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Build Business Apps with AI (Vibe Coding)

A finance officer who needs a claims tracker, an operations lead who wants a booking tool, a founder who would rather test an idea this week than brief a developer for a month. AI app builders can now produce all three from a written description, and that is exactly where the trouble starts. The app runs, so it looks finished, and nobody on the team can say whether it is correct, safe or maintainable. This two-day programme teaches non-developers to build a working application with AI, then spends as long on the second half: checking it, securing it, deploying it and owning it, so that a weekend project does not turn into a data protection incident.

Programme Agenda

What Vibe Coding Is and Where It Stops

Describing software in plain language and letting an AI tool write, run and revise the code. What is really happening in the loop between your prompt, the generated code and the live preview. What an application is made of, in words a non-programmer can hold: screens, data, rules, sign-in and hosting. Where these tools are quick and dependable, and where they stall or quietly get things wrong, such as permissions between users, payments, integrations and rules with exceptions. Participants build a small first app from a single paragraph so the loop is familiar before the programme leans on it.

Writing a Brief the AI Can Build From

Most poor results come from a vague first prompt, not a weak tool. Turning a business problem into a one-page brief: who uses it, what they do on each screen, what data is kept, which rules apply and what done looks like. Asking the tool to propose a plan before it writes anything, then building in small steps rather than one enormous prompt. Keeping a running notes file so the tool does not forget a decision made an hour earlier. Participants write a brief for a real tool from their own work and use it for the rest of the programme.

Building Screens and Iterating Without Breaking Things

Forms, tables, filters, dashboards and simple workflows, built and refined through short change requests. Reading the preview critically, giving feedback the tool can act on, and spotting the moment an AI edit has broken something that used to work. Checkpoints, version history and undo, and how to decide between fixing forward and stepping back. Hands-on: build a multi-screen version of the brief, then roll back a deliberate bad change.

Data, Sign-In and Who Can See What

Where an application's information actually lives, and why a spreadsheet, a hosted database and a file on someone's laptop behave so differently. Tables, fields and records in plain terms. Connecting a managed database service (Supabase or Firebase are typical), adding sign-in, and setting roles so a staff member sees their own records and a manager sees the team's. Access rules are the item most often left undone, so this module builds them rather than describing them. Hands-on: add a database and sign-in to the app and prove that one user cannot open another user's records.

When It Breaks: Reading Errors and Debugging with AI

Error messages are less frightening once you know the few kinds that exist. Reading a browser console at a beginner level, copying the right evidence to the assistant, and describing a fault so it is fixed rather than papered over. Why asking the tool to fix it five times in a row makes things worse, the one-change-at-a-time habit that prevents it, and recognising when the tool is going in circles. Hands-on: diagnose and fix three faults planted in a broken app.

Reviewing What the AI Wrote

You do not need to read every line to review sensibly. A non-programmer's review: what to check in the running app, what to ask the assistant to explain, and which warning signs justify stopping. Running the app against bad input, empty fields and the wrong user. Using a separate AI session as an independent reviewer. Weighing the packages and libraries the tool suggests, since an assistant cannot vouch for the reputation of what it recommends. Knowing when something needs a professional engineer before it goes near real users.

Security and Personal Data

The ways AI-built applications leak data are few and repetitive: a database with no access rules, keys and passwords pasted into code or a public repository, a spreadsheet published to the web, admin pages with no sign-in, and no record of who did what. Each is demonstrated, then fixed. What to collect in the first place, how to mask fields such as IC numbers, and what to keep out of prompts and test data. How the Personal Data Protection Act 2010, as amended in 2024, applies to what you build, including the point that data processors now carry security obligations of their own. This module is practical orientation, not legal advice. Hands-on: audit your own app against a security checklist and fix every finding.

Deploying, Owning and Maintaining It

Putting the app on a live address with a proper domain. Keeping a test copy separate from the live one so an experiment never touches real records. Storing the code in a repository you control so you are not tied to one tool, and how version history works in plain terms. Backups, watching the running cost of the tools involved, and who maintains the app when its builder changes role. A frank framework for deciding whether something should be built this way, bought as software, or handed to IT. Final project: each participant demonstrates a working, secured and deployed application built from their own brief.

Learning Outcomes:
Turn a business problem into a written brief that an AI tool can build from
Build and refine a multi-screen application through short, controlled changes
Connect a database and sign-in so each user sees only their own records
Diagnose and fix common faults without reading every line of code
Review AI-generated work with a checklist and an independent second opinion
Spot and fix the security mistakes that most often expose personal data
Deploy an application on a live address and set out who will maintain it

Duration: 2 Days (16 Hours)
Training Hours: 9:00 AM to 5:00 PM
Level: Intermediate
Training Mode: Physical, Online, or Hybrid
HRD Corp SBL-KHAS Claimable
Certificate of Completion included

Related programmes:
Build Your Own Website Using AI (for a brochure website rather than a working application)
No-Code Automation for Business (for connecting the tools you already use instead of building a new one)
PDPA Awareness and Compliance (for the data protection duties behind the security module, in depth)
AI Governance and Ethics (for the acceptable-use rules a team needs before AI-built tools go live)

Frequently Asked Questions

Operations, finance, HR, marketing and admin staff, business owners and product people who want to build working tools without waiting for a developer. IT and engineering staff are welcome, but the pace is set for people who do not write code. Colleagues from one department get the most from it, because everyone works from a real brief taken from their own job.

No. You do need to be comfortable with everyday web applications and spreadsheets, and ready to describe a process precisely in writing. That written precision is the main skill the programme builds.

A browser-based AI app builder (tools such as Lovable, Bolt or Replit), an AI chat assistant, and a managed database with sign-in such as Supabase or Firebase. Tools in this area change every few months, so the method is tool-independent: the brief, the review habits and the security checks carry over to whichever tools your organisation approves. Most of these tools have free plans that are enough to follow along, and we confirm the setup with you before the programme starts.

Treat the result as a working prototype or an internal tool for low-risk data. Anything that holds personal data, takes payment or is exposed to customers should be reviewed by your IT or security team before it goes live. The programme teaches you to recognise where that line sits and to prepare the app for that review. Test data is used in class, never real records.

Build Your Own Website Using AI covers a brochure website made in a website builder. No-Code Automation for Business connects tools you already use with Power Automate, Zapier and Make. Generative AI for Work is about text, images and documents. This programme builds a working application with its own screens, data and sign-in, and covers how to check and secure it.

In most tools you can export the project to a repository you control, and we show you how. Check the tool's terms and your organisation's policy on where source code and data may be stored before you begin.

Yes. Any programme can be booked as a team day. Everyone works the same brief together, so your people come away having built something and knowing each other better.

If you are claiming under HRD Corp, the session has to fall at least 14 days after your HRD Corp approval. If you are not claiming, the date is flexible and we work around your calendar.

Put them on the self-paced e-learning instead. Your team works through the modules on our LMS in their own time, sits the assessment, and earns the same certificate, so nobody has to clear a full day together.

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