I was diagnosed with Bipolar in 2021 after a major manic episode following my recovery from the physical symptoms of COVID.

Background

The last 4 years have been a particularly challenging time for me as I’ve learned to identify triggers / patterns that improve / worsen my disorder.

I’m really grateful to everyone who has supported me through this challenging time. Apart from family, I’ve been very lucky to have friends around me who take care of me. Some names I’d like to drop are: Shivam for pinging me and pushing me. Shreyansh for being an ideal younger brother and Rachit for always calling.

I wrote these lines some time back:

कुछ दोस्त मुझे यूँ मिले हैं ऐसे

गुलाब को गुलदान मिले हो जैसे

(Some friends have found me / like a vase finds its rose.)

I also owe apologies. To people I’ve hurt - with words, with actions, with silence. Some of it was the disorder talking. Some of it was just me. The line between the two isn’t always clear, and I’m not using bipolar as an excuse.

If you’re reading this and I’ve wronged you - intentionally or not - I’m sorry. I’m working on it. I can’t promise I won’t slip again, but I can promise I’m more aware now than I was before.

Why I’m sharing this now

For 4 years I’ve mentioned “health stuff” to colleagues and acquaintances without naming it. That ambiguity felt protective but also isolating. I’m tired of the cognitive load of half-truths.

There’s also the data angle: I’ve been tracking myself obsessively since diagnosis, and the patterns are finally clear enough to share. If even one person sees their own experience reflected here—or learns what to look out for—this post will have been worth it.

In this post, I present data analytics on my personal data that highlights the effects of / causes & some surprising benefits of being bipolar.

We start with a brief overview of what the polarity spectrum looks like & then quickly dive deep into the data and some visualisations.

All of the code used to create this is public here:

What is Bipolar?

Bipolar is a mood disorder, characterised by a boom-bust cycle of elevation and depression. Like all sinusoidal waves, it has both an amplitude and a time period.

And yes - the title is a double meaning. I ride an actual cycle too. It’s a Hero cycle I got from my elder brother - no gears or suspension. Premium Rush style. And a carrier. Not a pannier, mind you. A proper - can carry an atta-katta - carrier.

Early morning rides became my cheapest mood regulator: 20 km before sunrise resets whatever the night scrambled. The physical bi-cycle and the mental one are now inseparable in my head.

For me specifically:

Hypomania looks like: sleeping 2 hours and feeling invincible, non stop poetry writing, starting 5 side-projects, talking too fast.

Depression looks like: 14-hour sleep, unanswered messages, code that feels pointless, even basics like a bath starts to feel like a chore.

Modelling the cycle

So, what does a cycle look like? Not a bi-cycle (soft pun?), not a tri-cycle, but the bipolar cycle!

One of my move 37 ideas - a term from AlphaGo’s famous game, meaning an unexpected creative leap - was to look at this cycle from the lens of Ray Dalio whose work has gone into characterizing Economic cycles.

I’ll be writing a separate post on this soon. For those curious, here’s something to hold you over.

In the age of AI

When I’m elevated, some of my thoughts can be too crazy for even myself. I’ve derived huge value from ChatGPT DeepResearch for exploring chains of thoughts that can only come from a human hypo filled haze.

Applying Taleb’s model of fragility to organisational silos was one such example. I still remember the sigh of relief I breathed when the model confirmed I was thinking in the right direction.

My post on the parallels between Turing and Swartz’s deaths was another case where the LLM helped me chase a thread I couldn’t have followed alone.

Where am I now

Elevated, again. Sleeping 2-3 hours a night. Currently on lorazepam (sleep aid) and aripiprazole (mood stabilizer), with psych appointments every couple of months.

What’s helped most? Meds — especially sleep aids. And exercise to channel the excess energy. The cycling isn’t just a metaphor.

What I wish I’d known at diagnosis: how hard it all is. At my highs I have infinite optimism. At my lows, infinite pessimism. After a few cycles of this, it takes its toll.

I’m not fully comfortable talking about how this has affected my work. What I will say is that there are colleagues who stood by me at my times of need.

The data tracking isn’t about control — it’s about understanding. I’m not concerned with what exists today. I don’t want my brother to go through this. Or my children. I’d like to “solve” bipolar before I die, with solid technology. That’s who I am.

This post is part of that. I have multiple lenses now — Surah Ad-Duha from the Quran, a spring-mass-damper system, the Dalio model. I’ll be sharing these in future posts. The goal is to benefit anyone else going through this.

If you haven’t heard from me in a while — reach out. I appreciate it more than you know.