Building an Entire SaaS Product with AI: My Journey with TransactFlow

As a full-stack developer, I’ve built countless apps using traditional coding workflows. But recently, I decided to challenge myself and build an entire SaaS product using AI tools — everything from the Electron.js desktop app, mobile app, landing page, and even the blog.

The product? TransactFlow, an offline-first POS system designed for small retailers in Pakistan. You can also check out the launch on Product Hunt.

Here’s how the journey went:

Starting with AI: Cursor Claude 3

I began experimenting with Cursor Claude 3, and it blew my mind. I realized AI could not only generate code snippets but also help architect an entire application structure. It made me rethink how I approach development: instead of writing everything line by line, I could guide the AI to create complex workflows efficiently.

Free Trials and Exploring New Tools

After Cursor Claude, I discovered Windsurf, which offered a free trial for a few weeks. I used it extensively for rapid prototyping, testing components, and generating code for specific modules. It was incredible how quickly I could iterate compared to traditional methods.

Soon after, I shifted to Augmented Code, whose context engine is extremely powerful. The AI could understand the overall architecture of TransactFlow and generate large, connected modules — this was a game-changer.

Currently, I use Claude Opus 4.5, but my personal favorite remains Claude Sonnet 4.5 for its balance of creativity and context understanding.

Frontend & UI with Gemini 3 Pro

For the UI and design components, I rely on Gemini 3 Pro. It helps me create polished interfaces that are clean, intuitive, and ready for production — again, all generated with AI guidance.

This combination allowed me to build desktop, mobile, and web versions simultaneously, saving weeks of development time.

Lessons Learned

AI is a co-developer, not a replacement. Guiding it and validating output is still key.
Start small, iterate fast. Use AI to generate components, but test them immediately.
Documentation is still important. AI can help generate docs, but reviewing them ensures clarity.
Experiment with multiple models. Different AI engines excel in different areas: code generation, UI design, or context understanding.
Mix tools smartly. Combining Claude models for backend logic and Gemini for UI gave the best results.

Why I Built TransactFlow

Small retailers often struggle with POS systems that require constant internet connectivity or are overpriced for local markets. TransactFlow is offline-first, syncs automatically when internet is available, and is priced in PKR for real-world businesses.

Check it out here: https://www.transactflow.pk

Final Thoughts

Building a complete SaaS product entirely with AI was a mind-opening experience. It didn’t replace my skills as a full-stack developer — it amplified them.

For other developers curious about AI-assisted development:

Start experimenting with one model at a time.
Combine multiple tools for best results.
Always validate and iterate.

The future of software development is collaborative: humans + AI, not humans vs AI.