JEE and academia

This is (hopefully) a quick post I’m dashing off from the sidelines of the Basavanagudi aquatic Center where I’ve brought my daughter for her weekly swimming lessons

I write this as I’m reading Eric Hoel’s post on why he is leaving academia. Basically he talks about all the “extra curricular activities” that an academic nowadays needs to do. Reviewing journals, being on student bodies and the like.

The other reason he quotes is about how restrictive academia is – again because he is being evaluated on multiple dimensions, rather than simply on the quality of his research and teaching.

Given all of this, following four years as an assistant professor at tufts, he has chosen to quit academia full time and become a writer of newsletters. and he writes that “being an academic is not so easy any more”.

I was reminded of an old post I’d written about Indian and American universities. American universities admit students based on “a holistic set of factors”. So your test scores are important but so are your sports and charity work and 10 different kinds of extra curricular activities and all that.

Indian universities (at least the ones I went to) are far simpler – they admit solely on the basis of test scores.

After reading some articles on how the US admission process was producing highly homogeneous classrooms at universities, id written a few years back on how the Indian system rocked – because admissions were based on a single criterion, there was tremendous diversity jn the classrooms on all other criteria.

Now based on Hoel’s post I’m wondering if the same is true of teachers as well – the more the dimensions on which we evaluate professors for recruitment and tenureship, the more homogeneous the professorial class gets. Instead if we were to evaluate professors on narrowly defined conventional criteria (teaching and research) we’ll get a far more richer and diverse professors body.

This, however, is easier said than done. Quality of research is usually evaluated based on the quality and quantity of papers, and papers necessarily go through a peer review process.

And if your peers are all those who have succeeded in the “selected by holistic criteria” game, then you will have to conform to some of their biases to get good papers published.

All this said, I’m hopeful that in the next decade or so we will have a bunch of new and privately funded universities which Yale universities back tk what they used to be – centres of research and teaching , with professors selected on their credentials on these axes only, and a diverse body of students selected hopefully on a a small number of axes (such as test scores).

More on CRM

On Friday afternoon, I got a call on my phone. It was  “+91 9818… ” number, and my first instinct was it was someone at work (my company is headquartered in Gurgaon), and I mentally prepared a “don’t you know I’m on vacation? can you call me on Monday instead” as I picked the call.

It turned out to be Baninder Singh, founder of Savorworks Coffee. I had placed an order on his website on Thursday, and I half expected him to tell me that some of the things I had ordered were out of stock.

“Karthik, for your order of the Pi?anas, you have asked for an Aeropress grind. Are you sure of this? I’m asking you because you usually order whole beans”, Baninder said. This was a remarkably pertinent observation, and an appropriate question from a seller. I confirmed to him that this was indeed deliberate (this smaller package is to take to office along with my Aeropress Go), and thanked him for asking. He went on to point out that one of the other coffees I had ordered had very limited stocks, and I should consider stocking up on it.

Some people might find this creepy (that the seller knows exactly what you order, and notices changes in your order), but from a more conventional retail perspective, this is brilliant. It is great that the seller has accurate information on your profile, and is able to detect any anomalies and alert you before something goes wrong.

Now, Savorworks is a small business (a Delhi based independent roastery), and having ordered from them at least a dozen times, I guess I’m one of their more regular customers. So it’s easy for them to keep track and take care of me.

It is similar with small “mom-and-pop” stores. Limited and high-repeat clientele means it’s easy for them to keep track of them and look after them. The challenge, though, is how do you scale it? Now, I’m by no means the only person thinking about this problem. Thousands of business people and data scientists and retailers and technology people and what not have pondered this question for over a decade now. Yet, what you find is that at scale you are simply unable to provide the sort of service you can at small scale.

In theory it should be possible for an AI to profile customers based on their purchases, adds to carts, etc. and then provide them customised experiences. I’m sure tonnes of companies are already trying to do this. However, based on my experience I don’t think anyone is doing this well.

I might sound like a broken record here, but my sense is that this is because the people who are building the algos are not the ones who are thinking of solving the business problems. The algos exist. In theory, if I look at stuff like stable diffusion or Chat GPT (both of which I’ve been playing around with extensively in the last 2 days), algorithms for stuff like customer profiling shouldn’t be THAT hard. The issue, I suspect, is that people have not been asking the right questions of the algos.

On one hand, you could have business people looking at patterns they have divined themselves and then giving precise instructions to the data scientists on how to detect them – and the detection of these patterns would have been hard coded. On the other, the data scientists would have had a free hand and would have done some unsupervised stuff without much business context. And both approaches lead to easily predictable algos that aren’t particularly intelligent.

Now I’m thinking of this as a “dollar bill on the road” kind of a problem. My instinct tells me that “solution exists”, but my other instinct tells that “if a solution existed someone would have found it given how many companies are working on this kind of thing for so long”.

The other issue with such algos it that the deeper you get in prediction the harder it is. At the cohort (of hundreds of users) level, it should not be hard to profile. However, at the personal user level (at which the results of the algos are seen by customers) it is much harder to get right. So maybe there are good solutions but we haven’t yet seen it.

Maybe at some point in the near future, I’ll take another stab at solving this kind of problem. Until then, you have human intelligence and random algos.

 

Hot hands in safaris

We entered Serengeti around 12:30 pm on Saturday, having stopped briefly at the entrance gate to have lunch packed for us by our hotel in Karatu. Around 1 pm, our guide asked us to put the roof up, so we could stand and get a 360 degree view. “This is the cheetah region”, he told us.

For the next hour or so we just kept going round and round. We went off the main path towards some rocks. Some other jeeps had done the same. None of us had any luck.

By 2 pm we had seen nothing. Absolutely nothing. For a place like Serengeti, that takes some talent, given the overall density of animals there. We hadn’t even seen a zebra, or a wildebeest. Maybe a few gazelles (I could never figure out how to tell between Thomson’s and Grant’s through the trip, despite seeing tonnes of both on the trip). “This is not even the level of what we saw in Tarangire yesterday”, we were thinking.

And then things started to happen. First there was a herd of zebras. On Friday we had missed an opportunity to take a video of a zebra crossing the road (literally a “zebra crossing”, get it?). And now we had a whole herd of zebras crossing the road in front of us. This time we didn’t miss the opportunity (though there was no Spice Telecom).

Zebra crossing in Serengeti

And then we saw a herd of buffaloes. And then a bunch of hippos in a pool. We asked our guide to take us closer to them, and he said “oh don’t worry about hippos. Tomorrow I’ll take you to a hippo pool with over a fifty hippos”. And sped off in the opposite direction. There was a pack of lions fallen asleep under a tree, with the carcass of a wildebeest they had just eaten next to them (I posted that photo the other day).

This was around 3 pm. By 4 pm, we had seen a large herd of wildebeest and zebra on their great annual migration. And then seen a cheetah sitting on a termite hill, also watching the migration. And yet another pool with some 50 hippos lazing in it. It was absolutely surreal.

It was as if we had had a “hot hand” for an hour, with tremendous sightings after a rather barren first half of the afternoon. We were to have another similar “hot hand” on Monday morning, on our way out from the park. Again in the course of half an hour (when we were driving rather fast, with the roof down, trying to exit the park ASAP) we saw a massive herd of elephants, a mother and baby cheetah, a pack of lions and a single massive male lion right next to the road.

If you are the sort who sees lots of patterns, it is possibly easy to conclude that “hot hands” are a thing in wildlife. That when you have one good sighting, it is likely to be followed by a few other good sightings. However, based on a total of four days of safaris on this trip, I strongly believe that here at least hot hands are a fallacy.

But first a digression. The issue of “hot hands” has been a long-standing one in basketball. First some statisticians found that the hot hand truly exists – that NBA (or was it NCAA?) players who have made a few baskets in succession are more likely to score off their next shot. Then, other statisticians found some holes in the argument and said that it was simply a statistical oddity. And yet again (if i remember correctly) yet another group of statisticians showed that with careful analysis, the hot hand actually exists. This was rationalised as “when someone has scored a few consecutive baskets, their confidence is higher, which improves the chances of scoring off the next attempt”.

So if a hot hand exists, it is more to do with the competence and confidence of the person who is executing the activity.

In wildlife, though, it doesn’t work that way. While it is up to us (and our guides) to spot the animals, that you have spotted something doesn’t make it more likely to spot something else (in fact, false positives in spotting can go up when you are feeling overconfident). Possibly the only correlation between consecutive spottings is that guides of various jeeps are in constant conversation on the radio, and news of spottings get shared. So if a bunch of jeeps have independently spotted stuff close to each other, all the jeeps will get to see all these stuffs (no pun intended), getting a “hot hand”.

That apart, there is no statistical reason in a safari to have a “hot hand”. 

Rather, what is more likely is selection bias. When we see a bunch of spottings close to one another, we think it is because we have a “hot hand”. However, when we are seeing animals only sporadically (like we did on Sunday, not counting the zillions of wildebeest and zebra migrating), we don’t really register that we are “not having a hot hand”.

It is as if you are playing a game of coin tosses, where you register all the heads but simply ignore the tails, and theorise about clumping of heads. When a low probability event happens (multiple sightings in an hour, for example), it registers better in our heads, and we can sometimes tend to overrepresent them in our memories. The higher probability (or “lower information content”) events we simply ignore! And so we assume that events are more impactful on average than they actually are.

Ok now i’m off on a ramble (this took a while to write – including making that gif among other things) – but Nassim Taleb talks about it this in one of his early Incerto books (FBR or Black Swan – that if you only go by newspaper reports, you are likely to think that lower average crime cities are more violent, since more crimes get reported there).

And going off on yet another ramble – hot hands can be a thing where the element of luck is relatively small. Wildlife spotting has a huge amount of luck involved, and so even with the best of skills there is only so much of a hot hand you can produce.

So yeah – there is no hot hand in wildlife safaris.

Animals in motion and animals at rest

We are back in moshi now after a 4 day safari across northern Tanzania. We did one safari each in tarangire national park and ngorongoro crater, and two whole days of safari at Serengeti. During that time we even spent the nights in (luxury) tents inside the Serengeti park.

In terms of animal “sightings” there was absolutely no comparison to what we’ve seen in india (Bandipur / kabini / Bhadra). Back home we’ve failed to see a single big cat in the wild, across 10 safaris. We very easily went into double digits on this trip.

The main difference I think is the terrain. Karnataka is all thick forests which means that visibility is low. An animal needs to be within a couple of tens of metres from the road for you to be able to see it.

In the African savannah (will come to that in a bit, or in another blogpost), though, you can literally see for miles and miles and miles and …

https://open.spotify.com/track/64SFBGTQvXgEHds3F01rpc?si=_sYbcLzZQ5eCaJGGZ1T09Q&context=spotify%3Asearch%3Ai%2Bcan%2Bsee%2Bdor%2B

On the first day in tarangire I spotted an elephant from at least a kilometre away. Turned out it was a herd, drinking water from the tarangire river stream. And we could keep our eyes on it while our driver-guide navigated the paths and bends to take us close to them. This kind of visibility would have been impossible in the Karnataka forests.

It was more stark with the big cats. If you go on any safaris in Karnataka and ask the guides about potential sightings they talk about it in terms of “movements”. Stuff like “there has been good movement of tigers in the last two days but not so much of leopards” etc.

This is important because in the thick forests of Karnataka pretty much the only time you can spot big cats is when they are moving. When they are at rest (as big cats are wont to be a lot of the time) they are resting away from the roads, and because of the terrain they are impossible to spot.

Things can’t be more different in the East African savannah. Our first sightings of lions, on Saturday afternoon, for example, was of a pack sleeping right next to the road.

My fingers added for context, to show how close they were

Even when the animals are resting away from the tracks, the nature of terrain means that you can still spot them. And this – the fact that you can see for miles in the savannah – means that the chances of spotting an animal at rest are significantly higher.

We saw at least four other packs of lions resting under bushes. Our only leopard sighting was of one sleeping on a tree (from what I hear it was there for so long – obviously, since it was sleeping – that pretty much everyone who was in Serengeti on Sunday afternoon managed to see it). Our first cheetah sighting was of one resting on a termite hill. And so on.

So the main reason you see more big cats in Tanzania, compare to india, is that the terrain allows you to see them at rest. And the cat lifestyle is based on short hunts followed by long periods of rest, which means this massively ups the chances of seeing them.

Now I wonder how it is in grassy areas in india, such as Assam.

Tanzania – initial thoughts

This is our first overseas holiday since august 2019 and it still hasn’t sunk in that we’re not india. It’s been 4-5 hours since we landed at Kilimanjaro international airport, and while thjings have been nice there is very little evidence so far that we are in “forin”.

Vehicles drive on the left side of the road. There are plenty of motorcycles. Trucks are brightly painted. Buses look like those in our city, though a lot of them seem smaller.

The weather is also similar – we’ve swapped 12.8 degree north and 920M above sea level for 3 degree south and 1000M above sea level. It was sunny in the afternoon but there has always been a nice breeze blowing – from the nearby Kilimanjaro!

The place is dry though. there is a lot of dust. And dusty winds. And very little vegetation (outside of our hotel). Our guide, on the way from the airport to the hotel, informed us that rains have been delayed this year and so things have been dry.

So all put together, it’s so far been like being somewhere in india itself, just a part that is drier and dustier than bangalore. The only differences so far have been –

Our guide drove far more carefully than I’ve seen Indian drivers. very measured in overtaking. No honking. Etc.

Looks like liquor licences here are far more liberal than in india. There is some charm sitting at a tiny hotel bar drinking. India’s restricted liquor licenses (Im told there have been no new liquor licenses in Karnataka since 1993 or something) means you need a certain scale to operate a bar. So you have few quaint dribbling places.

But that’s about it. Midway through this blogpost the power supply at the hotel went off. and this post will get published when the power gets restored. And I don’t even know if the hotel here has power backup!

Cross docking in Addis Ababa

I’m writing this from Addis Ababa bole international airport, waiting for my connection to Kilimanjaro. We arrived here some 3 hours back, on a direct flight from bangalore.

The flight was fine, and uneventful. It was possibly half empty, though – the guy in the front seat had all 3 seats to himself and had lay down across them.

Maybe the only issue with the flight was that they gave us “dinner” at the ungodly time of 3am (1230 Eastern Africa time). I know why – airlines prefer to serve as soon as they take off since food is freshest then (rather than reheating at the end of the flight). And if they serve two meals the second one is usually a cold one (sandwiches cakes etc)

The airport here is also uneventful. There are a couple of bars and a few nondescript looking coffee shops. It is linear, with all gates being laid out in a row (reminds me of KL, and very unlike “star shaped airports” such as Barcelona or Delhi).

In any case I’ve been doing the rounds since morning looking for information of my flight gate. The last time I saw it hadn’t yet been published. But there was something very interesting about the flight schedule.

Basically, this airport serves as a cross dock between Africa and the rest of the world, taking advantage of its location in one corner of the continent.

For example, all flights that have either departed in the last hour or due to depart in the next 2 hours are to various destinations in Africa (barring one flight to São Paulo and Buenos Aires).

Kinshasa. Cape Town. Douala. Antananarivo. Entebbe. Accra. Lubumbashi via Lilongwe. Mine to Kilimanjaro (and then onward to Zanzibar). Etc. etc.

No flight that goes north or east, barring one to Djibouti. And no take offs between 6am (when we landed here) till 815 (Cape Town). And until around 8, people kept streaming into the airport (and the lines at the toilets kept getting longer!)

Ethiopian’s schedule at bangalore is also strange. Flights arrive at 8am 3 days of the week and then hang in there idly till 230 am the next morning. Time wise, that’s incredibly low utilisation of a costly asset like an aircraft (that said it’s a Boeing 737Max).

After looking at the airport schedule though it makes more sense to me. Basically in the morning, flights bring in passengers from all over Asia and Europe, and connect them to various places in Africa.

In the evenings, flights stream in from all around Africa and cross dock people to destinations in Europe and Asia. Currently the cross dock is one way – out of Africa in the evenings and into Africa in the mornings.

This means that there are some destinations where, given time of travel, the only way to make this cross dock work is to keep the aircraft idle at the destination. In African destinations for example, I expect shorter turnarounds – this morning I noticed that the first set of departures were to far away locations – Cape Town, Johannesburg, Accra, Harare and then to Lusaka, etc.

I don’t expect this to last long though. In a few years (maybe already delayed by the pandemic) I expect ethiopian to double its flight capacity across all existing destinations. Then, it can operate both into Africa and out of Africa cross docks twice in a day. And won’t need to waste precious flight depreciation time at faraway airports such as bangalore.

PS: so far I haven’t seen a single flight from any other airline apart from Ethiopian at the airport here.

Missionaries and Mercenaries

When a company gets founded, it does so by a bunch of “missionaries”. Founders seldom are in it solely for the money (though that is obviously one big reason they are there). They found companies because they are “missionary” about the purpose that the company wants to achieve (it doesn’t matter what this mission is – it varies from company to company).

As they start building the company, they look for more missionaries to help them to do it. Rather, among early employees, there is a self selection that happens – only people who are passionate about the mission (or maybe passionate about the founders) survive, and those in it for other purposes just move on.

And this way, the company gets built, and grows. However, there comes a point when this strategy becomes unsustainable. A largish company needs a whole different set of skills from what made the company large in the first place. And some of these skills are specialist enough that it is not going to be easy to attract employees who are both good at this specialisation and passionate enough about the company’s mission.

These people look at their jobs as just that – jobs. They are good at what they do and capable of taking the company forward. However, they don’t share the “mission”, and this means to attract them, you need to be able to serve their “needs”.

For starters, they demand to be paid more. Then, they need the recognition that the job is just a job for them – they need their holidays and “benefits” and “work life balance” and decent working hours and all that. These are things people who are missionary about the business don’t necessarily need – the purpose of the mission means that they are able to “adjust”.

The choice to move from a missionary organisation to a more “mercenary” organisation (not just talking of money here, but also other benefits and perks) needs to be a conscious one from the point of view of the company. At some point, the company needs to recognise that it cannot run on missionary fuel alone and make changes (in structure and function and what not) to accommodate mercenaries and let them grow the business.

The choice of this timing is something a lot of companies don’t get right. Some do it too late – they try to run on missionary fuel for way longer than it is sustainable, and then find it impossible to change culture. This leads to a revolving door of mercenaries and the company unable to leverage their talents.

Others – such as Twitter – do it way too early. One thing that seems to be clear (to me) from the recent wave of layoffs at the company, and also having broadly followed the company for a long time (I’ve had a twitter account since 2008), is that the company “went professional” too early.

There was a revolving door of founders in the initial days, until Jack Dorsey came back to run the company (apart from running Square) for a few years. This revolving door meant that the company, from its early days, was forced to rely on professional management – mercenaries in other words. Over a period of time, this resulted in massive bloat. The company struggled along until Elon Musk came in with an outlandish bid and bought it outright.

From the commentary that I see on twitter now, what Musk seems to be doing is to take the company back to “missionaries”. Take his recent letter for example. He is demanding that staff “work long hours at high intensity“. A bunch have resigned in protest (in addition to last week’s layoffs).

The objective of all these exercises – abrasive management style, laying off half the people first, and then putting onerous work conditions on the rest – is to simply weed out all the mercenaries. The only people who will agree to “work long hours at high intensity” will be “missionaries” – people who are passionate about growing the company and will do what it takes to get there.

Musk’s bet, in my opinion (and based on what I’ve read elsewhere), is that the company was massively overstaffed in the first place, and that there is a sufficient quorum of missionaries who will stay on and take the company forward. The reason he is doing all this in public (using his public twitter account to give instructions to his employees, for example) is the hope that these actions might attract potential missionaries from outside to beef up the staff.

I have no clue if this will succeed. At the heart of it, a 16 year old company wanting to run on missionaries only doesn’t make sense. However, given that the company had been listing (no pun intended), this might be necessary for a temporary reboot.

However, one thing I know is that this needs to be an “impulse” (in the physics sense of the term). A short and powerful jab to move the company forward. At an old company like this, running on missionaries can’t be sustainable. So they better fix the company soon and then move it on a more sustainable mercenary path.

Heads of departments

Recently I was talking to someone about someone else. “He got an offer to join XXXXXX as CTO”, the guy I was talking to told me, “but I told him not to take it. Problem with CTO role is that you just stop learning and growing. Better to join a bigger place as a VP”.

The discussion meandered for a couple of minutes when I added “I feel the same way about being head of analytics”. I didn’t mention it then (maybe it didn’t flash), but this was one of the reasons why I lobbied for (and got) taking on the head of data science role as well.

I sometimes feel lonely in my job. It is not something anyone in my company can do anything about. The loneliness is external – I sometimes find that I don’t have too many “peers” (across companies). Yes, I know a handful of heads of analytics / data science across companies, but it is just that – a handful. And I can’t claim to empathise with all of them (and I’m sure the feeling is mutual).

Irrespective of the career path you have chosen, there comes a point in your career where your role suddenly becomes “illiquid”. Within your company, you are the only person doing the sort of job that you are doing. Across companies, again, there are few people who do stuff similar to what you do.

The kind of problems they solve might be different. Different companies are structured differently. The same role name might mean very different things in very different places. The challenges you have to face daily to do your job may be different. And more importantly, you might simply be interested in doing different things.

And the danger that you can get into when you get into this kind of a role is that you “stop growing”. Unless you get sufficient “push from below” (team members who are smarter than you, and who are better than you on some dimensions), there is no natural way for you to learn more about the kind of problems you are solving (or the techniques). You find that your current level is more than sufficient to be comfortable in your job. And you “put peace”.

And then one day you find ten years have got behind youNo one told you when to run, you missed the starting gun

(I want you to now imagine the gong sound at the beginning of “Time” playing in your ears at this point in the blogpost)

One thing I tell pretty much everyone I meet is that my networking within my own industry (analytics and data science) is shit. And this is something I need to improve upon. Apart from the “push from below” (which I get), the only way to continue to grow in my job is to network with peers and learn from them.

The other thing is to read. Over the weekend I snatched the new iPad (which my daughter had been using; now she has got my wife’s old Macbook Air) and put all my favourite apps on it. I feel like I’m back in 2007 again, subscribing to random blogs (just that most of them are on substack now, rather than on Blogspot or Livejournal or WordPress), in the hope that I will learn. Let me see where this takes me.

And maybe some people decide that all this pain is simply not worth it, and choose to grow by simply becoming more managerial, and “building an empire”.

CGM Notes

At about 5:30 pm last Wednesday, I chanced upon a box of Sandesh crumbs lying in the office. A colleague had brought the sweets to share the previous day, and people had devoured it; but left aside the crumbs. I picked up the box and proceeded to demolish it as I reviewed a teammate’s work.

Soon the box was in the dustbin. I chanced upon a cookie box that another colleague had got. And started to demolish the cookies. This was highly atypical behaviour for me, since I’m trying to follow a low-carb diet. At the moment, I assumed it was because I was stressed that day.

Presently, I took out my phone to log this “meal” in the Ultrahuman app. There the reason for my binge was clearly visible – my blood sugar had gone down to 68 mg / dL, pretty much my lowest low in the 2 weeks I wore the last sensor.

This, I realised, was a consequence of the day’s lunch, at Sodabottleopenerwala. Maybe it was the batter (or more likely, the sauce) of the fried chicken wings. Or the batter of the onion pakoda. Something I had eaten that afternoon had spiked my blood sugar high enough to trigger a massive insulin response. And that insulin, having acted upon my lunch, had acted upon the rest of the sugars in my blood. Sending it really low. To a point where I was gorging on whatever sweets I could find.

About a year (or maybe two?) back, I had read Jason Fung’s The Obesity Code, which had talked about insulin being the hormone responsible for weight gain. High levels of insulin in the blood means you feel hungrier and you gorge more, or something like that the argument went. The answer was to not keep triggering insulin release in the blood – for that would make the body “insulin resistant” (so you need more insulin than usual to take care of a particular amount of blood sugar). Which can lead to Type 2 diabetes, high triglycerides, weight gain, etc.

And so Fung’s recommendations (paraphrasing – you should see my full blogpost based on the book ) included fasting, and eating fewer carbs. Here I was, two years later, finding evidence of the concepts in my CGM data.

I have worn a CGM a couple of times before. Those were primarily to figure out my body’s response to different kinds of foods, and find out what I should eat to maintain a healthy blood sugar level. The insights had been fairly clear. However, since it had been ten months since I last wore a CGM, I had forgotten some of the insights. I was “cheating” (eating what I wasn’t supposed to eat) too much. And my blood sugar had started going up to scary levels.

The objective of this round of the CGM was to find out “high ROI foods”. Foods that gave me a lot of “satisfaction” while not triggering much of a blood glucose response. The specific hypothesis I was trying to test was that sweets and traditional south indian lunch trigger my blood sugar in the same manner, so I might as well have dessert instead of traditional south indian lunches!

Two weeks of this CGM and I rejected this hypothesis. I had sweets enough number of times (kalakand, sandesh, corner house cake fudge, etc) to notice that the glucose response was not scary at all. The problem, each time, however, occurred later – maybe the “density of sugars” in the sweets triggered off too much of an insulin response, leading to a glucose crash (and low glucose levels at the end of it).

Traditional south indian lunch (I would start with the vegetables before I moved on to rice with sambar and then rice with curd) was something I tested multiple times. And it’s not funny how much the response varied – a couple of times, my blood glucose went up very high (160 etc.). A couple of times there was a minimal impact on my blood glucose. It was all over the place. That said, given the ease of preparation, it is something I’m not cutting out.

What I’m cutting out is pretty much anything that involves “pulverised grains”. Those just don’t work for me. Two times I had dosa – once it sent my blood sugar beyond 200, once beyond 180. One idli with vade sent my blood sugar from 80 to 140 (on the other hand, khara bath (uppit) with vaDe only sent it to 120). Paneer paratha (on the streets of Gurgaon) sent my sugar up to 200.

That some flours work for me I had established in previous iterations wearing the CGM – rice rotti hadn’t worked, jowar rotti hadn’t worked, ragi mudde had been especially bad. But that dose and idli and paratha also don’t work for me was an interesting observation this time. I guess I’ll be eating much less of these.

What did work for me was what has sort of become my usual meals when going out of late – avoiding carbs. One Wednesday, I got my team to order me an entire Paneer Butter Masala for lunch (Gurgaon again). Minimal change in glucose levels. That Friday, I had butter chicken (only; no bread or rice with it). Minimal change yet again! Omelettes simply don’t register on my blood sugar levels (even with generous amounts of cheese).

To summarise,

  • Sweets may not send my sugar very high, but in due course they send it very low (due to high insulin response). The only time this crash doesn’t happen is if I’ve had the sweets at the end of a meal. Basically, avoid.
  • Any kinds of pulverised grains (dosa, idli, rotti, paratha) is not good for me. Avoid again
  • The same food can have very different response at different times. This could be due to the pre-existing levels of insulin in the body. So any data analysis (I plan to do it) needs to be done very carefully
  • On a couple of occasions I found artificial sweeteners (like those in my whey protein) causing a glucose crash – maybe they get the body to release insulin despite not having sugars. Avoid again.
  • Again last week I met a friend for dinner and we had humongous amounts of seafood. I didn’t eat carbs with it. Minimal spike.
  • Some foods cause an immediate spike. Some cause a delayed spike. Some cause a crash.
  • Crashes in glucose levels (usually 1-2 hours after a massively insulin-triggering meal) were massively correlated with me feeling low and jittery and unable to focus. It didn’t matter how recently I had taken the last dose of my ADHD medication – glucose crash meant I was unable to focus.
  • Milk is not as good for me as I thought. It does produce a spike (and crash), especially when I’m drinking on an empty stomach
  • Speaking of drinking, minimal impact from alcohols such as whiskey or wine. I didn’t test beer (I know it’s not good)
  • Biryani (Nagarjuna) wasn’t so bad – again it was important I ate very little rice and lots of chicken (ordered sides)
  • Just omelette is great. Omelette with a slice of toast not so.

All these notes are for myself. Any benefit you get from this is only a bonus.

Signalling, anti-signalling and dress codes

A few months back, I read Rob Henderson‘s seminal work on signalling and anti-signalling. To use a online community term, I’ve been “unable to unsee”. Wherever I see, I see signalling, and anti-signalling. Recently, I thought that some things work as signals to one community but anti-signals to others. And so on.

I was reminded of this a couple of weekends back when we were shopping at FabIndia. Having picked up a tablecloth and other “house things”, my wife asked if I wanted to check out some shirts. “No, I have 3 FabIndia shirts in the washing pile”, I countered. “I like them but maintenance is too hard, so not buying”.

The issue with FabIndia shirts is  that they leech colour, so you cannot put them in the washing machine (especially not with other clothes). Sometimes you might get lucky to get a quorum of indigos (and maybe jeans) to put in the machine at a time, but if you want to wear your FabIndia clothes regularly you have no option but to wash them by hand. Or have them someone wash them for you.

That gave rise to the thought that FabIndia shirts can possibly send out a strong signal that you are well to do, since you have domestic help – since these shirts need to be hand washed and then pressed before wearing (the logistics of giving clothes for pressing near my house aren’t efficient, and if I’ve to do it consistently, I need help with that. I end up wearing Tshirts that don’t need much ironing instead).

On the other hand, the black T-shirts (I have several in various styles, with and without my company logo) I wear usually are very low maintenance. Plonk them into the washing machine with everything else. No need of any ironing. I don’t need no help to wear such clothes.

And then I started thinking back to the day when I would wear formal shirts regularly. Those can go into the washing machine (though you are careful on what you put in with them), but the problem is that they need proper ironing. You either spend 20 minutes per shirt, or figure out dynamics of giving them out for ironing regularly (if you’re lucky enough to have an iron guy close to your house) – which involves transaction costs. So again wearing well cleaned and ironed formals sends out a signal that you are well to do.

I think it was Rob Henderson again (not sure) who once wrote that the “casualisation” of office dress codes has done a disservice to people from lower class backgrounds. The argument here is that when there is a clear dress code (suits, say), everyone knows what to wear, and while you can still signal with labels and cufflinks and the cut of your suit, it is hard to go wrong.

In the absence of formal dress codes, however, people from lower class are at a loss on what to wear (since they don’t know what the inherent signals of different clothes are), and the class and status markers might be more stark.

My counterargument is that the effort to maintain the sort of clothes most dress codes demand is significant, and imposing such codes puts an unnecessary burden on those who are unable to afford the time or money for it. The lack of a dress code might make things ambiguous, but in most places, the Nash equilibrium is most people wearing easy-to-maintain clothes (relative to the image they want to portray), and less time and money going in conformity.

As it happened, I didn’t buy anything at FabIndia that day. I came home and looked in the washing bin, and found a quorum of indigo shirts (and threw in my 3-month old jeans) to fill the washing machine. My wife requested our domestic helper to hand-wash the brown FabIndia shirts. While watching the T20 world cup, I ironed the lot. I’m wearing one of them today, as I write this.

They look nice (though some might think they’re funny – that’s an anti-signal I’m sending out). They’re comfortable. But they require too much maintenance. Tomorrow I’m likely to be in a plain black t-shirt again.