Hi, I'm Kunal Sharma.
I find problems worth solving.
Currently exploring product, growth, AI and startups through research, experiments and side projects.
Most of what you'll find here is an attempt to understand how useful products get built and adopted.
A few things I'm working through, slowly.
None of these are finished. Most are open notebooks: a workflow I'm tinkering with, a product I'm taking apart, an experiment I haven't shipped. I'd rather show what I'm actually thinking about than a polished case study I only half-believe.
BookOS: a reading & note-taking workspace
Talked to 10 readers to understand where their reading workflows broke down: PDFs, highlights, and notes living in separate tools with no sense of progress. Scoped and shipped an MVP around that insight: an in-browser PDF reader, cloud-synced library, notes tied to highlights, and a reading dashboard with progress tracking and streaks.
Valorant: ranked & retention teardown
Working through what's actually happening inside Valorant's progression and ranking systems, and why the behavioural design feels more deliberate than most competitive games admit. Notes in progress, not a polished thesis yet.
Slack: positioning & adoption case study
A slow-built case study on how Slack got adopted, positioned, and grew, focused on the parts most teardowns skip: communication norms, internal momentum, and what “good timing” actually means in B2B.
AI workflow & writing experiments
Notes from using Claude and GPT as actual thinking partners, for research, drafting, and developing ideas. Trying to figure out where AI genuinely changes how I think, and where it just makes me feel productive.
Legal internship discovery: workflow experiment
A small product experiment for a specific friction: how fragmented opportunity discovery is for legal internships. Aggregating listings, surfacing relevant firms, and trying to reduce the anxiety of always feeling like you’re missing something.
Reflections: philosophy, systems, technology
An ongoing journal of short notes: what I notice using AI tools, why one product feels considered and another doesn't, what changes in me when I adopt a new workflow. Mostly thinking out loud. Some of these may show up here as proper writing later.
I tend to notice the systems behind things, and the small details inside them.
I come from a technical, research-leaning background, but most of what I actually spend my time on sits between disciplines: AI, systems, workflows, design, psychology, and how products end up feeling the way they feel. I'm trying to learn how good digital products actually get built, by reading, taking things apart, and looking closely enough to understand why something works.
I'm not a senior PM, a founder, or an "AI expert." I'm someone in the middle of figuring all of that out: reading a lot, taking small things apart, writing notes I rarely publish. The questions I'm most drawn to are the boring-sounding ones: why does this feel good to use? what's the hidden workflow underneath this product? what changed in me when I started using this tool?
The projects on this site are mostly explorations in progress. They're closer to how I actually think than anything that'd fit on a résumé, and most of them aren't finished. I'd rather show what I'm working through than wait until everything looks polished.
- 01 What makes a digital product feel considered, versus one that just functions?
- 02 What does it actually take to think with AI, rather than just produce faster with it?
- 03 Is taste something you can practice, or just something you slowly notice in yourself?
Most of what's here is mid-thought. I'd rather show that, than wait until everything looks finished.
K.If something here resonated, or you're poking at similar things, I'd love to talk.
I'm not selling anything. Mostly just curious about people thinking about the same questions: AI, product, systems, how good digital experiences get built. Happy to compare notes, share what's in progress, or just say hi.