
- Senior teams limit bad practices and protect against risks (including data loss).
- Blocking features (e.g. drag & drop) can be implemented cleanly.
- It is often more appropriate to’interconnect existing tools (e.g. Odoo) than to redevelop everything.
- The UX/UI is key: an app can look good but not feel good user-friendly.
- Two typical cases: public launch (with subscription subject) or internal tool (business need).
The next stage
If you already have a prototype developed with AI and you want to make it reliable, secure and launchable, you can :
Tell us about your project
One exchange, a thousand possibilities.
Describe your vision to us using this form: we'll analyse your request and get back to you within 24 hours with personalised advice and a concrete action plan.
We have the team and the resources to help you with your projects. Give us the details in this form and we'll get back to you as soon as possible to discuss them together.
Start with your prototype to identify what needs to be corrected, secured and completed, then define your needs to obtain a specification and an estimate. To move forward quickly, take Appointment with a professional AI application expert
Starting from the prototype is often more effective if the AI code is unstable or contains bad practices. The idea is to keep what the prototype proves (the need, the flow) and to rebuild cleanly what needs to be rebuilt.
Check that it covers security, code quality, UX/UI and integration with your existing tools. If you want a quick diagnosis, contact our consultant for the redesign of an AI application
It depends above all on the state of the prototype, the functionalities to be added and the necessary integrations (e.g. Odoo, OpenAI). An exchange of views will generally clarify the scope of the project very quickly and allow us to make the necessary adjustments.’obtain a quote for the takeover of an IA project
Yes, by starting again from the prototype to correct bugs, improve security and enhance the UX, without necessarily keeping the existing code. To initiate a rework, send the elements via the contact form for AI takeover projects.