Immigrant Founder

Fintech / Analytics / Proof of work /long BTC / long India / long US innovation

[Immigrant Founder @Immigrant_in_us]

@Nithin0dha @harshmadhusudan @rajan0611 finally

[Nithin Kamath @Nithin0dha]

I've spoken many times about the need to make it easier for NRIs to invest in India. Finally, some great news. SEBI just released a consultation paper proposing a fully digital onboarding process for NRIs, without needing them to be physically present in India! Kudos to SEBI for this pragmatic move.

This is huge because NRIs tend to have large amounts of capital to invest and are a highly durable source of inflows into Indian markets. At @Zerodha, we have over 50,000 NRIs investing with us today. A stat that surprised me when we looked at our numbers: ~80% of them are active. That's a ridiculous number. They tend to invest more, take a longer-term view, and seem to be much stickier investors than regular investors.

This number has grown a lot over the last few years, mostly because the process got simpler. SEBI's earlier changes meant NRIs no longer needed the whole PIS setup to invest. Most NRIs now come in through NRO Non-PIS accounts. These accounts work almost like resident accounts today, with intraday, BTST, and F&O access, and no CP code needed.

But one massive bottleneck has remained: onboarding.

Even today, to open an account digitally, an NRI has to be physically in India. If they are abroad, there's a ton of physical documentation involved and dealing with international courier delays. It has always been the most painful part of the journey.

SEBI’s proposals in the new consultation paper fix this longstanding gap. They’re proposing allowing e-signs directly from the client's country of residence. If finalized, this would relax tedious documentation rules and delays. Something that would take 2-3 weeks or even months could be done within 1-2 days. That's a big win. By removing all this friction, this investor base can easily be many times larger.

Getting foreign money into India matters. It helps the investors, but it also helps the rupee and the larger India story. Anything that makes it easier for this money to come into India is worth doing.

[Johann Kurtz @JohannKurtz]

https://t.co/TqtDrW0D8X

[Immigrant Founder @Immigrant_in_us]

@harshmadhusudan Good point - especially when the ROI on that Mag7 capex is unclear to negative, and capex of one is revenue for the other (circular loops). Can unwind as easily as the built up.

[Immigrant Founder @Immigrant_in_us]

@harshmadhusudan Couldn’t agree more - what’s your view of obvious 5 low hanging fruits that govt could go for? To me, opening a Zerodha account as an NRI was 30+ days - and involved mailing physical documents to Bangalore. I did it anyway - but know many who don’t invest just because of that.

[Nithin Kamath @Nithin0dha]

One thing that feels under-discussed in all the conversations about attracting foreign capital into India is the Indian diaspora.

There is a large population of NRIs who are emotionally and financially interested in investing in India. But today, for many of them, the process of opening accounts, completing documentation, and actually investing in Indian markets is still far more painful than it needs to be.

Making life easier for NRIs could be one of the lowest-hanging fruits for attracting long-term capital into India.

This is something we’ve been focusing on heavily at @zerodha as well. Over the last year or so, we’ve made several changes to make investing as seamless as possible for NRIs. But there are still many frictions that exist because of regulatory and compliance requirements.

Hopefully, SEBI and the government look at this more closely and think about how to make it easier for NRIs to bring money into India and participate in Indian markets. For a country trying to attract global capital, the Indian diaspora seems like the most obvious place to start.

[Andrew Ng @AndrewYNg]

AI-native software engineering teams operate very differently than traditional teams. The obvious difference is that AI-native teams use coding agents to build products much faster, but this leads to many other changes in how we operate. For example, some great engineers now play broader roles than just writing code. They are partly product managers, designers, sometimes marketers. Further, small teams who work in the same office, where they can communicate face-to-face, can move incredibly quickly.

Because we can now build fast, a greater fraction of time must be spent deciding what to build. To deal with this project-management bottleneck, some teams are pushing engineer:product manager (PM) some teams are pushing engineer:product manager (PM) ratios downward from, say, 8:1 to as low as 1:1. But we can do even better: If we have one PM who decides what to build and one engineer who builds it, the communication between them becomes a bottleneck. This is why the fastest-moving teams I see tend to have engineers who know how to do some product work (and, optionally, some PMs who know how to do some engineering work). When an engineer understands users and can make decisions on what to build and build it directly, they can execute incredibly quickly.

I’ve seen engineers successfully expand their roles to including making product decisions, and PMs expand their roles to building software. The tech industry has more engineers than PMs, but both are promising paths. If you are an engineer, you’ll find it useful to learn some product management skills, and if you’re a PM, please learn to build!

Looking beyond the product-management bottleneck, I also see bottlenecks in design, marketing, legal compliance, and much more. When we speed up coding 10x or 100x, everything else becomes slow in comparison. For example, some of my teams have built great features so quickly that the marketing organization was left scrambling to figure out how to communicate them to users — a marketing bottleneck. Or when a team can build software in a day that the legal department needs a week to review, that’s a legal compliance bottleneck. In this way, agentic coding isn’t just changing the workflow of software engineering, it’s also changing all the teams around it.

When smaller, AI-enabled teams can get more done, generalists excel. Traditional companies need to pull together people from many specialties — engineering, product management, design, marketing, legal, etc. — to execute projects and create value. This has resulted in large teams of specialists who work together. But if a team of 2 persons is to get work done that require 5 different specialities, then some of those individuals must play roles outside a single speciality. In some small teams, individuals do have deep specializations. For example, one might be a great engineer and another a great PM. But they also understand the other key functions needed to move a project forward, and can jump into thinking through other kinds of problems as needed. Of course, proficiency with AI tools is a big help, since it helps us to think through problems that involve different roles.

Even in a two-person team, to move fast, communication bottlenecks also must be minimized. This is why I value teams that work in the same location. Remote teams can perform well too, but the highest speed is achieved by having everyone in the room, able to communicate instantaneously to solve problems.

This post focuses on AI-native teams with around 2-10 persons, but not everything can be done by a small team. I'll address the coordination of larger teams in the future.

I realize these shifts to job roles are tough to navigate for many people. At the same time, I am encouraged that individuals and small teams who are willing to learn the relevant skills are now able to get far more done than was possible before. This is the golden age of learning and building!

[Original text: https://t.co/1pUxNC5UXk ]

[Michael McNair @michaeljmcnair]

Gold and silver are not acting well in a period of rapidly rising geopolitical risks. We have an Iran War, Strait of Hormuz blockade, rising volatility. In the old framework, that setup should be close to ideal for gold. But once you understand what is now driving gold, this move makes perfect sense.

Something fundamental changed after the US and Europe froze Russian reserves in 2022. For decades, surplus countries parked their excess savings in US dollar assets, mostly Treasuries. The freezing of Russian reserves combined with the current administration's explicit push to discourage foreign countries from parking excess savings in US financial assets, forced surplus countries to rethink where they store reserves.

And those countries haven't changed their domestic policies that generate the excess savings, so those savings have to be placed somewhere. The result is that gold and silver have increasingly become the obvious “neutral” reserve assets.

That’s why gold decoupled from the three factors that used to explain it…real interest rates, volatility, and liquidity. Now reserve accumulation flows have become the primary driver.

That shift has a consequence I don’t think most investors have thought through. If gold is now primarily driven by reserve flows from surplus countries, then gold has become pro-cyclical.

Reserve growth is driven by export revenues, trade surpluses, economic growth in surplus economies. When the global economy is strong and surplus countries are generating large export revenues, their excess savings grow, their reserve accumulation accelerates, and gold catches a bid. When that surplus generation is disrupted, the bid weakens or reverses.

This is exactly what is happening with the blockade of the Strait of Hormuz.

The GCC countries are major reserve/gold buyers and now their export revenues are collapsing. They likely need to liquidate some reserves to cover fiscal obligations, and gold is one of their most liquid assets. Even if the reserve sales aren’t excessive yet, the market can see their reserve accumulation has stalled and probably reversed. That flow, which was a meaningful source of gold demand, has gone to zero at best.

There are also secondary effects on other surplus economies. China is the world's largest oil importer. An energy shock of this magnitude slows Chinese growth, and compresses Chinese surpluses, which slows Chinese reserve accumulation. That same growth shock ripples through Korea, Taiwan, Japan, and the rest of Asia.

The whole chain that has been driving gold higher, surplus countries generating excess savings that need a home outside the dollar system, is being disrupted by an event that in the old model would have been unambiguously bullish for gold.

This doesn't mean the structural case for gold is broken. The dollar standard is still ending. Surplus countries still need an alternative to Treasuries and gold is still the most obvious destination. But it does mean gold is going to be more volatile along that structural trend than most people expect, and the volatility will correlate with global growth and surplus generation rather than with the old drivers. Gold rallies when surpluses expand. Gold sells off when surpluses contract. Even if the reason for the contraction is rising geopolitical risk that, under the old model, should have sent gold to the moon.

[Pratyush @pratyushbuddiga]

Whenever this cycle ends, the Citrini “report” will be an extremely funny relic of the mania like a Bored Ape or Peloton’s stock chart.

The DoorDash analysis is a third grader’s understanding of marketplaces.

[Andrew Ng @AndrewYNg]

Job seekers in the U.S. and many other nations face a tough environment. At the same time, fears of AI-caused job loss have — so far — been overblown. However, the demand for AI skills is starting to cause shifts in the job market. I’d like to share what I’m seeing on the ground.

First, many tech companies have laid off workers over the past year. While some CEOs cited AI as the reason — that AI is doing the work, so people are no longer needed — the reality is AI just doesn’t work that well yet. Many of the layoffs have been corrections for overhiring during the pandemic or general cost-cutting and reorganization that occasionally happened even before modern AI. Outside of a handful of roles, few layoffs have resulted from jobs being automated by AI.
Granted, this may grow in the future. People who are currently in some professions that are highly exposed to AI automation, such as call-center operators, translators, and voice actors, are likely to struggle to find jobs and/or see declining salaries. But widespread job losses have been overhyped.

Instead, a common refrain applies: AI won’t replace workers, but workers who use AI will replace workers who don’t. For instance, because AI coding tools make developers much more efficient, developers who know how to use them are increasingly in-demand. (If you want to be one of these people, please take our short courses on Claude Code, Gemini CLI, and Agentic Skills!)

So AI is leading to job losses, but in a subtle way. Some businesses are letting go of employees who are not adapting to AI and replacing them with people who are. This trend is already obvious in software development. Further, in many startups’ hiring patterns, I am seeing early signs of this type of personnel replacement in roles that traditionally are considered non-technical. Marketers, recruiters, and analysts who know how to code with AI are more productive than those who don’t, so some businesses are slowly parting ways with employees that aren’t able to adapt. I expect this will accelerate.

At the same time, when companies build new teams that are AI native, sometimes the new teams are smaller than the ones they replace. AI makes individuals more effective, and this makes it possible to shrink team sizes. For example, as AI has made building software easier, the bottleneck is shifting to deciding what to build — this is the Product Management (PM) bottleneck. A project that used to be assigned to 8 engineers and 1 PM might now be assigned to 2 engineers and 1 PM, or perhaps even to a single person with a mix of engineering and product skills.

The good news for employees is that most businesses have a lot of work to do and not enough people to do it. People with the right AI skills are often given opportunities to step up and do more, and maybe tackle the long backlog of ideas that couldn’t be executed before AI made the work go more quickly. I’m seeing many employees in many businesses step up to build new things that help their business. Opportunities abound!

I know these changes are stressful. My heart goes out to every family that has been affected by a layoff, to every job seeker struggling to find the role they want, and to the far larger number of people who are worried about their future job prospects. Fortunately, there’s still time to learn and position yourself well for where the job market is going. When it comes to AI, the vast majority of people, technical or nontechnical, are at the starting line, or they were recently. So this remains a great time to keep learning and keep building, and the opportunities for those who do are numerous!

[Original text; https://t.co/zbIhZHfCC0 ]

[Justin Wolfers @JustinWolfers]

U.S. jobs growth is *entirely* one sector.

Last month, growth in private education and health services accounted for +137k of +130k jobs added

Over the past three months, it's +246k of +219k

Last six months: +367k of +85k

Last year: +773k of +359k

[Tibo @tibo_maker]

my predictions for 2026

1. Google will overtake everyone in the AI race, forcing OpenAI, Anthropic, and xAI to specialize. Anthropic is already there. generalist AI won’t win forever.

2. AI agents will buy things for humans on websites like Amazon as reliably as humans do today. once agents get wallets, commerce changes fast.

3. AI security will become a massive problem. not just AI-driven cyber attacks, but a surge of vulnerabilities from vibe-coded apps shipping too fast.

4. people think we’ll be able to clearly label “human-generated” content or trace non-AI media with tags and provenance. I don’t think this will work. many will try but all will fail.

5. people think AI-generated content will ship with built-in receipts showing which model touched what. again, many will try but I don’t think this will stick.

6. robots will scale faster than most expect, especially humanoids. hardware finally starts catching up with software.

7. "Cursor for X" will be the default the mental model. AI won't just live in chat boxes and side panels, but will be embedded directly inside workflows.

8. people think 2026 is the year of generative video. I think that was 2025. 2026 is about world models, prompt-to-3D, and playable generations.

9. text will stop being the default input everywhere, especially for consumer products. for B2B, text stays dominant longer.

10. companies will test product ideas on thousands of AI personas and predict outcomes before writing code. this quietly kills most ideas early.

11. memory will continue to be the moat in AI tools.

12. people think ChatGPT app stores are a big startup opportunity. I don’t see it working.

13. AI-based customer support, onboarding, and customer success will explode. humans handle only edge cases.

14. most AI companies move away from pure seat-based pricing toward hybrid models: seats + tokens + inference.

15. people think agent marketplaces will explode. I’m not convinced. maybe some niches work, but it won’t be a dominant model.

[Melody Wright @m3_melody]

@BillyJeen I wrote about it in December in the free version of the stack.

They’ve been doing g this since May and sales are still abysmal.

https://t.co/IQuNEIVWue

[Hemant Mohapatra @MohapatraHemant]

My yearly reminder to all founders as you go build that next Google/MSFT/Salesforce killer app in 2026: when distribution is proprietary, distribution wins (Comcast vs Netflix), when distribution is commoditized, best product wins (chrome vs IE), when product is commoditized, best service wins (Amazon vs others), when service is commoditized, best network wins.

[Blake Burge @blakeaburge]

Had a friend tell me once: "When you're feeling overwhelmed, there are only two things you should do––get organized and get to work. The rest is just noise. Peace is found in progress."

Some of the best advice I've ever received.

[Sahil Bloom @SahilBloom]

Major life trap: Getting your dopamine from information gathering. Dopamine from information is a dangerous drug. Your entire life will change the moment you stop looking for more information and start acting on the information you already have. Get your dopamine from action.

[Lyn Alden @LynAldenContact]

My December macro newsletter is now available.

It discusses the debasement trade, changing macro conditions, and the large dislocation between the economy and markets.
https://t.co/jKRb3SH87p

[Immigrant Founder @Immigrant_in_us]

@HayekAndKeynes In world of analytics- this is pure elegance. Mona Lisa of metrics.

[Gabbar @GabbbarSingh]

Glad to see Laalu alive to see his family getting decimated at the polls.

Thousands of 90s kids who had to live away from their parents in boarding schools just to avoid getting kidnapped, thousands who had to forfeit their ancestral land as a bribe to get a clerical job, millions who studied hard under a lantern or a petromax to somehow escape the jungle raj. All of them, across the world, doing well, now looking at their phone screens and the numbers, and smiling. This is victory.

[Harsh Gupta Madhusudan @harshmadhusudan]

Long Term Asset Return Study-The Ultimate Guide to Long-Term Investing.
https://t.co/aZFtRzXEqT
By Deutsche Bank. Just came out last week. Covers last 100/200 years of data, based on what is available. Across economic growth, equities, bonds, gold.

Some good insights and charts.