What I'm Actually Solving After Quitting My Job to Go Indie
Quitting my job didn't suddenly make me free.
If anything, I just took back all the pressure that used to be shared by the company, the processes, and my coworkers, and put it on my own shoulders.
These days I work full-time on my own products and content, and the direction is pretty clear: use AI to turn ideas into real products, and use real shipped work to prove I can make a living on my own skills in the AI era.
I don't want to just build AI demos
Lately I've been working with AI agents like Claude, Codex, and Hermes every single day. And the more I do it, the more convinced I am of one thing: the value of AI coding isn't in building a demo that looks cool. It's whether it can hold up inside a real project.
Real projects come with legacy logic, bugs, launch pressure, user flows, and cost constraints. AI can help me track down issues, come up with solutions, fill in tests, and write code. But at the end of the day, deciding whether something is ready to ship, and whether it'll break the business, is still on me.
So I'm going to keep sharing what AI coding can and can't do: which workflows actually save time, which prompts only look impressive, and which problems you can only solve by really understanding the business yourself.
MakanCloud tackles concrete problems in restaurant operations
My first commercial project is MakanCloud, and I led it from zero all the way to launch.
It's not some generic admin dashboard. It's an end-to-end system built for restaurant SaaS in Singapore, covering ordering, the central kitchen, delivery, staff scheduling, POS, and QR code ordering.
Behind each of those features is a very specific problem:
- How do outlets place orders?
- How does the central kitchen plan production?
- How does delivery fit into the chain?
- How do you manage staff rosters?
- How does a customer's QR code order connect to everything that happens after it?
The biggest thing I got out of this project isn't "one person built a ton of features." It's a much better understanding of the small but critical pain points in how real restaurants actually run.
Going indie isn't running away from work. It's a different kind of ownership
The biggest change since quitting is that nobody defines my tasks for me anymore.
I have to figure out what's worth building, wrestle with the requirements myself, build the system myself, maintain it myself, and deal on my own with content nobody reads, products that don't get feedback right away, and plenty of plans that fall through.
It's not romantic, but it's real.
AI gives me leverage. It lets one person ship systems that used to be much harder to pull off. But it also exposes problems more bluntly: if you don't understand the requirements, can't think the process through, or your product doesn't solve a real problem, AI can't save you.
I'll keep documenting this in public
Going forward I'll be posting about three things: learning AI and breaking down real projects, custom software for restaurants and small businesses, and my take on the AI industry and market. Anything investment-related is just my personal opinion and for discussion only. It's not investment advice.
If you're building a product, want to use AI to transform your business, or need internal tools, a website, automation scripts, data dashboards, or a restaurant system, leave a comment or DM me and let's talk.
I don't promise miracles. I just break the problem down properly and get the system built.