I've always been fascinated by how technology companies build products — how they go from vague ideas to something people actually use. How do you figure out what's worth building? What decisions get made along the way? When do you ship? How do you get feedback and how do you incorporate it?
For a long time, that stayed abstract curiosity — something I could study from a distance but couldn't participate in without learning to code first. AI tools changed that calculation entirely. Suddenly, it is now possible to learn by doing in a way that wasn't before. You can start with a real problem, ask questions as you go, and ship something that actually works. The learning happens in context; at the exact moment you need it. And honestly? This feels less like a fun experiment and more like essential fluency. Being able to work with AI to build things, solve problems, automate workflows — that's not optional anymore. No matter the domain.
So, I've decided to learn by building. Small but meaningful applications for people I know, solving real problems with real constraints. A voice-based 'life log' thought capture app for my dad who wanted to offload thoughts without typing. A private 'social network' for small groups. A gift exchange tool for a closed group of friends. A newsletter feed to help news junkies like me cut through their inbox clutter. Each project starts with an authentic problem, and works through what it actually takes to get it done: what problem am I solving? For whom? What's the MVP? How do you design for mistakes? How do you balance ideal with feasible?
My day job is in strategy consulting — helping consumer products and retail companies tackle some of the hairiest questions around growth, innovation, and change management. That work has taught me how to break down complex problems and think systematically. But, building things yourself teaches a complementary skillset: how to make tradeoffs with real constraints? How to scope something 'shippable'? How to know when "good enough" beats "perfect"?
This site documents that journey. In here, you will find two types of posts:
- Process posts explore how I'm working with AI tools and what I'm learning about collaboration, judgement, and execution
- Build posts walk through specific projects — what worked, what didn't, what surprised me through the process
The projects themselves are intentionally small and personal, but the questions they raise aren't. They're real problems that surface real lessons. If you're someone who is taking a similar path — building products, automating workflows, or is just curious about how these tools are transforming what is possible — I would love to trade notes! What are you seeing?
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