The ghost of the London dream is back once again, as the new Urban Development minister has hinted at creating an “Oxford Street” like area around College Street. The plan is rather interesting: no honking zone, no cars, wider footpath. But they also made sure to use the label. Oxford Street.

If you go to any new, and apparently “modern,” tech park of a mega Indian city, you’d notice tall glass buildings, heavily influenced by US/EU style skyscrapers. The ones you generally notice in TV series and movies when they show the Manhattan skyline. They signal affluence. But a glass tower is a strange thing to import into India.1 The all-glass facade was built for cold, grey climates where you want to trap whatever sun you get. Drop the same building into Hyderabad or Chennai, and you've built a greenhouse, then spent a fortune air-conditioning your way out of a problem you designed in. We copied the skyline and skipped the reason it looked that way.

Beverly Hills is not only an affluent city in California. It is also a gated society roughly 1km away from my place. Roughly 12 kms north of this Beverly Hills, there is a busy lane, and a “modern” stylish office space around Hitech City. If you suddenly see the name of the road or building on your map, you might get surprised. It’s called Dallas Center.

Recently, Hyderabad added another jewel to its US crown: Donald Trump Avenue.

Why does this keep happening?

Both come down to status. The mechanism, though, is straight out of development economics. Kolkata's version is nostalgia for a status it once had. Hyderabad's is aspiration for a status it wants next.

For Kolkata, the root cause of this is quite straightforward. Colonial hangover. The previous CM highlighted it herself in a press briefing: how influential the city used to be under the British. She wanted it to regain its “former glory.” The route she opted for was beautification2. The new minister for urban development seems to be following the same footsteps.

For Hyderabad, it’s a bit more economical, I feel. Human beings, for centuries, want to move from lower per-capita areas to higher ones. For better opportunities, for a better life. Hyderabad’s state, Andhra Pradesh initially and now Telangana, has been one of the richest states in India by per capita income for the last 20+ years. So the question becomes: where do you go from the top of your own league? You go to the country everyone in your league is trying to reach. And what do you do when you can’t go there but want to signal the aspiration anyway? Name your cities, areas and buildings like that.3

The irony is the city’s public transport infra is mostly non-existent, like in many US states.

There's a name for this in development economics: isomorphic mimicry. It's borrowed from biology, where a harmless species evolves to look like a venomous one without ever growing the venom. Institutions do the same. They copy the visible shape of something that works elsewhere. The Manhattan skyline, the Oxford Street label, because they are cheaper and easy to see. The part that made it work is expensive, slow, and often photographs very badly, so it never arrives. Copy the skyline, skip the reason. Or better, don’t even think about the reason.

The tram plan for College Street is the part I can actually support. No cars, no honking, a cleaner street you can walk and do your book shopping. That sounds great on paper. And that's the unglamorous and boring stuff that usually never gets copied. But it comes bundled with cobblestones and matching shopfronts, because the point was never just to fix the street. It was to make it look like somewhere else. The status signalling core is still there.

College Street is already the largest second-hand book market in the world. It doesn't need to resemble Oxford Street. Oxford Street should be so lucky.

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AI sovereignty, loosely speaking, is the ability not to be entirely dependent on foreign models for your critical infrastructure, your data, and your decisions.

I am not gonna dive deep into that, but would rather dive a bit deeper into what and how Indian tech circles reacted to it. And moreover, what I think we are doing completely wrong.

I came across this post on X by Sekar Vembu (not sure if that is his real name), which encapsulates my thinking on this topic to some extent. Here is an excerpt from that:

Neither the “nationalists” nor their critics, often branded as “globalists” or worse, “anti-nationals,” seem interested in the solution that would truly benefit India and its diverse people, who are desperate for honest opportunities to use their talent, work hard, and succeed. The real moral solution for India is an ultra-minimal government combined with a maximally open and free market, operating under a system of law and justice that everyone can trust.

The values of socialism are so ingrained in us that we often turn to the Government for answers. The irony is this: even by this standard, we are failing. This is not happening because we are too socialist, but because we are not coherently anything. Or rather, we haven’t figured out what we are.

Before I write more about the incoherence, let’s actually understand what a coherent pipeline looks like.

Let’s look at the US, for example. They have a proper research talent pipeline, a lab-to-startup pipeline already in place. They have world-class research focused public & private universities where the focus has been to do precisely this. What we see today with Anthropic, OpenAI, etc., is a cumulative result. Not a singular data point. The focus of the Indian state should be to create an environment such that these research-heavy pipelines do exist. Our R&D spend (as a % of GDP) is way below that of many developing countries. The focus at the grassroots level is simply not there.

But at the same time, the government can’t really magically create 10 state-of-the-art companies just by virtue of some central funds, which is essentially what we are asking of them. And here, there can be a better way.

Let’s forget about the US for a moment. Come to Asia. Our neighbour, China. They came to the show pretty late, but as soon as the cutting-edge DeepSeek model was out & made headlines, the Chinese government went into full socialist mode. They made sure GenAI adoption happened. Many Chinese companies have already pushed “all-in-one” DeepSeek AI servers. They have set a target of 70% AI adoption for various government and private organisations.

Now compare that to India. Even with our ingrained socialistic values, we are not socialist enough to pull this off. We have Sarvam, the only leading GenAI company right now. But how many Indian companies or government organisations are actually using it? On the contrary, Indian conglomerates have announced mega deals with US-based companies.1

This is not to say that the government should coerce Indian companies into using Sarvam for everything. Absolutely not. (At the end of the day, the better models would win. As they should.) But they can easily put two of them together and initiate something. Or better, start using it for the PSUs that they are running - actively!

Maybe private insurers don't need to move immediately. But LIC can start, and their eventual success will encourage the rest.2

All these talks of AI sovereignty would bring absolutely no value if Indian companies aren’t even using it. Because a big part of the software lifecycle of these products is the feedback. Once you start using the products, you come across different roadblocks that further help in refining these models. But without proper industrial use (and only academic masturbation), this brings absolutely no value at all.

These models improve through usage. There will be edge cases that the models will miss. There will be some domain-specific use cases in which it would fail miserably. The LIC agent would randomly see an erroneous output around 10:43 AM on a Tuesday morning. These will all help shape the product. And that’s how the product would become better (and maybe even see adoption outside India!).

And the thing is, many government processes are riddled with inefficiencies. Be it getting a real estate project approval or getting a hearing in court, most of our systems are overburdened because of manual inefficiencies. GenAI, if used properly, can do wonders here. And the conversation should start here. We are currently focusing too much on the first layer: “Why doesn’t India have more GenAI companies?”

On the contrary, we are not actively asking: “Where can we deploy GenAI solutions?” Asking this question actively can bring some changes in the PSU structures also. Indian PSUs are not built to optimise for outcomes in most cases. Their approach is conservative in nature, audit-defensibility above all else, with KPIs built around uptime and compliance rather than impact. Indian states can’t whip out AI solutions like China did, but for sure, they can create some outcome-driven pilot programmes.

This, from my semi-vantage point, is a concrete policy ask. Currently, it is completely absent.

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This was one of the first things that I noticed, fresh off the train. And the thing is, Liverpool felt warm. Genuinely. The people were friendly (but a bit different from the London crowd), the pubs were loud in a good way1, and the city had a kind of bruised confidence that I found immediately familiar.

But London, the city I had just come from, the one that doesn’t advertise itself as welcoming, is actually 46% non-white by the 2021 census.2 Liverpool is 16%.3 It felt a bit like a person who introduces themselves as “very chill” at a party. The ones who don’t mention it usually are.

I have seen this before, closer to home.

Kolkata hosted South Asia’s first-ever Pride march.4 July 2nd, 1999. Fifteen people attended that event. In their colourful shirts, walking through the monsoon rain. The city had its history with rights movements, its self-image as the progressive, intellectual capital of India. And that self-image might not be entirely wrong. The adda culture, the Bhadralok, the Bengali Renaissance, Tagore. The city believes in its own openness.

But walk around a tech park in Bangalore or Hyderabad on a busy Monday morning. You would notice the sheer diversity of states, languages, accents, and food in the cafeteria. It is a melting pot of cultures. Then walk around the offices of Kolkata. The signal is drastically different.

This is not about dismissing the cities and their claims. Both cities might be welcoming. But labelling yourself as “welcoming” doesn't always translate into people from different backgrounds actually coming. For that, you need a slightly different gravitational pull. You need investments. You need to cultivate a different culture.

Both Liverpool and Kolkata were, at some point, two of the most commercially important cities in their respective empires. The ones through which the wealth actually moved. Liverpool’s docks in the 19th century were pivotal. Calcutta was British India’s commercial and administrative nerve centre until 1911, when the capital quietly shifted to Delhi.

Then came the decline. And here the stories rhyme so closely it’s almost uncomfortable.

Liverpool’s version had a clear villain with a name. After the Toxteth riots of 1981, Geoffrey Howe, Thatcher’s Chancellor, wrote a private memo suggesting the government consider “managed decline” for Liverpool.5 The suggestion was quite straightforward - don’t spend any money there. Let it go. “We must not expend all our limited resources in trying to make water flow uphill.” The memo became public 30 years later. Liverpool has not forgotten it. Almost 60% of the city voted Remain in 2016. The Conservatives haven’t won a council seat there since 1998. The city’s relationship with Westminster is structurally contentious. If one goes north, the other would prefer south.

Kolkata’s story is messier and more layered because it had multiple villains. The first one came from Delhi, and it wore the costume of fairness, whereas the reality was different. Completely.

In 1952, the Government of India introduced the Freight Equalisation Policy.6 The stated intent was balanced regional development. In practice, it subsidised the transportation of raw materials (coal, iron ore, steel) to anywhere in the country, eliminating the cost advantage of being close to the source. West Bengal, Bihar, and Odisha held over 90% of India’s iron and steel production at the time. The policy stripped them of their natural industrial advantage and redirected private capital towards Maharashtra, Gujarat, Tamil Nadu. Industries moved west and south. The unseen effect of the policy was disastrous for the East. It ran for four decades, until 1993. Pranab Mukherjee, a Bengali, later admitted it as a leading cause of eastern India’s industrial stagnation.7

Howe’s memo explicitly said, “Let Liverpool decline.” The freight policy was implicit in nature: “Let’s build a system where Kolkata’s advantage counts for nothing.” One was outright cynical in nature, whereas the other one wore the suit of an economic idea. The outcome, for both cities, was roughly the same.

Then came the homegrown villains. The Left Front governed West Bengal for 34 consecutive years. The labour militancy, the political violence, the brain drain - it was all happening at once. And then TMC, who continued the tradition of “spectacular governance” with different and worse aesthetics. Until very recently, West Bengal had never been governed by the party at the centre. Delhi and Kolkata have had a cold relationship.

Ask someone from Kolkata why Bengal always fights Delhi, and they'll say: because Delhi has always been wrong. Ask someone in Delhi, and they'll say: because Bengal has always been difficult. Liverpool and Westminster have the same conversation, in different accents.

Both cities interpreted being left behind as proof of their own distinctiveness. Which, to be fair, it partly was.

So what did they do instead?

Liverpool sold the Beatles. Kolkata sold Tagore. Both are, in their own ways, real. The cultural output of both cities, across music, literature, cinema, football, and “intellectual tradition”, is genuine and significant (Liverpool 10x more than Kolkata obviously). I am not being dismissive. But there’s a difference between a city that has culture and a city that has replaced its economy with culture.

The regeneration documents for Liverpool are full of phrases like “knowledge economy” and “creative industries.”8 But the Albert Dock tourism, Beatles pilgrimages, and stadium tours are far from being the hallmarks of a creative industry. Liverpool's own government data shows the city produces 25% less economic output per person than the national average. That gap has not changed in a decade. The regeneration documents use the phrase 'knowledge economy' anyway.

Kolkata has IIT Kharagpur nearby, ISI, Jadavpur University, and some real research output. But compare that to Hyderabad or Bangalore on actual economic footprint, and the contrast becomes clear.

Both cities were, to some extent, forced into this. The industries left. The investment didn't come. But at some point, the story you tell about being left behind stops being an explanation and starts being an excuse. The chip on the shoulder becomes the identity. The grievance becomes the brand.

Liverpool’s stadium tour is excellent. I did it. Walking out of the tunnel, into the ground where Shankly built something from nothing, you feel it. I had goosebumps. But Shankly didn’t build a monument. He built a team, with working-class people who had very little, and told them it meant more. The irony is that “This Means More” is now a premium hospitality package.

Kolkata’s Durga Puja is a genuine marvel of collective creativity, a UNESCO Intangible Cultural Heritage since 2021.9 But the same city watched its manufacturing base hollow out over three decades and responded primarily by getting better at organising the puja.

I should say where I am standing. I am from Kolkata10. I love the city unreasonably (and often I hate this fact), the way you love things that formed you before you had opinions about them. And I spent only ~48 hours in Liverpool. Long enough for a poster & the people to occupy a space in my mind. The warmth was real. The history is real. It is genuine. It attracts thousands - across the universe.

But “Open, Proud & Welcoming” on a poster at Lime Street, and “Cultural Capital of India” on a thousand Kolkata tourism websites - are both doing a specific kind of work. They are cities narrating themselves into relevance.

The ones which are, generally, don’t narrate.

This is the post I promised in The City That Invited Me to Take a Walk -“Liverpool deserved its own”

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It ended up being one of the best runs of recent times. And Garmin also updated my VO2 max after that.

I was in England for roughly 9 days. 6 of which were spent in London (in two phases), 2 in Liverpool. And 1 in Bath. This was the first time I went out of India. My wife’s1 UCL convocation was the reason for the trip. As noted from the duration of stay, the observations will be London-heavy.

For phase 1 of the London trip, we stayed near Paddington station. I had done very little research about the city before the trip (I am generally very lazy in this aspect), and I was totally surprised by it.

Most of my frame of references would be the Indian cities that I have visited and stayed in, so pardon my comparative and a bit of reductionist lenses. But I don’t think they are directionally completely wrong.

Anyways, carrying on, the neighbourhood where we were staying had many green, continuous pastures. The footpaths were wide. The air was comparatively cleaner (AQI was around 10). I knew about the AQI, and had a slight idea about the footpaths also, but the greenery was rather surprising.

I have this habit of looking for data when I see something unique. So, I had to verify if the greenery which I was seeing around Paddington was just a local thing or not. Apparently not. Looking at HUGSI, more than 41% of London is green. In India, currently, the only big city that came close was Pune. And I haven’t visited that.

I spotted many runners on the road in the evening. And many of them were carrying a backpack. Which was kinda surprising. But apparently, London has this culture where you return home while running. This serves two purposes: you get back to your home, and you also have a workout in. I liked that.

We left London for Bath. And stayed there for a day before leaving for Liverpool. Bath is a historic city full of historical artefacts. The fish & chips I had there were heavenly. If you are a history nerd, you would love Bath - for sure.

After that, we went to Liverpool. This deserves a separate blog post, so I won’t spend much of my time here. If London was like Delhi-Mumbai, Liverpool would be like Kolkata. There are some strong, striking resemblances also. I will cover them in a detailed blog post later.

After 2 days in Liverpool, we came back to London. And this time, the weather was completely different. Previously, it was windy and a bit chilly. Now, it has become hot and sunny. This time, we stayed near Euston Square. This area, particularly, had many Indian restaurants (and expats too!). Even in Paddington, there were a few Indian & Pakistani restaurants (had Delhi & Lahore in their name), but here the number was quite high.

We took the tube (basically their metro) for most of our commute. Efficient, and the fares are capped - once you hit GBP 8.90 on your Oyster card for the day, you travel free for the rest of it. I only found out midway through the trip. This felt like a great nudge for citizens to take the tube!

Sunday, 24th May, was the final day of this season’s Premier League football. The streets were vibrant and colourful. Spotted many Arsenal fans and a few Spurs. And most of the Arsenal fans were mocking the Spurs fans. A few fans of other teams were also there, who were eating and drinking in eateries and pubs. And having serious discussions about their teams. This whole scene reminded me of Kolkata’s football culture to some extent. We would often see this level of banter between East Bengal and Mohun Bagan fans. But London was far more vibrant - for sure.

When I woke up on my 2nd last day, I received a “new trend” notification in my Apple Health.

I like walks. And running. As you can see. My 21-day average was around 10k steps. But in England, for the last 7 days, it was around 21k steps. The last day, I went for a run around the street. It was a bit annoying as I had to stop on every signal, but even after accounting for that, it was far more pleasurable than running in India. My respect for Indian runners (and people who walk) increased greatly. To commit to a cause even after so many obstacles is not a matter of a joke. That day, I ended the day with 30k steps.

London just invites you to walk. Wide roads, greenery, a kind of ambient permission to slow down even when the city is busy. There were suited types (the tech and fin bros) rushing somewhere, and there were people just sitting in parks doing nothing in particular. Both kinds seemed comfortable existing in the same city.2

I love city centres. Seeing many people from hugely different backgrounds coming together for work is refreshing. London had some added layers on top of that. The greenery and Victorian architecture.

I always thought of immigration as a means, not as an end. You leave your city and country to pursue something - a job, a degree, etc. So it made little sense to me when I would come across people whose only target would be to leave India at any cost.

But after this trip, that started making some sense to me.

London doesn’t make the argument loudly though. It just shows you what a city can feel like when the basics are sorted - the air, the footpaths, the green. And somewhere between the Kensington run and the 30k steps on the last day, I think I got it.

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I have a habit of skimming through election manifestos. They are not written in the stars, and a huge chunk of what’s promised never gets implemented anyway. But they give you a directional read on how a party thinks about socio-economic problems.

I remember skimming through the Communist Party of India (Marxist) manifesto in 2024. I loved the social section. They talked about legalising “civil unions” 1 for same-sex couples, a stronger anti-discrimination bill, and measures against honour killings. I was beaming with joy: “Damn! Finally! This is awesome!”

Then I hit the economics section. I felt like vomiting. It felt like the person you fall in love with turned out to be a criminal. The proposals wanted to reverse privatisation across PSUs, introduce a statutory minimum wage decree linked to CPI, double MGNREGA allocations while adding urban employment guarantees, and re-impose trade restrictions. Everything pointed back toward the same license raj2 that kept millions at the mercy of the state for four decades.

Congress's Nyay Patra (The Manifesto of Justice) promised to fill 30 lakh government vacancies and hinted at taxing the wealthy. It was enough to alarm the middle class, not enough to inspire the poor. On social issues, they were cautiously progressive. Vague commitments on caste census, a nod toward minority rights, nothing that would cost them votes. BJP needed nothing more. The BJP's Sankalp Patra (The Manifesto of Pledge), meanwhile, was mostly about continuity and delivery of existing schemes. Free ration for five more years, MUDRA loan limits doubled. On social issues, the silence was loud. The Uniform Civil Code got a mention, but LGBTQ did not - competent welfare, dressed up as vision.

Some aspects of each I liked. Some I couldn’t stomach. The pattern continued across every manifesto I read.3

I have been trying to find a home for my political beliefs for a while. After some soul-searching, I have accepted there isn’t one. A few tenets of what I believe:

• I am pro-LGBTQ. They should have matrimonial rights in India.

• I believe in secularism. The temple, mosque, and church should be separate from the state.

• I believe in free markets. Proper free markets, not ones where only the big conglomerates get richer. 4

• Agriculture in India should be commercialised and privatised to some extent.

• The government should largely subsidise healthcare (specially for a country like ours), but private players should be allowed to step in.

• True competition in the private sector should exist, and the government should ensure that, without over-regulating.

• Reservations should exist, but we need to exclude those who already have proper representation and privilege.

• I believe in a strong social safety net. Garlic bread and pasta may not be everyone’s right, but bread and butter is.

After some research, I came across libertarianism. It is popular in the US, and closely mirrors most of what I believe, except for one thing, which is a dealbreaker. Libertarians are strongly against social welfare. I am not. I believe it is the government’s & society’s moral duty to ensure everyone can afford dal and bhat (Dal & Chawal). Beyond that floor, market dynamics should do the work.

Turns out there’s a school of thought built exactly on that tension: Ordoliberalism, or Social Liberalism. The German post-war model. The state as referee and safety net, not as player. It even has a phrase for it: Soziale Marktwirtschaft, social market economy.

I started developing a propensity toward the word “liberal” for a separate reason. In Indian social media and political discourse, both the left and right use “liberal” as an insult. I figured: there has to be some merit in a position that both sides find threatening. The liberals might be doing something right. Even though the word means 100 different things to 1000 different people, I have started identifying with the tenets of social liberalism.

Having a set of beliefs instead of a loyalty to a party is uncomfortable. There’s a degree of what I can only call atheistic discomfort. Bhagat Singh was a staunch atheist5. In his writings, he described how the absence of belief in any supernatural force, in any structure larger than himself, worsened his suffering. A belief system might have eased his pain.

Believing in the tenets of social liberalism does something similar. You stop relying on a party. You start questioning their motives. You know, quietly, that none of them will bring the social change you want to see. In your city. In your state. In your country.

They are not your football club. You don’t cheer for them. The tribal instinct is missing.

In my neighbourhood, about a kilometre from my place, there is a beautiful lane built (not sure who maintains it) by one of Hyderabad’s major real estate builders. It has greenery, some standalone gated bungalows and a massive high-rise. I love my evening walks there. And I often have the same internal argument:

“God bless capitalism. No government agency could build and maintain something like this. But when these buildings went up, the promoters made far more than the workers. Then again, ten thousand people got paid who otherwise wouldn’t have. Isn’t that still better than a barren plot?”

I never quite resolved it. I don't think I am supposed to.

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I didn’t pay much attention to exit polls, and what they had projected, until someone brought to my attention one tweet which was supposed to be “exposing” the fraud techniques of PPA.

At that moment I found it quite interesting 1. I tweeted about it but couldn’t write this one up. I had some major family functions. So I thought I would write up why I found their numbers and methods quite interesting. Being an Analytics professional, it made some sense to me.

First things first, one thing that we need to keep in mind: every model is wrong. Some are useful. There are some assumptions that you need to make while modelling.

In this video, we can hear the head of PPA talking about their assumptions and methodologies. They apparently covered more than 6 lakh voters in West Bengal. 4.5 lakh were male and 1.5 lakh were female. They started doing this 4-5 months before the poll. They seemed to be following a bottoms-up approach, as opposed to Axis My India which follows a top-down approach. Pradeep Gupta of Axis My India had mentioned this distinction2. Their first job is to gauge who is winning the election (a macro trend), and then they try to predict how much everyone is getting. PPA seems to be doing the opposite.

Anyways, doubling down on their methodology now, one by one.

4.5L Male vs 1.5L Female

I had an assignment in my previous company. I had to build a model to predict whether a doctor would recommend a prescription drug. We found that the presence of one particular risk factor almost guaranteed that this medicine would be prescribed, roughly 90% of the time. If it was absent, things became trickier, and we had to do some complicated modelling for that.

What we did was simple. If the risk factor is present, it is automatically a positive case for prescription. For the rest, a model is used.

When someone pointed out the 4.5L vs 1.5L split in a reply to that tweet, they called it a biased sample. I thought the opposite. This imbalance is a feature, not a bug.

Women in West Bengal have overwhelmingly voted for TMC. Maybe except a small section, the preference is near-deterministic. So once you start calculating from your sample and see that irrespective of age, location, or anything else, a statistically significant number of women voters are going to one party, you don’t really need more of them. A homogeneous group doesn’t need a large sample to be estimated accurately. You can simulate voters in each constituency from a smaller base, and make a healthy projection.

Male voters are the ones who differ a lot demographically (at least that has been the case historically). Age, area, community, occupation: all of it plays a role. For this, you need to make many cuts of the data and find statistical significance at each level. So it absolutely makes sense to have more people from that category.

Is the number enough?

With 6 lakh total across 294 constituencies, you are working with roughly 2,000 effective samples per constituency on average. The margin of error at 95% confidence works out to about plus or minus 2.2%, and with a realistic design effect accounting for clustered sampling, you are closer to plus or minus 3.5%.

The male sample (4.5 lakh across 294 seats, roughly 1,530 per constituency) is where the real modelling happens. And here is where it gets a bit uncomfortable. PPA is doing bottoms-up. That means they are building the prediction seat by seat, constituency by constituency, not detecting a broad state-level wave and working downward. For that approach, 1,530 respondents per seat with a margin of error of 3.5% is genuinely thin. West Bengal has had plenty of seats decided within that margin. So unless, you get a overwhelmingly large signal with male + female combined, it is a bit difficult to give a verdict for a seat.

So the sample size is the honest weak point (but apparently- this is still the highest number of people polled). It is not fraud, as the tweet implied. It is just a constraint that every field survey operates under, and one that compounds when you are making 294 individual calls rather than one aggregate projection. The results came out right. But that tension between the sample size and the methodology’s ambition doesn’t fully dissolve just because the headline number landed.

Doing it for 4-5 months

There is an important assumption baked into this. If you are collecting opinions over 4-5 months, you are assuming the person’s opinion won’t materially change in that window. That is a risky assumption on paper. But I think it holds in practice more often than not. People don’t really switch their political party of choice in a few months, unless something fairly dramatic happens.

Worth noting though: the SIR controversy (the removal of around 90 lakh voters from the rolls) peaked during the campaign window, well after data collection would have begun. That is exactly the kind of late-breaking structural event that could move opinions, particularly among voters who found their names missing. Whether that showed up in the data or was simply absorbed as noise, we don’t know.

The booth-level sampling within each constituency is another assumption that is hard to audit from the outside. If their 1,500 odd male respondents per constituency skewed toward urban booths, or particular communities, the aggregate swing detection could still be right while individual seat calls were getting lucky. A correct answer arrived at through an imperfect route is still a correct answer, but it is worth knowing which one you have.

For ambiguous problems, you need to absorb some ambiguity by making operational assumptions. That is not a flaw in methodology. It is just how applied work gets done. The alternative is paralysis.

One more thing worth sitting with

There is another data point about this election that I find genuinely interesting, separate from the methodology question.

Before the SIR, West Bengal had more women voters than men: 38.7 million versus 38.4 million. After SIR deletions, that flipped. 5.7 million women were removed from the rolls, against 3.4 million men. Women accounted for 63% of all deletions.

Now, this says nothing about preference. The women who remained may well have voted TMC at exactly the same rates as always. The question of whether 8 in 10 women voted TMC is completely separate from whether there were 38 million or 33 million women on the rolls.

But it does mean that TMC’s female voter base was structurally smaller in 2026 than in any previous election, not because preference shifted, but because a significant chunk of that base was simply not eligible to vote. Whether that was enough to swing seats is something only post-poll data will tell us. The CSDS-Lokniti survey will eventually have the gender crosstabs. Until then, we are speculating.

PPA made their assumptions, committed to them, and got the headline number right. The tweet trying to expose them as fraudulent ended up being a pretty decent advertisement for their approach.

Every model is wrong. This one happened to be useful.

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Many companies have started doing something unusual. They have started publishing weekly snapshots of how employees use AI. It often comes as a leaderboard where the employees are ranked. Or a personal email telling you how you used AI last week.

There is something very familiar about this whole exercise. Like a cover song you can’t quite remember.

For a long time, the standard unit of employee productivity was presence. Think about factory work, where hours logged were directly proportional to the output. It takes 30 minutes to produce a product. You work for 9 hours, and you produce 18 products that day. You tap in at the beginning of the day, and then tap out when it is time to head home. If the floor manager sees you near your machine, he knows you are working.

The knowledge economy broke that logic completely. When the knowledge economy became the dominant economy, managers (with the old way of thinking) started losing sleep. Your output is no longer directly proportional to your input or hours logged. A developer who stares at the ceiling for 40 mins, then ships a feature in 3 hours, is not less productive than someone who takes 6 hours or a night of coding. This should have forced a harder question: what does productive work actually look like? Most companies don’t have this figured out. So they relied (and still do) on the hours logged metric.

In Hinduism, Vishnu had ten avatars across the yugas (eras). Each one suited to the crisis of its age. Bad management has its own avatar tradition. The factory foreman becomes the incompetent knowledge-work middle manager, who becomes the incompetent AI-adoption evangelist. Same underlying worldview. Different costume.

Now that GenAI has arrived, a similar pattern is emerging. The companies are asking themselves one question: “How to gauge if the employee is actually using GenAI?” and a similar suboptimal solution is being developed. Let’s start counting the tokens consumed. Prompts fired. And let’s put it on a leaderboard to encourage more people.

Jensen Huang recently suggested that if a $500,000 engineer isn’t consuming $250,000 worth of AI tokens annually, something is wrong. There is a version of this argument that makes sense. Powerful tools should be used. Under-leveraging AI is a real problem. But the moment you turn that into a numeric expectation and tracking, you are back in Goodhart territory.

There’s a concept in economics called Goodhart’s Law. The short version: when a measure becomes a target, it stops being a good measure. The moment you tell people that token consumption is what gets rewarded, token consumption is what you’ll get. Not better thinking. Not faster shipping. Not cleaner decisions. Just more prompts. Longer conversations.

Honestly, you can’t blame the people gaming the system. When you set wrong incentives, it is bound to happen. This is a failure that is creeping from the top.

Measuring the real impact of GenAI at work is doable. But it is hard. You have to go back to your boardroom, look at old JIRA tickets, and analyse that. What was the average time to ship features with X degree of complexity in the past? How much time is it taking now? What used to take three weeks, does it take ten days now? What used to need four revisions, does it need two? That kind of measurement is doable. It just requires intellectual rigour and some patience, and most organisations are running low on both.

You can do this outside the engineering work too. Are decisions getting made faster? Are they getting reversed less often? Are first drafts closer to final outputs? Are we spending less time in meetings trying to figure out what to do next? The focus on “Are people using AI more?” is the wrong thing to do. The better question is: is the cost of getting to clarity going down?

Vishnu, at least, had a purpose for each avatar. The form changed because the problem changed. The incompetent manager’s avatars share no such logic. The problem keeps changing. The solution stays the same: find a number, trust the number, reward the number.

The tap-in, tap-out in the knowledge economy never really measured work. It measured the anxiety of managers who didn’t know how else to look. Tokenmaxxing is just the same anxiety, wearing a different UI.

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In this post, I will try to capture the common theme that I saw across the 4 parts, along with some personal opinion on the polls.

The opinions expressed here are my own. Doesn’t reflect any organisation I'm part of.

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If I have to sum up what I observed across the 4 pieces (and spending 24+ hours), it would be this: West Bengal lifted the floor. It didn’t raise the ceiling.

Let’s start from the top: health. The state is able to save infants (or at least do a comparatively better job) but not mothers. States like Kerala, Tamil Nadu, and Karnataka have been doing a better job in this aspect continuously. And then there is a set of states that have been quite poor. West Bengal is stuck somewhere in between. It has done comparatively better in some of the primary access metrics. But when it comes to providing holistic care, the state is just not there.

When we shift to IT services, there is a similar pattern. It is not a leading state, by any means. We have the southern states (minus Kerala)1, Maharashtra, and NCR taking the lead there. But compared to rest of the states, WB is not doing a bad job. Even the IT services export has been more than most other states. But still, it is roughly 1/17th of what Karnataka does (the leading state). For a state to grow in this economic climate, you need more investments being made in the knowledge work economy. More values need to be generated, more jobs need to be created.

Again for manufacturing and industries, there is a similar pattern. We have the leaders in Gujarat & Odisha, who have a comparatively less IT exports than WB. But they have increased their share of manufacturing outputs over the years. They seem to be intentional in taking a particular (or multiple) route.

West Bengal’s approach in industrialization seems wide, but shallow. I don’t know if it is a bug or a feature. If it is intentional, then it is a feature. A generalist economic strategy is not inherently wrong. There can be a version of the state that is deliberately pluralist. Open to bidi, jute, IT exports & trades simultaneously. Where you don’t want to take a particular vertical, but be open to everything.

But even in that case, you would need a more aggressive approach. Generalist strategies would also require some aggressive execution. Specially when you are in the bottom half as per the per capita income figures. You are competing against states that have picked up particular lanes and running very hard on that.

Gujarat knows what it is. Telangana knew what it wanted to become and moved toward it. If WB's answer is "we want to be open to everything," then the follow-up question is: what did you do to make everything easier? The investment climate, the land acquisition process, the labour relations history, the private sector confidence, these are the conditions that make a generalist strategy viable. And the data doesn't show those conditions are being built or nurtured.

So, it doesn’t look like a feature. Rather a drift (a bug). And the drift has been accumulated over decades, across governments and policies. Being at odds with the central government for 50+ years didn't help the cause either.2

If you are aware of the cities of India, when you think of Bangalore, you would automatically think about Tech. Mumbai - Finance. Hyderabad - GCCs & pharma. Chennai (or rather Tamil Nadu) - large scale manufacturing. What about Kolkata? I can’t think of any USP. And this is a policy failure. A massive one. Small scale MSME sectors - that are hard to formalize & tax, and even harder to attract investments - can’t be your USP. The question is why this drift was never corrected. And the answer is partly structural, and partly political incentives.

The floor is what gets you re-elected. The ceiling is the hard-work that compounds over the time. Which doesn’t have a instant gratification, and for that reason often gets ignored.

Welfare schemes like Lakshmir Bhandar, Kanyashree, Duare Sarkar etc., have visible effects. A woman receives ₹1,000 in her account. She knows who sent it. That is a rational political exchange and it works. The data also confirms it works on its own terms: poverty fell, access improved, welfare reached people.

But industrial policy is different. The benefits of a big semiconductor plant,or a formal manufacturing cluster takes decades to show up in the per capita income numbers. Building a secondary school infra in a remote district often won’t have a face on it. And more often the government who started it, loses power in the meantime. The voter who got her share of Lakshmir Bhandar will vote in the election. The worker who could have had a formal job, in a plant that was never built, would never know what they missed.

This is not a problem which is only unique to the state of West Bengal. The structural incentives of democracies are present everywhere. But it becomes hugely important for a low-income state where the immediate need is quite real, and the patience for a long-horizon investment is limited, and often not politically viable.

The problem is that rationality at the political level and rationality at the developmental level are pointing in opposite directions. Elections reward the floor. Nothing rewards the ceiling. So the floor got built, and the ceiling didn’t. There are no indications that someone is attempting to build the ceiling either.

Coming to the elections, it was a very disappointing affair seeing how the leading two parties behaved. Their core message relied heavily on polarization. One opted for a region based (Bengali cultural identity), another religion based.

It was widely covered by many leading news agencies how the parties used fish, meat as a theme to promote themselves3. It is good for generating content, some memes here and there. A few viral reels, perhaps. But I personally found it utterly ridiculous. Highly disappointing.

The highest court of India rightly pointed out how polarizing and politically charged the atmosphere is in West Bengal. After judicial officials were harassed in Malda. They were on point with respect to that. But I don't know how they casually dismissed the voting concerns of millions. Offering this as reassurance: that the rights of voters purged from the rolls cannot be "washed away forever".

There is always a next election. That is exactly what people in a polarized state are told, every five years, by someone.

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Ask anyone from West Bengal about the state’s “intellectual heritage”, and they will not stop talking. Tagore. Ray. Sen. Banerjee. Two Nobel laureates in economics. One in literature, also the first Asian. A filmmaker who put Bengal on the world map. A city that ran the country for 138 years.

The data has a more complicated view.

The literacy number

West Bengal’s literacy rate in 2011 was 76.26%. The national average that year was 74.04%. Bengal was ahead and ranked 13th out of 27 states.

Not first or second. Or third. But Thirteenth.

Between 2001 and 2011, that rank did not move. India improved. West Bengal improved at roughly the same pace. No ground gained, no ground lost.1

The gender picture

This is the part of the data that is genuinely positive.

In 2011, the gap between male and female literacy in West Bengal was 11 percentage points. Among 27 major states, West Bengal was placed 9th best on gender parity. Better than Gujarat, Karnataka, Odisha, and most of the Hindi belt. The states with worse gaps included several that are conventionally considered more developed.

By PLFS 2023-24, that gap had narrowed to 6.5 points, placing West Bengal 7th best among 28 major states. The improvement is real, and it is faster than most peers.

On this one measure, West Bengal is in the better half of the country and moving in the right direction. One caveat worth keeping in mind: the improvement reflects a narrowing gap, not both genders becoming more literate. Women are closing in on men. That is a different and perhaps a more meaningful signal than the overall rise in literacy.

Where children fall off

West Bengal and Tamil Nadu are the only two states that maintain their own education MIS and submit bulk data to UDISE+2, rather than feeding directly into the national system. Their primary-level dropout figures, both reported as zero, should be read with that in mind.

The secondary level is a different story.

West Bengal’s secondary school dropout rate in 2023-24 was 17.98%. The national average is 14.1%. Among states above that average, West Bengal sits in the upper half, in the same band as Madhya Pradesh and Chhattisgarh (and surprisingly, Karnataka).3

The structural reason is visible in the school composition data. 79% of schools in West Bengal are at the foundational and preparatory level. Only 11.6% are secondary. Imagine a child who just completed Class 8 in a remote district, and the nearest secondary school is far, then the decision to continue doesn’t remain purely academic. It is logistical and economic. And that often means forcing an undue goodbye.

This is made more uncomfortable by the ghost school data. UDISE+ 2023-24 identified 3,254 schools in West Bengal with zero student enrolment, the highest count in the country. These schools collectively employed 14,627 teachers. Infrastructure and teaching capacity are concentrated where students are no longer located, while districts with growing adolescent populations lack access to secondary education. The state education minister’s response when this was reported: “I have to look into it.”4

Income and poverty

West Bengal has hovered around ₹75-82 for every ₹100 earned by the average Indian over the past decade, consistently below the national average. The gap has not closed.5

We need to take a pause and absorb what this chart is actually telling us. It does not measure absolute income. It measures how each state’s economy performs relative to the national average, on a per-person basis. If the average Indian earned ₹100 in 2023, West Bengal’s economy generated ₹82 per person, Karnataka’s ₹175, Bihar’s ₹36.

That framing matters. West Bengal is not getting poorer in absolute terms. It is failing to keep pace. And in a country where Karnataka and Tamil Nadu are pulling away, failing to keep pace is its own kind of falling behind.

This ties it back to part 2 of the series. When you have an ‘unproductive’ workforce. This is bound to happen.

The multidimensional poverty numbers tell a relatively encouraging story. West Bengal’s MPI poverty rate fell from 21.28% in 2015-16 to 11.89% in 2019-21, below the national average of 14.96%. Welfare delivery has worked. People have moved out of deprivation on the indicators that matter: sanitation, cooking fuel, electricity, and bank access. These are essential for a human being.

But almost every state improved by a comparable margin. West Bengal’s relative position did not change. The same states that were ahead in 2015-16 were ahead in 2019-21. Those who were behind are still pretty much behind. Welfare worked. It just worked everywhere. For everyone.

What the HDI says

The Human Development Index (HDI) tries to answer a simple question: how well are people actually living? It combines various factors that are important for a good life into a single number. India’s state-level HDI rankings place West Bengal at 0.674, ranked 20th among 28 major states, below the national average of 0.685.

West Bengal scores above the national average on both the health component (life expectancy ~71-72 years) and the education component (mean years of schooling ~7.5). Which is not bad. But it is the per capita income that pulls the composite down (might be the same reason why Goa is number 1). Per capita GSDP sits well below the national average.

Amartya Sen and Abhijit Banerjee. The two economists who got their Nobel for measuring and understanding human development are both from West Bengal.6 The state that produced them has a human development index score that Kerala crossed decades ago. That sentence is uncomfortable to write. But it is accurate.

West Bengal delivers at the baseline. Literacy is above average. The gender gap is narrowing. Primary enrolment is high. Poverty is falling faster than in most states. These are real, and the data is quite clear on them.

But the next layer does not hold. Secondary dropout is among the worst in the country. Per capita income is not moving upwards against the national average. HDI has been stuck in the medium band for a long time. The state gets people through the door. It has not figured out what to do with them once they are inside.

Welfare worked. Wealth did not follow.

Data sources:

• Census of India 2001, 2011 (Office of the Registrar General)

• PLFS 2023-24 (MoSPI)

• UDISE+ 2023-24 (Ministry of Education)

• Rajya Sabha Q.1131, Dec 2025 (Ministry of Education)

• NITI Aayog National MPI Progress Review 2023

• RBI Handbook of Statistics on Indian States 2024-25

• Global Data Lab Subnational HDI 2023

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India is the world’s fourth (or fifth) largest economy by nominal GDP. By per capita income, it ranks 136th. That gap is the context for everything that follows here.

At that income level, the ability of most citizens to purchase private healthcare is alarmingly limited. The quality of the public system is not a policy preference. It is essential for survival & wellbeing, which means that when you want to understand how a state is doing, the health numbers are among the most honest data available. They reflect what the system actually delivers to people who cannot opt out of it.

This piece looks at West Bengal’s health profile across five indicators: infant mortality, maternal mortality, anaemia, institutional delivery coverage, and public health financing. Some numbers are good. Others are not. Together, they describe a state that has solved one set of problems and left another untouched.

The IMR picture

West Bengal’s infant mortality rate is 17 deaths per 1,000 live births. That places it alongside Karnataka, well ahead of states like MP, UP, Gujarat, and comfortably below the national average of 25. The improvement over the past decade has been steady and real.

Infant mortality rate measures deaths in the first year of life per 1,000 live births. It is one of the most widely used proxies for a state’s health system because it captures nutrition, maternal care, immunisation coverage, and access to neonatal facilities in a single number. A state that does well on IMR has typically gotten several things right simultaneously. That is quite important for an Indian state.

Across nearly a decade, West Bengal has consistently outperformed India on this measure. The gap has been consistent.

The improvement from 31 in 2013 to 17 in 2023 tracks better than the national pace. On under-five mortality1, West Bengal has already met the 2030 SDG target of under 25. Bihar and Uttar Pradesh are still in the 30s.

The MMR reversal

Maternal mortality tells a different story. A sharply different one.

In 2014-16, West Bengal’s MMR was 101 deaths per 1,00,000 live births. India’s was 130. West Bengal was not just better than average. It was well ahead.

Then something shifted.

India kept improving. West Bengal did not. By 2017-19, the lines had crossed. India’s MMR fell to 103. West Bengal’s had climbed to 109. By the latest available data, India sits at 88. West Bengal is at 104, grouped with Bihar, well above states like Tamil Nadu (54), Maharashtra (33), and Kerala (19).

West Bengal is one of only four states where MMR increased against the national declining trend between survey periods, alongside Haryana, Uttarakhand, and Chhattisgarh2. A peer-reviewed study in Scientific Reports found that while most major states showed a broadly linear decline in MMR from 2014 to 2020, West Bengal showed a cyclical pattern, stagnating where others improved.

The infant survives. The mother does not, at rates that have stagnated over the last few years.

The access explanation does not hold

Poor MMR often stems from poor access to better institutional care. Women delivering at home, without skilled attendance, without emergency obstetric backup. It follows the basic logic.

That explanation does not fit West Bengal’s numbers3.

Institutional deliveries rose from 75.2% in NFHS-4 to 91.7% in NFHS-5. Nine in ten births now happen in a medical facility. Crucially, the cost of delivery in public facilities actually fell over this period, by Rs 5,236 per delivery on average. The access problem, to the extent it existed, has been substantially addressed.

West Bengal got more women into hospitals. But the MMR didn’t improve.

This points to a quality problem, not an access problem. Women are reaching facilities. What happens inside those facilities, and the condition women arrive in, is the unresolved question.

The anaemia evidence

The condition women arrive in is measurable and may be a more important causal factor of why the MMR numbers have stagnated. Anaemia prevalence is one of the strongest predictors of maternal mortality risk. It reduces the body’s capacity to manage blood loss during delivery, increases the risk of preterm birth, and amplifies every other complication.

West Bengal’s anaemia numbers are not just high. They are worsening, and they have been worsening across three survey rounds.

Among women aged 15-49, prevalence increased from 63.2% in NFHS-3 (2005-06) to 62.5% in NFHS-4 (2015-16), and then jumped sharply to 71% in NFHS-5 (2019-21). India’s national average is 57%. West Bengal has the highest prevalence of anaemia among women of any large state in the country.

This is not a story of a state that made progress and then slipped. Anaemia among women was high in 2005, remained high through 2015, and then deteriorated further. The NFHS-4 to NFHS-5 spike of nine percentage points is one of the largest increases recorded among major states in the period.

The men’s numbers add context. Anaemia among men aged 15-49 dropped marginally from NFHS-3 to NFHS-4, from 32.3% to 30.3%, then rose sharply to 39% in NFHS-5. India’s national average is 25%. This is not solely a women’s nutrition story. It is a systemic public health condition that affects the state’s population broadly.

What the budget says

A state with anaemia at 71% among women is a state with a chronic nutritional deficit that predates healthcare delivery. Reversing it requires sustained investment in public health infrastructure, nutrition programmes, and preventive care.

West Bengal allocated 6.4% of its total expenditure to health in 2025-26, marginally above the national state average of 6.2%. On that metric, it appears to be doing its share.

The more telling number is out-of-pocket expenditure. Per capita OOPE in West Bengal is Rs 4,010 annually4, the second highest in the country after Kerala. Over 50% of total health expenditure in the state comes directly from household spending, not government funding.

Kerala’s high OOPE reflects a wealthy population choosing premium private healthcare on top of a functional public system. West Bengal’s high OOPE reflects a public system that is not absorbing enough of the healthcare burden. Patients are paying because the alternative is inadequate.

The 2026-27 interim budget, tabled ahead of the state elections, allocated 7.5% of GSDP to social services spending. Capital outlay, the spending that builds infrastructure, has consistently undershot budget estimates by 20-34% in recent years. What is budgeted and what is built are different numbers.

The summary

West Bengal is a state that has successfully reduced infant mortality to near-southern-state levels. That is a genuine achievement, and the data is clear on it.

The same data shows a maternal mortality rate that stopped improving a decade ago and has since worsened relative to the national average. It shows anaemia among women at 71%, the highest of any large state, rising across three survey rounds. And it shows a public health financing structure where households bear more than half the cost of care.

West Bengal did the work on access. Institutional deliveries are near 92%. The gap is not in whether women reach hospitals. It is in the condition they arrive in, and in whether the infrastructure they reach is equipped to manage it.

The next piece in this series looks at literacy, education, and human development.

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Data Source:

• SRS Special Bulletin on MMR (RGI),

• SRS Statistical Reports

• NFHS-3/4/5 State Factsheets (IIPS/DHS Program)

• PRS Legislative Research Budget Analysis 2024-25 and 2025-26

• National Health Accounts 2021-22 (MoHFW)

• Contributing factors for reduction in maternal mortality ratio in India: https://www.nature.com/articles/s41598-024-65009-0

I want to pause and emphasize a bit here. This is not “knew a few people vaguely”, “oh! I have seen her on Insta”, “yeah! I have heard about him” kinda situation. I literally knew only the groom. Two from college days. One colleague. I had to travel to different states for 2/3 of the weddings. I have written about one of these weddings before, mostly about the food and the tug-of-war. This is about something else.

I was a bit nervous before the first wedding. I was pretty unsure how it would go. I am an ambivert. So, I was not sure if I would like the experience or not. I spent most of my time near the food stalls. Sipping drinks and eating kebabs. By the third time, I started appreciating the events much more. This is a unique experience. And I would highly recommend it. Why?

Mostly for two reasons.

The first is about what the invitation implies. Suppose you are invited to a wedding. If the invitation is genuine, that is something worth acknowledging. The bride/groom probably had invited 1% of the total pool of people they know. And they thought you should be one of them. That is a big privilege in itself. One shouldn’t take this for granted. The final guest list might have many constraints. Budget, venue capacity, proximity, etc. And you made it. Added to that, you are the only person from the common circle that they thought of inviting. That is also a bit special.

There is something a little ungrateful about being invited to one of the most important days of someone's life and spending it wishing you were home watching something on your laptop. Or worse, declining because you will not know anyone there, as if your own comfort is the relevant variable. It is about their life. The biggest day of their life. If you value them, just be there.

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The second reason is harder to articulate, but I think it is an important one.

I was listening to an episode of the Art of Manliness recently, a conversation with Jeffrey Hall, a professor who studies human relationships and has a book called The Social Biome. The central idea in the episode is that socialising is a kind of hormetic stressor, the same category as exercise or a cold shower. A small, acute dose of it makes you more resilient. The friction is not incidental to the benefit. It is the benefit. Just like with exercise, people tend to dramatically overestimate how bad it will feel before they do it. And post that, most of the time, we feel better.

I didn’t have the vocab for it then, but I kinda-sorta lived this principle back in 2018. In 2018, I was figuring out what to do with my life. I was trying to know myself better. I had no job. Nowhere to go. I was preparing for entrance exams1. During that period, I decided that I would always go out whenever someone had invited me. It can be an acquaintance. A distant relative. Some puja or festivals. It doesn’t matter. I will be attending them.

I would never create a comfortable space around myself. In my bed. The social stress forces you to think about what you want to do. And when you meet your peers, you also get to know about what is happening elsewhere. Someone is moving to a new city, a new country. Getting a new job. This makes you think about what you would like to do. When you are a bit aimless in life, it is quite possible to drift away. You tend to stay at home and inside your head. Which is not a great neighbourhood to stay in. Going out, meeting people, and answering "what are you up to?" forces a question you keep avoiding when left alone.

I had figured this out before I had a name for it. Hall calls this "following the weaker impulse." When you have had a hard day, and there is somewhere to be and every part of you wants to stay home, you notice that impulse and you go anyway. Not because you are disciplined in some grand sense, but because you have started to understand what that discomfort is actually doing for you.

Weddings where you know no one are a concentrated version of this. You cannot drift to a familiar corner. (Because there is none. Duh!) You have to engage, or you have a bad time2. And almost always, you end up having a better time than you expected.

I have had real conversations with a retired army man who was advising his niece to learn Java and AI, two people from startups who disagreed with each other about something I have now forgotten, and a local businessman who was quite busy with his weekend orders. I do not remember any of their names. I haven’t talked to them ever since.

But I remember all three of those evenings quite well.

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By nominal GDP, the city clocks in at roughly $150 billion, sitting comfortably behind Mumbai ($310B) and Delhi ($294B) and ahead of Bengaluru ($110B), Hyderabad ($75B), and Pune ($69B). Third place. Top three. Eastern India's undisputed anchor.

The problem is that nominal GDP rank rewards size. Kolkata has 15 million people. It has the eastern port, the rail hub, significant private sector presence in trade, finance, and services. The $150B is not fiction. But the question this series is asking is different: is that number growing fast enough, relative to the city's scale and potential? Is Kolkata punching at its weight, or below it? That’s what we will try to understand here.

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Adjust for Population. The Rank Collapses.

Kolkata's metropolitan area has roughly 15 million people. Compare that to Bengaluru (13 million) and Hyderabad (10 million). At those population levels, Bengaluru's $110B GDP yields a higher per-capita output than Kolkata's $150B. Hyderabad, at roughly two-thirds of Kolkata's population, is closing the aggregate gap faster than the headline numbers suggest.

I find the whole numbers game comparable to how India’s GDP is discussed. India, too, has the world’s 5th/6th (ranking is debatable now) largest economy. But just when you look at the per capita numbers, they change drastically. From 5th to 136th. The sum looks powerful; the distribution tells a different story. Kolkata's third-place rank works the same way.

The cleaner picture comes from looking at state-level per capita income, where official data is actually reliable. Delhi's per capita NSDP stands at ₹4.93 lakh. Telangana (Hyderabad's state): ₹3.87 lakh. Karnataka (Bengaluru): ₹3.80 lakh. Maharashtra¹ (Mumbai + Pune): ₹3.09 lakh.

West Bengal: approximately ₹1.7 lakh.

That is not a rounding error. West Bengal's per capita income is less than half of Karnataka's and less than a third of Delhi's. The third-richest city belongs to a state where per capita income sits well below the national average.

Which brings us to another deeper number. Kolkata is the only major Indian city whose share of the national GDP is smaller than its share of the national population.

CPR Insights

This is something worth imbibing. Mega (for India - we now use the term Mega instead of Metro) cities are the places where people move for “better” opportunities. That is to increase their earning potential. So ideally, for a mega city, you should have a population that is more productive. This is clearly not the case for Kolkata. Every other large Indian city — Mumbai, Delhi, Bengaluru, Hyderabad, Pune, Chennai — produces more than its population weight suggests it should.

And yet, Kolkata² is still carrying a slow-growing state.

The New Economy Test

The other way to measure a city's economic vitality is to look at where new wealth is being created: startups, venture funding, and knowledge economy jobs.

In 2024, Bengaluru saw 485 funded startup deals. Delhi NCR, 332. Mumbai, 231. Hyderabad, 56. Pune, 47. Chennai, 46.

Kolkata is not in that tier. According to Inc42's 2024 funding data, Kolkata is categorized alongside Ahmedabad, Jaipur, and Indore as cities with fewer than 100 total funded deals since 2014. It shows up in descriptions as a "regional innovation hub," which is the kind of phrase that sounds encouraging and means relatively little.

The Startup Blink 2024 Global Index places Bengaluru among the world's top 20 cities by startup ecosystem strength, with Hyderabad and Pune inside the top 100. Kolkata does not appear in the top 100.

Office leasing tells the same story more gently. Kolkata posted a 69% year-on-year growth in office space leased in 2025. The highest growth rate in India. But it absorbed 2.3 million square feet in a year that saw Bengaluru absorb 28 million. (For every 1 sq ft of office space that Kolkata absorbed in 2025, Bangalore absorbed 12) The growth rate is real. And a 69% yoy growth is worth acknowledging. But the base is small.

So: What Is Kolkata?

Kolkata remains the commercial and financial centre of eastern India. It is the eastern rail hub, the gateway to the northeast, the port that handles Bangladesh trade. It is not a hollowed-out city. It continues to have real economic activities.

But it is also a city that was built for a different India and has not fully adapted to the one that exists. Its rank at third in nominal GDP reflects both legacy and genuine activity, but the cities below it are growing faster in the things that compound. Some numbers are encouraging in this aspect, but they are far from being assuring. Kolkata needs more of that, and fast.

The state behind the city is the deeper issue. That is what the rest of this series covers: what decisions about industry, investment, and policy produced the numbers above, and what those numbers mean for the 100 million people who live in the state of West Bengal.

This is Part 1 of the West Bengal Election Data Series. Part 2 covers industrialisation, investment, and the long story of Bengal’s economic structure.

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Data sources:

• EAC-PM Working Paper WP/31/2024 — Relative Economic Performance of Indian States: 1960-61 to 2023-24 — link

• RBI — Handbook of Statistics on Indian States — link

• NITI Aayog — Macro and Fiscal Landscape of West Bengal (2025) — link

• Knight Frank India — India Real Estate: Office and Residential Market H2 2025 — link

• CPR India — Crudely Estimating Domestic Product for City-Regions — link

• Inc42 — Indian Tech Startup Funding Report 2024 — link

• StatisticsTimes — GDP Growth of Indian States — link

1 This deserves a separate deep-dive. Maharashtra, even after having two mega cities in Pune & Mumbai, is ranked 10th in the per capita income list for states.

2 What we call Kolkata here may differ from study to study. But directionally, it would yield similar results. Some studies would include the industrial belts of Howrah & Hoogly - while others may not.

This is the second piece in Grain of Data's West Bengal Election Data Series, looking at investment and industrialisation. Six comparison states: Gujarat, Maharashtra, Tamil Nadu, Karnataka, Telangana, and Odisha. Different models, different trajectories. WB's position among them is the story.

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Where capital goes

Foreign direct investment (FDI) measures the equity capital flowing into a state from overseas. Factories, technological partnerships, long-term investments, and acquisitions. It is not a perfect measure of economic health, but it is one of the cleaner signals of where large investors expect returns.

FDI is an imperfect proxy for investor confidence: it skews toward states with financial hubs (Maharashtra), IT ecosystems (Karnataka). But across five years, it tells a consistent story.

Maharashtra and Karnataka together absorbed the overwhelming share of India's state-level FDI between FY21 and FY25. The five remaining states split what's left, and WB's slice (hovering between $73M and $298M annually) is thin even within that group.

A few things to note before reading this chart cleanly.

Karnataka's FY22 spike to $22B reflects a surge in startup funding rounds (Byju's, Swiggy, Flipkart raises) classified as FDI equity. That capital was real and consequential for Karnataka's tech ecosystem. But it reads differently from the long-horizon manufacturing investment that drove Gujarat's FY24 numbers. Karnataka's FDI has moderated since, reaching $6.6B in FY25 as that funding cycle cooled.

Gujarat's trajectory is the more interesting one. From $1.9B in FY21 to $7.3B in FY24, driven by Micron's semiconductor plant and PLI-linked manufacturing investments. This is long-horizon capital, not startup equity rounds that can exit overnight.

Telangana's FY24 jump of $3B, up 132% year-on-year, was driven by Amazon and pharma manufacturing. A state that inherited Hyderabad's infrastructure in 2014 and has since built on it steadily.

West Bengal's FY25 figure of $298M is its highest in five years. That is a positive signal and deserves fair weight. In absolute terms, it remains at roughly 1.5% of Maharashtra's annual FDI inflow, and 4.5% of Karnataka’s. Almost insignificant in the chart.

Stuck between two models

Not all states are chasing the same economic destination, and FDI alone doesn't capture the structural picture. The chart below plots each state's agriculture share of GSVA¹ (Gross State Value Added) against its industry share, using FY2021-22 data from NITI Aayog's Macro and Fiscal Landscape state briefs.

Gujarat and Odisha sit in the top-left & the top-right: high industry, moderate-to-high agriculture. Both have grown their industrial base significantly. Gujarat at 49.3% industry GSVA is an outlier even among large states nationally. Odisha has taken a resource-and-steel path to a similar position.

Karnataka and Maharashtra sit in the bottom-left: low agriculture, low-to-moderate industry. Tamil Nadu is nearby.

Telangana sits closer to West Bengal than to any other state on this chart. Both carry higher agriculture shares and lower industry shares than their peers. They share a quadrant.

Both sit in the high-agriculture, low-industry quadrant. But Telangana's agriculture share has been declining as its economy grows. West Bengal's has not moved as decisively. High agriculture at 21.1%, comparable to Odisha. Low industry at 24%, comparable to Karnataka. The structural transformation, in both possible directions, is incomplete.

This is not a value judgment. These are the coordinates. What they mean is that WB's economy is organised around a different model, or more precisely, has not yet committed fully to any model.

Manufacturing's signal

Here is where the WB story gets counterintuitive. And it adds to the previous point.

18.8% of West Bengal's workers are employed in manufacturing. That is higher than Karnataka (10.4%), Maharashtra (12.4%), and Tamil Nadu (16.8%). On workforce share alone, WB looks like a manufacturing economy.

The scatter plots manufacturing workers as a share of workforce against manufacturing's share of GSVA. States above the 45-degree line get more output per worker than their employment share suggests: high-productivity manufacturing. States below get less.

West Bengal is below the line. 18.8% of workers in manufacturing, 13.3% of GSVA from manufacturing.

Gujarat sits well above. Gujarat's manufacturing workforce generates 37% of its GSVA from 23.8% of its workers. West Bengal's generates 13.3% of GSVA from 18.8% of workers. The gap in manufacturing productivity is visible even from these ratios.

The gap is explained by composition. 47.12% of West Bengal's informal enterprises are in manufacturing, the highest share in India (ASUSE 2023-24). West Bengal alone employs 40% of all women working in tobacco manufacturing nationally. Half of India's unorganised tobacco enterprises are in the state. The average registered MSME in WB employs 10 workers. For Telangana, that figure is 143.

WB's manufacturing is wide but shallow. Bidi, handloom, jute, cottage metalworks. These are industries with high labour intensity and very low value addition per worker. They show up in the employment data without showing up proportionally in output.

The manufacturing growth rate of 8.1% per annum over the last decade is real, higher than the national average of 5.5%. But it is occurring primarily in a thin formal layer on top of a vast informal base that has not been upgraded.

The formal economy that never scaled

The IT exports chart is the starkest in this series.

Karnataka exports ₹6.20 lakh crore in software annually. West Bengal exports ₹0.36 lakh crore. The ratio is roughly 17:1, with a state accounting for 2/3 of West Bengal’s population.

Kolkata had, and still has, credible inputs for an IT economy (as we can see - more than Gujarat & Odisha). Salt Lake Sector V and New Town have established IT parks. Real estate costs remain lower than Bengaluru or Hyderabad. The English-speaking graduate workforce is large. TCS, Wipro, and Infosys all have established presences.

The formal economy of WB (the organised manufacturing sector, the IT sector, the parts that generate corporate tax, attract large-scale private investment, and create salaried employment) has not grown fast enough to become the dominant story. West Bengal’s economy is disproportionately concentrated in sectors that are difficult to tax and difficult to attract large-scale private capital into: informal manufacturing, low-productivity services, and agriculture.

What the data says

The four charts tell one consistent story - if we examine closely.

Capital flows to Maharashtra and Karnataka at a scale West Bengal has not approached in any recent year. The structural position shows an economy carrying high agriculture and low industry, having not moved decisively toward either an industrial or a knowledge-services model. Manufacturing employment is large but productivity per worker is low, concentrated in informal micro-enterprises rather than factory-scale production. And in the formal knowledge economy, the gap with the leading states is not narrow.

None of this makes West Bengal a failing economy (at least, yet). Its manufacturing is growing faster than the national average. Its FDI is at a five-year high. It absorbed ₹4,416 crore in central capital investment loans, the fifth highest among all states. The public sector capacity and willingness to invest is present.

What is less present is the private sector conviction that follows. The investment data, the structural position, the manufacturing productivity gap, and the IT export numbers all point in the same direction. West Bengal is a large economy organised around sectors that are hard to scale, hard to tax, and hard to attract large-scale private capital into.

That is where things stand today. Whether the next decade changes the composition is an open question.

The next piece in this series looks at health parameters.

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Data Sources:

• Sectoral GSVA shares from NITI Aayog Macro and Fiscal Landscape state briefs (2025), based on MoSPI data for FY2021-22.

• FDI figures from DPIIT quarterly factsheets; some FY21-23 figures are approximate.

• Manufacturing workers from PLFS 2022-23 via NITI Aayog briefs.

• IT exports from STPI and SEZ official data, FY2023-24.

• MSME firm size from DC-MSME Udyam Registration Bulletin. Informal enterprise share from ASUSE 2023-24 via Factly.

1 GSVA (Gross State Value Added) is the total value of goods and services produced within a state, after subtracting input costs. Think of it as the state's contribution to national output. If a factory in Gujarat buys ₹60 worth of raw materials and sells output worth ₹100, it adds ₹40 to Gujarat's GSVA. It is the primary measure used to calculate GSDP.

Let's first define what is what.

Means are simple. Let's assume you are building a product feature. A good, solid software feature. The feature can be anything. Adding a search to your website, redesigning the old homepage, or creating a new category in the e-commerce app. The feature adds business value. But it doesn't use any GenAI. In this case, we are using GenAI just to write the code. This is treating GenAI as a means. It is just a tool in the background. The user would never know if the feature was built using Cursor or Claude Code.

What is GenAI as an end product? In this scenario, you are not only using GenAI to write the code, but the core product offering also has an embedded GenAI feature. For example, it can be a GenAI-powered data analyst, a document generator that generates documents for clinical trials, or a text-to-SQL converter. For these use cases, you are not merely using language models for coding. The core offering itself includes these capabilities as the end product.

Let me give you a concrete example. At my previous organisation, we built a document generation tool for scientific writers. The underlying feature was a language model stitching together structured data from different specified sources and free-text summaries into a draft document. A researcher would review and edit, but the first draft came from the model. That is GenAI as the ends. The model's output was the product. If it hallucinated a dosage or misread a table, that was not a bug in the background. That was the product failing. And it used to happen.

When we are using GenAI as a means, and when we are deep into the productivity debate, there is an implicit assumption that LLMs or SLMs can produce many lines of code, very quickly. That is absolutely true. And for most cases, the output remains unchanged (the feature would have been there even without GenAI), so there can be a productivity bump, if it is being used correctly.

But for the rest, it will hardly be the case. What I see, read, and hear is that people treat everything as GenAI as the means, even when the company or the team is building AI-native features. Shipping a text-to-SQL product is not the same as shipping a search bar.

Once you start looking, this misframing shows up everywhere. A LinkedIn post celebrating "we shipped 10x faster" rarely specifies what was shipped. Similarly, productivity metrics like lines of code or tickets closed don't distinguish between a team that used Copilot to build a payment flow and a team that shipped an AI-native feature on top of an LLM. The numbers look the same. The problems are not.

On this, another important note is prototyping and production.

Prototyping has become easier for both cases. For sure. If I had to give a demo to stakeholders using Streamlit or Shiny, it would take at least a week to build the minimum viable product. Lots of back and forth on Stack Overflow, Googling and whatnot. Now it often takes a day of intense prompting. Most companies have tie-ups with different organisations, so you get almost unlimited tokens and a huge context window.

Similarly, even when your core product offering is GenAI-embedded, you will have it easier to prototype. One or two solid SQL use cases, and you are done building the prototype.

Productionising is a different beast altogether. And the degree of difficulty increases here, too. When the core offering is a GenAI-driven feature, the relative increase in difficulty will be very, very high compared to when you are using it just as a coding agent. You now have a model that hallucinates, behaves differently across prompt variations, and has different token length requirements for different use cases. You need better evaluation frameworks to gauge the model's performance. You need to think about what happens when the model is confidently wrong and a user acts on it. None of this has a clean engineering solution (yet). Most of it does not show up in the prototype at all.

The slope chart above is not precise. The numbers are illustrative. But the shape of it is right: the two lines start close and end very far apart.

The next time someone shares a productivity stat about GenAI, it is worth pausing for a second. Which kind of productivity? A coding assistant helping ship a search bar is a real gain, no argument there. But if the product itself runs on a language model, the prototype was never the hard part. It has never been easier to build one. That is also, unfortunately, the easiest part of the whole lifecycle.

Kant warned against treating ends as merely means. He was talking about people. But the pattern, as it turns out, is not limited to philosophy.

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Which is probably why hollow praise irritates me as much as it does.

I was having a chat with a very distant acquaintance (The husband of a friend’s friend). It went political very quickly. There were huge praises for the current regime. Apparently, everything is quite smooth now in India. We have ‘honest’ people working in the bureaucracy. The previous regime was full of corrupt officials and politicians. I nodded. Within 10 mins, I came to know that he is planning to leave the country pretty soon. He will be settling in the USA, at least for the next 10 years, with his spouse. In Texas.

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There’s a particular kind of frustration that doesn’t have a clean name. It shows up when someone posts “India is rising” from their apartment in New Jersey, or writes “Joy Bangla” from a flat in Gurgaon. I’ve felt it plenty of times and never been able to fully articulate why it bothers me.

It isn’t envy. It’s something closer to a credibility problem. Which ties it back to the point of hollow appreciation.

If the government is genuinely doing a great job, the most obvious vote of confidence you could cast is to live under it. To use its roads, breathe its air, send your kids to its schools, get sick in its hospitals. Praise from someone embedded in the consequences of governance is, at minimum, an informed opinion. It is genuine. Praise from someone who has already left is a bit like a restaurant critic writing glowing reviews from a country that doesn’t serve that cuisine.

There’s a political science framework that explains this cleanly. Hirschman’s Exit, Voice, and Loyalty: when institutions (like your country or state) fail you, your options are to exit (leave), voice your dissatisfaction (engage, push back), or show loyalty (stay and absorb it). Most emigrants have chosen exit. Cheering from abroad is loyalty without the burden of staying. Combining the worst of two worlds.

Sanjaya Baru, the economist and former media advisor to ex-PM Manmohan Singh, has a term for this. He calls it performative nationalism (don’t think he has coined it). In his recent book and interviews, he points to a specific irony: the same diaspora that fills Madison Square Garden and Wembley to chant “Bharat Mata Ki Jai” (“Glory to Mother India”) accounts for 1.8 million citizenship surrenders since 2014. They praise India loudly, and then formally, legally, permanently exit it.

(Here is a clip from one of his interviews; the full interview is also worth a watch)

If anything, distance is meant to create objectivity. You’ve seen how other governments operate. Fine. But if that comparative clarity has genuinely convinced you that India is doing well, the logical next step is to return. Yet they aren’t. Because they’re in Canada, not Cuba.

That’s the thing. The praise costs them nothing 1. They are cheering from the outside.

It isn’t that NRIs can’t have opinions about India, or Bengalis outside Bengal can’t care about West Bengal. Of course they can. But there is a difference between “here is my concern from the outside” and “everything is great, keep it up.” The former requires engagement. In a way, it is actually quite authentic; you are worried about your people, even after leaving your city-state-country. You think about them, you are up to date. The latter requires nothing except a good wifi connection and some ambient nationalism.

None of this is about vilifying someone for leaving their state or country. For hundreds of years, people have been moving from cities with fewer opportunities to ones where there is a relative abundance. It is natural to outgrow a place. Your city. Your state. Your country. The problem isn’t the leaving. It’s the cheerleading that follows, often directed at the very institutions that couldn’t hold you.

Praise from someone who could leave but stayed means something. They’ve seen the alternative and decided to remain. That skin in the game gives the endorsement weight. Praise from someone who left tells you, at best, that they feel nostalgic. At worst, that they need the identity without the inconvenience.

Put your money where your mouth is, or at least your postal address.

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Leave a comment below. I’d love to hear from those who stayed, those who left, and those who are currently packed and ready to go.

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“Oh yeah! I don’t think their approach is gonna work.” - I replied.

“Then, why didn’t you say anything?”

“I didn’t think it was my place to point that out, and they didn’t seem to be taking any feedbacks.”

He nodded and walked away. I am not sure if he was impressed or just done with the conversation. I didn’t ask.

This was a pattern in my early days. Cross-departmental meetings, internal reviews, and even casual conversations where someone said something obviously wrong. I would notice. I would say nothing. I would walk out and process it alone.

I would cross-check reports five times before sending. (We didn’t have GenAI to do that.) No typos. Everything is in place. Not because anyone asked me to, but because I was quietly terrified of being ‘found out’.

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There is a formal name for this, as it turns out. You guessed it right.

During COVID, I used to go out for an afternoon walk/run in a nearby park after 4. One day, I went out. Just when I reached the park and was about to start the run on Strava, I saw my manager had messaged: “We can connect whenever you are free”. I panicked a bit, even though there was absolutely no reason. My manager was quite chill in these cases. I ran my fastest 1k (~5:50 min). I was panting like a thirsty dog. And came back home in 15 mins.

This imposter syndrome also had a positive side. It made me focus on work a lot more. I would push the limits regularly. It was tiring. But it was effective. That low-grade anxiety made me careful. It made me listen. I learned a lot because I assumed I didn't know enough (which should be the default mode anyway).

Then, something quietly started changing. The change wasn’t like a sudden cloudburst, but rather like a slow sunrise.

As my career progressed, I started interacting with different people. I sat through many meetings, many inefficient ones, and my point of view about myself changed. There have been so many meetings where I would hear a director or VP say something ridiculous and leave the room thinking, “Man! These guys have no idea at all.”

I started doing the math. And the math was oddly comforting.

If they have a job, I thought, I will definitely have a job1. If they are senior, I can be senior. If that passes review, mine will certainly pass review. It is a reasonable inference on paper. In practice, it makes you sloppy.

These interactions changed my perspective. From being an imposter, I started becoming overconfident. There have been assignments where, instead of being super focused, I started coasting. Chilling - if you will. And that resulted in subpar outputs.

The problem with imposter syndrome is that you let your fear do the thinking. You catastrophise, you shrink, you over-prepare for things that didn't need that much preparation. But the problem with its opposite, being overconfident, is that you let your comfort do the thinking. You stop treating the problem in front of you as a problem. You treat it as a formality.

What I am trying to do now is simpler, and harder. Treat each assignment like it deserves attention. Not because I am scared, not because it is easy, but because I am getting paid to do it well and it is in front of me right now. That is a sufficient reason.

I don't know if I have solved this. The pendulum still swings, but less often. And less drastically. I still walk into some rooms feeling like a fraud and some rooms feeling like I'm doing everyone a favour by showing up. Neither is accurate. Both are, in their own way, a distraction.

The problem does not care about my relationship with my own competence. Which is, honestly, a relief.

The Karnataka 2023 assembly election was the Zepto moment in Politics. Let me elaborate on what I mean by that.

For the uninitiated, Zepto is a quick commerce company in India. They started their business in 2021 with a radical promise - 10-minute grocery delivery. When they started, India already had some quick commerce players who were relatively slow (~30-45 minutes). Zepto were aggressive with their promises.

At that time, some existing players like Big Basket shrugged them off completely. Big Basket had a model where you would order groceries and they would be delivered the next day. In a selected 4-hour slot. They were adamant that Zepto’s model wouldn’t last. Unscalable, they said. Other companies like Swiggy Instamart, and Blinkit did some retrospection and started adapting slowly.

Fast-forward to 2026, the 10-minute delivery market - though, now, it can’t quite be called that - is thriving. Big Basket still does slot-based deliveries. But they now also deliver iPhones in 10 minutes. They have accepted, quietly, that what they did initially was a mistake of some sort, and had to adapt.

The 2023 Karnataka elections made headlines in a similar fashion. The main opposition at that time - Congress - announced a bucket of schemes which grabbed the headlines. Free bus rides for women in public buses, free electricity up to a certain limit, and more. The incumbent BJP government called it freebies. “Revdi culture,” the PM said - revdi being a traditional North Indian sweet, the phrase was his way of calling these promises empty handouts, distributed for votes the way sweets are distributed at festivals. He doubled down on this framing across multiple campaigns, including in the 2021 Delhi election. The message was consistent: you cannot make systematic progress with these policies.

Congress won the 2023 Karnataka election with a thumping majority.

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Then came Delhi’s election in early 2025. At rallies in Rohini and RK Puram, the PM assured voters that not a single existing welfare scheme - the same free electricity, the same free bus rides - would be discontinued if the BJP came to power. The then-ruling CM of Delhi, Arvind Kejriwal, not without some glee, called it an acceptance of their model. The word “revdi” didn’t come up. ¹

Delhi is not a single case. In Maharashtra’s 2024 election, the competitive bidding reached almost comedic levels. The ruling Mahayuti’s Ladki Bahin scheme started at ₹1,500/month for women. The Congress-led MVA countered with ₹3,000. Mahayuti then revised their own promise to ₹2,100. Both alliances were simultaneously promising farm loan waivers, youth stipends, senior citizen pension hikes - each announcement timed within days of the other. ² And within days of actually winning on the back of Ladki Bahin, officials quietly began reviewing whether the state could afford it. ³ In Madhya Pradesh, Bihar, wherever there was an election, similar optics followed.

There are two things worth sitting with here.

One is that welfare schemes are not inherently bad. A large portion of the country is still below the poverty line, and direct cash transfers can be meaningfully helpful. Development economists like Jayati Ghosh argue that basic welfare - free water, food, electricity - isn’t a freebie but a human right, with real downstream gains in productivity and consumption. The government’s own Economic Survey 2024-25 found that welfare schemes are narrowing the urban-rural consumption gap, with the bottom deciles seeing the highest expenditure growth. ⁴ That’s not nothing.

The other thing is the motive. Means & ends. The RBI has flagged repeatedly that states with revenue deficits are spending over 20% of their revenue expenditure on subsidies, crowding out capital investment. The Supreme Court, as recently as February 2026, called it a “culture of freebies” and a threat to fiscal stability. ⁵ There’s a difference between a welfare scheme designed to help people and one designed to be announced before an election. The trouble is that from the outside, they look identical. And everyone - voter, journalist, economist - has largely stopped pretending otherwise.

We are seeing something similar in quick commerce. Swiggy’s Instamart and Blinkit are both burning significant cash - expanding dark stores, subsidising deliveries, fighting for market share in what analysts have called a “land grab” phase. ⁶ Zepto, the category-defining player, hasn’t been publicly listed, so its finances remain opaque - though a confidential IPO filing in late 2025 may change that soon. ⁷

Instead of organising the quick commerce space more efficiently, the players are doubling down on speed. Just as the political parties are doubling down on poll promises, rather than directing spending to where it is more structurally needed.

When will it end? In quick commerce, I think the practices will slowly converge. Most orders already arrive after 10 minutes. It will probably settle somewhere around 20-30 minutes, which is operationally far more sustainable. SKUs will be reduced. A hub-based model may emerge for costlier items - you can get an iPhone in 3 hours, not 20 minutes. The companies have a clear reason to get there. They need to make money for their shareholders, and reality has a way of asserting itself.

That pressure doesn’t exist for politicians. The Karnataka moment showed everyone - across party lines - that welfare schemes win elections. Big Basket saw the demand and adapted. Every political party saw the result and adapted. The difference is that Big Basket’s pivot will eventually have to pencil out. The political pivot has no such requirement.

I don’t see this changing unless the policy conversation succeeds in making it costly - not morally, but practically - to promise schemes without funding plans, without sunset clauses, without any accountability for what happens after the votes are counted.

Or unless voters start asking for different things. More roads. Better schools. Institutions that work. That’s a slower, harder kind of politics. But it’s the only version where the incentive actually changes.

NOTE: I am a product & policy observer. Views are personal and do not reflect those of any organisation that I am a part of.

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Footnotes

¹ Modi at Rohini rally, Jan 5 2025 - Business Standard; BJP wins Delhi - Business Standard, Feb 8 2025

² Maharashtra 2024 election - Wikipedia; Maharashtra party manifestos - Marksmendaily, Nov 2024

³ Mahayuti mulls tweaks to Ladki Bahin scheme - Business Standard, Nov 26 2024

⁴ Economic Survey 2024-25 on welfare schemes - PIB; Freebies vs welfare debate - Outlook India

⁵ RBI State Finances report analysis - Ideas for India; Freebies and Fiscality - Millennium Post, Feb 2026

⁶ Swiggy Instamart losses - Bloomberg, May 2025; Swiggy in 2025 - Inc42

⁷ Zepto confidential IPO filing - CNBC, Dec 2025

So, I did that. I visited the Kolkata Book Fair, almost after 8 years. Here is the ordinary analysis of everything that I witnessed.

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It was a Sunday. I reached the “Boimela Prangon” (The Book Fair Ground) around 6 PM. There was a huge deployment of police in that area, and the car was stopped well before it could take the U-turn to the gates. It felt a bit off that they were stopping vehicles so far ahead. Judging from the outside, I didn’t find it too crowded. I was proven very wrong quite soon.

When I entered through Gate number 4, it was packed. There was a distinct smell of fish and chicken coming from the food stalls. Won’t lie, that was quite appetising. I moved on to the first stall. Starmark by Emami. I don’t know why I entered that stall. It was just the nearest one, so I thought, “heh! Why not?” The stall had mostly acclaimed fiction and non-fiction.

I didn’t have any particular book in my mind before visiting. I thought I would explore different stalls, and if I liked any titles, I would buy them. There were 2-3 books I was planning to buy from Amazon anyway: Thinking, Fast and Slow, The Myth of Sisyphus, Meditations, etc. So if they were available in one of the stalls, I would go for them.

In the 2nd stall, I found Meditations. Picked it up casually. Was happy. Then something happened, and I remembered the saying of one of my uncles who used to advise us not to buy books from the Book Fair as they are ‘very costly’. I noted the price and checked online. Almost 3x. I quietly put that book down and continued my window shopping.

After that, I came near the Penguin Random House stall. It was crammed with people. They were trying to maintain a peaceful ambience inside. So there was a huge queue outside, people being let in in batches. Needless to say, I am not a fan of crowds (unless it is in a football stadium). So I decided to skip it altogether. But for some reason, it made me happy. That so many people are lining up to enter a store full of books.

I was thirsty at this point. The only stalls selling water were the food stalls, and they were unbearably crowded. 10x more than the Penguin House. So I had two choices: stand in the queue for a water bottle, or bear the thirst. I opted for the latter. Happily.

I continued my sojourn. Every year, the Kolkata Book Fair has a country theme. This year’s was Argentina. They had a few snippets about the country and some books written in Spanish. As usual, I understood nothing. I was wandering at this point. Aimless wandering is not bad, to be honest. In a mela, you need to do this kind of exploration. And then I saw two counters, radically opposite in both position and probably what they preach, giving out the Quran and the Bible. For free. Mostly, these stalls were empty. The Brahmo Samaj stall, which I came across soon after, was also like that. Empty.

Then I came across the country-specific sections, where mostly the representatives of different embassies have their stalls. Generally, there is a buzz around the stalls of the US, Russia, France. This year, for the first time in almost 20 years, the USA decided not to participate, while China returned after 15 years. Our ‘friendly’ neighbour, Bangladesh, also skipped twice in a row. Ukraine was a surprise debutant this time. But their stall was empty. There were a few participants in the France stall.

Announcements were going on thanking the CM for her help and cooperation. Which irked me a lot. But apparently that is the theme now. Be it the CM or the PM.

Then I came across the section of news publishers. The Times of India had something cooking. I couldn’t understand what or why, but people were lining up to get a book. Ei Somoy, a famous Bengali newspaper, had someone discussing something in Bengali. There was a stall for The Week also, which I found interesting. I didn’t know they were that big.

Now, the main part. Until this time, I had almost forgotten about the two big players of the book fair: Ananda Publishers (owned by the ABP Group) and Patra Bharati. We used to line up for these stalls. And most of our books would come from these two alone. Judging by the 100+ metre long curly queues at both, I would assume that this trend hadn’t changed. At all. The length of these two queues made the penguin one look quite puny.

It was almost 7:15. I was thirsty. I decided to call it a day. Left the premises. Crossed the road. I didn’t buy any books. But the nostalgic memories were well fed.

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But that wasn’t the only binary that existed. Cultural binaries are huge. And I think every regional culture has them.

For example, in West Bengal, we had many. Some were Bengal-specific, others pan-Indian. Sachin vs Saurav, Lata vs Asha, Soumitra vs Uttam, East Bengal vs Mohun Bagan, Amitabh vs Rajesh Khanna, Beatles vs Stones, Kishore vs Rafi, Saurav Ganguly vs Rahul Dravid 1 (this probably deserves a separate blogpost). I grew up in the middle of some, while others were blasts from the past.

One such socio-political binary that we believed in, and to some extent were taught too, was Gandhiji (and Nehru) versus Netaji.

23rd January was Netaji’s birthday. When I opened social media and scrolled through some statuses, I noticed many instances where people will claim him as the “First PM of India” or “The Father of the nation”, as usual. The current regime started propagating this belief relatively recently; Bengalis have been saying this for decades.

For example, I received this WhatsApp forward on 22nd January, this year too.

It reads: “Tomorrow, I will be abused again”

Anyways, the bigger point is: we are taught history as black and white. Obviously, we had many heroes and villains. If you conduct genocide, you can’t be called a hero. There’s no grey area there. But for most other cases, there is a huge grey area. And we are hardly encouraged to explore that.

Did Gandhi’s non-violence prolong British rule and cost lives? Did Netaji’s alliance with Axis powers compromise moral standing for tactical gain? These aren’t comfortable questions, but they’re necessary ones. But we are never encouraged to ask or analyse these.

The essays we wrote were hardly analytical; mostly we memorised facts and vomited them. My home tutor in classes 9-10 did a great job avoiding that. He would highlight what was happening in Europe, and how India was getting affected. But at the end of the day, the questions were not like that. So, we were not expected to have an analytical lens there.

The examination system doesn’t just fail to reward analytical thinking. It actively punishes it. Every mark you spend constructing an argument is a mark you don’t spend vomiting the ‘facts’ from the textbook.

This kind of teaching benefits no one. And it helps the ruling party immensely (irrespective of the party). They get to set the tone. Invent their own heroes and villains. Rather than analysing the motive of the past characters, we just label them as evil or god. And we are not encouraged to debate about their motives, incentives and overall character.

This is also prevalent in science, but not to this extent. You can mug up some formulas and answer some questions. But most of the science stuff requires you to know the logic of the formula as well.

This matters beyond academic interest. When we can’t analyze historical trade-offs, we can’t evaluate contemporary ones either. The same binary thinking that turns Gandhi into a saint or a sellout is what reduces every policy debate to patriot vs traitor.

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There has been an ongoing debate about gig work in Indian public policy circles. It entered the mainstream when AAP MP Raghav Chadha raised the issue in Parliament 1. I remember having an involuntary eye-roll moment then. Give me a break.

Lakhs of people have joined gig work in India, not because it is aspirational, but because there are no better alternatives available. This is the best one can do in a weak job market. Imagine what they would be doing without the gig work? And if we are being honest, politicians and policymakers have collectively failed to create more stable employment opportunities in the first place.

Since then, the issue has resurfaced multiple times, most prominently during the nationwide protest on 31st December. I have read articles, listened to podcasts, and consumed viewpoints across the spectrum. But after skimming through all of that, I kept coming back to one uncomfortable conclusion.

Most Indian gig platforms preserve the risk of gig work but quietly erode the freedom that defines it. In effect, they combine the worst of two worlds. And this aspect has not been discussed nearly enough.

Before going further, a few words on what gig work is supposed to mean.

Gig work does have genuine benefits. It has a low entry barrier. It allows people to participate in the labour market quickly. And, most importantly, it promises autonomy over when you work and what work you accept. This was discussed at length in an episode of Everything Is Everything, where Amit Varma and Ajay Shah unpacked the economic logic behind gig work2. I will not go into depth here. But this is a fantastic episode to listen to.

Another excellent piece was written by Fahad Hasan, who explored why gig work exists, the value it creates, and the reasoning behind recent boycott calls and why it was misguided3.

Most debates I have seen fall into two buckets. Either moral binaries of good versus bad, or thoughtful analyses of why the gig economy emerged and what problem it solves.

But my concern lies elsewhere.

Is India’s gig economy actually gig?

Consider this example. Soumyarendra Barik, a journalist with The Indian Express, worked as a delivery partner for three days to understand worker pain points 4. After rejecting four orders, his account on Swiggy was blocked for a significant duration. On Zomato, his ID was disabled for fifteen minutes. The apps even use oddly stressful notification sounds when an order is not accepted, according to him.

In another podcast report, a gig worker described how his ID was disabled simply because he took a lunch break.

These were genuine WTF moments for me. Not because they were shocking, but because they strike at the very definition of gig work.

If I am a gig worker, I should have the autonomy to decide when I work and which work I accept. That autonomy is not a nice-to-have feature. It is the defining feature of gig work. If rejecting three or four orders leads to penalties, throttling, or account suspension, then in what meaningful sense is this a gig?

In permanent jobs, control is explicit. There are fixed hours, structured responsibilities, and KPIs to meet. In return, there is security, predictability, and benefits.

What we seem to have built instead is a system that borrows the control mechanisms of permanent employment and combines them with the insecurity of gig work.

And it is why I think we need far more honest and different conversations.

The current debate asks: ‘How do we protect gig workers?’ But that assumes they are gig workers. The evidence suggests otherwise.

Real gig work, where workers genuinely choose when and whether to work, has meaningful benefits.​​​​​​​​​​​​​​​​ But when you penalize workers for declining orders, disable accounts for lunch breaks, and throttle access for assertion of choice, you are not running a free marketplace. You are essentially managing employees.

Either give workers genuine autonomy (the ability to say no without algorithmic punishment) or classify them as employees with corresponding protections. What we have now isn’t a compromise or an imperfect equilibrium. It’s the worst of both worlds: the insecurity of gig work combined with the subordination of employment.

This is not gig work. It’s the employment relationship stripped of obligations.

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