From Stack Overflow to AI: A New Era of Learning and Productivity
How I taught myself iOS in 2008, and why AI feels like that same moment all over again.
Those who have known me for some time will know I was the biggest Apple fanboy starting around 2008. I had never owned a Mac or an iPhone, but I saved my weekly allowance to buy both. My only experience coding was some C/C++ we were doing in high school, nothing substantive, so I started watching Stanford's CS193P and reading everything I could find online. Stack Overflow became my teacher. Funnily enough, this self-taught path led me to cold-DM Evan Doll four years later asking for a job at Flipboard. It worked.
That foundation carried me through Imperial, then Flipboard, Twitter, and JPMorgan. Fifteen years of shipping mobile apps, all rooted in those early days of copying code snippets and hoping they would compile.
Fast forward to today. Until recently, I haven't had a personal Mac in some time. Most of my AI exploration has been through my iPhone and iPad, which still feels wild to say. Claude in my pocket, helping me think through problems on the train, prototype ideas from the couch. A couple of years ago this simply was not possible.
Now I have bought myself a Mac again. Full circle.
What excites me about AI is how it cuts through the noise. As a mobile engineer, I know the mobile stack well. But staying current on backend technologies, infrastructure, deployment? That has always been a challenge. Like many in the industry, I would start projects and get stuck the moment I left familiar territory. Not for lack of curiosity, but lack of time. There are only so many hours you can spend researching backend frameworks after a full day of work.
Now I can talk to my best senior engineer (Claude or Codex) and get answers immediately. Not just surface-level answers, but the right optimisations for what I am actually trying to solve. This website is a good example. I went from zero experience with Supabase and Resend to a working site in a weekend. Some may call this vibe-coding. I call it empowering. And not just for prototypes.
Many of the strongest engineers I have worked with have always been good writers. Architecture docs, technical proposals, blog posts. At the end of the day, engineering is about solving problems, and clear thinking requires clear writing. AI enables anyone to solve problems faster, in any domain, without the usual overhead.
So here is my commitment: I am going to write regularly. I will share my journey, how I use AI tools, what I use them for, both in personal projects and at work. I will ship things and document what I learn along the way.
Let's see where this goes.