Operator first. Builder second.
I ran two national entities at AIESEC with real P&Ls before I ever sold a Notion build. Six and a half years across sales, ops, events, and strategy. Cornell Tech AI on the academic side. Bangkok-based, working worldwide. n8n is the tool I happen to be best at; the practice is operator judgment wired into infrastructure that survives a handover.
Three documentaries, three bets on the next decade.
I revisit these whenever I am building anything meant to last longer than a sprint. The shape of career that fits this practice, the decade we are in, and the proof that narrow AI pointed at one real problem is where the value actually shows up.
Three videos. Three bets. I send these to every client who asks the real question behind the build: why are we doing this at all.
The M-Shaped Future: a career for people with too many interests
Nandesh’s notes
The video I send anyone who asks what I actually do. I am an M-shaped professional. Polymath on paper, operator in practice. That is how I ended up stacking automation, sales engineering, and product work across very different companies. Freelancing was the perfect vehicle for that shape. It let me take on the under-automated work in each company and leave once the system was handed off. Three months in Thailand was the consolidation. The M-shape stays, but now every point is load-bearing for future work.
The AI Doc, or How I Became an Apocaloptimist
Nandesh’s notes
The documentary that got every frontier-lab CEO on camera at the same time. Altman, Amodei, Hassabis, Leike, Sutskever, asked the same blunt question: what world are we building for our kids. No one walks away with a clean answer, and that is the honest part. I sit on the other side of that question every day. I am not training frontier models. I am wiring them into how small teams actually work. The bet is whether the average team, using today’s tools, can hold onto the part of the work only a human can do. Every workspace I ship makes the machine invisible so the human is left with strategy and judgement.
AlphaGo to AlphaFold: how DeepMind turned game-playing into science
Nandesh’s notes
The documentary I come back to when a client asks is AI actually useful or just hype. AlphaGo and AlphaFold were not chatbots. They were narrow, deeply-trained systems pointed at one specific, valuable problem. That is the lesson I carry into every build. The wins come from pointing AI at one workflow your team does every week and taking the chore out of it. Not an AI agent runs your whole business. A Fireflies transcript becomes a Notion page with decisions. A form submission becomes a qualified lead. Every engagement I ship is a small AlphaFold for one team’s recurring work.
Every workspace I ship is a small AlphaFold for one team’s recurring work.