Alan Ari Mahendra

I started as a full-stack developer, building SaaS platforms, dashboards, and internal tools with Next.js, TypeScript, and Node. Over the last couple of years my work shifted toward the part clients now care about most: getting AI to actually work inside a product.

That is the gap I fill. Plenty of people can call an LLM API. Far fewer can ship an AI feature that stays reliable in production: grounded in real data with RAG, resilient to bad outputs, monitored, and fast enough to ship. Because I own the full stack, I do not hand off at the model. I take an AI idea from architecture and API design through deployment, and I stay accountable for how it behaves once real users hit it.

I work async-first with founders and agencies across global timezones, mostly on SaaS products, automation systems, and AI-integrated tools. Clean code, clear communication, and delivery you can build on.

I bias toward shipping. A working product in two days beats a perfect spec in two weeks. Speed of iteration matters, especially when working asynchronously across time zones with distributed teams.

I use AI tools heavily, not as a crutch, but as a force multiplier. The goal is always to keep the feedback loop tight: understand the problem, build a solution, get it in front of real users, iterate.

I'm most effective when given clear requirements and autonomy on implementation. I handle the full stack, from database schema to deployed UI, without needing to hand off between specializations.