Incorporating your startup the right way - India, Germany, USA | Founder Finance 101

The reason I chose to write about this topic is to help fellow founders benefit from my learnings which I picked up the hard way. Most first-time founders make mistakes and I did them too and I wish someone guided me the right way when I started. 

I had an unique(slightly painful) experience of setting up multiple entities myself across different countries and keeping them "investor ready". On paper it sounded exciting but in reality, it shaped my choices more than I expected, because as I founder I value ease and time spent on admin topics.

I would like to start from the very first step of choosing the right country to set up your entity and then elaborate about the process in each country.

Figuring out where you're really building

Before thinking about forms, lawyers, or incorporation packages, its important to figure out:
  • Where are my first customers?
  • Where do I plan to raise money?
  • Where is my team going to be based (at least in the beginning)?
In my experience, it’s almost always easier to register where your main market and investors are. That’s where you’ll need to open bank accounts, sign contracts, and build credibility. Most global VCs prefer dollar accounts, so sometimes an US entity becomes inevitable. Each country of choice comes with its pros ai nd cons, its really all about identifying what is best for you.

The assumption here is that we are building a venture which is investor-ready at every stage. That means the way you incorporate should not only work for today but also stand the test of scale, fundraising, and due diligence later.

Each country comes with its own trade-offs. Having personally incorporated in India, Germany, and the US, I can tell you that the paperwork is only the surface. The real differences show up in compliance load, costs, taxes, how investors react and even how easy it is to just open a bank account.

That’s why I’ve split this into a series. This post is the consolidation piece giving you the framework and big picture. Then, in separate deep dives, I’ll go step by step into each country’s process, costs, and lessons learned.

Here’s what’s coming:
  • India - Cheap to start, but heavy compliance and filings. I’ll explain how I registered a Private Limited, what it cost me and why I found compliance painful.
  • Germany - A UG sounds attractive on paper (€1 share capital) but the bureaucracy is brutal. Investors prefer a GmbH which has a higher share capital (€25000 share capital). I’ll share my experience running a UG/GmbH, the difference between them and what investors think of each.
  • USA (Delaware C-Corp) - The global VC default. Fast to set up, clean structure, and the easiest for fundraising. But tricky if you’re not physically in the US. I’ll break down the steps, from incorporation to 83(b) to bank accounts.

A common thread, what is true everywhere

No matter where you set up, some rules don’t change.
  • Pick one base entity - Don’t scatter companies across countries. It feels smart in the moment, but later it kills you with compliance and tax complexity.
  • Hold your shares cleanly - Either you buy founder shares directly, or (if you’re thinking long-term wealth structuring) you create a holding entity that owns your shares. Just be careful: a corporate holdco can break things like QSBS in the US. If you’re not sure, default to holding personally and file your 83(b) on time.
  • All IP lives in the company - Don’t keep your code in your personal name. Assign it properly.
  • Keep books and filings clean - Even with zero revenue, you’ll still have deadlines. Miss them and you’re bleeding cash and credibility.

If you are a first time founder. Choose the setup that works for you, focus on avoiding liability, avoid tax issues and think ahead of the current stage of your business. 

Learning Capitalism - How AI is separating thinkers from followers

There is a strange reality around us. Artificial intelligence is becoming the most powerful tool ever created by humanity. It can write, code, design, plan, summarise and even think ahead for us. As Sam Altman said, "its like carrying a bunch of PhD level experts in your pocket". Everyone talks about how AI will make humans smarter, faster, more capable. But when I look closely, it's different. It's a strange effect which I previously never imagined.

I always knew human behaviours were being cognitively altered by apps, but not once did I think AIs would make humans dumber. There is an evident paradox which is pushing the limits of human intelligence creating a strong divide between the thinkers and the followers. As humans our brain needs consistent activation of cognitive muscles to make ourselves smarter. Smarter does not mean a directly proportional IQ. It means the ability to learn and evolve as per our surroundings. This increases the brain plasticity which is one of the most important things that makes humans better than other creatures. 

But with AI, people have started to outsource thinking. A similar phenomenon occurred when calculators were invented. People stopped doing basic mental math and lost relative cognitive ability, while a small group of people focussed on more intelligent math problem solving. Another very interesting example is GPS, where people stopped remembering routes. In all these inventions the common aspect was that majority humans outsourced their thinking and took help of the inventions to reach an outcome. But with AI it's different, as AI isn't doing one thing, it's able to do many things in cognitive synergy resulting in a similar thinking capability like a human brain. While the top 1% of people use AI to enhance their cognitive ability, the majority are falling into the trap of using AI for any question that strikes their brain. 

Over time, this creates two very different types of people. A small group who use AI as leverage to push themselves harder, and the large majority who let AI replace their effort completely.

This is why I call it learning capitalism. Just like in economic capitalism, where resources accumulate to those who know how to use money well, intellectual power will accumulate to those who know how to use AI well. The fittest brain workers will grow sharper because they combine their own thinking with AI’s power. The rest will slowly fall behind, becoming dependent consumers of intelligence rather than producers of it.

The majority of people offload their primary cognitive skill while a minority built new levels of mastery on top. This magnifies this divide a hundred times more between average and the top learners.

The paradox is that, AI should have been a great equaliser for the masses, as it gives everyone the ability to learn, create and build. Yet the more powerful it becomes, the more it risks creating an intelligence inequality unlike anything we have seen. A few people will become cognitive athletes, training their minds every day with AI as a sparring partner. Everyone else will become sheep, blindly following whatever output the machine gives them.

The consequences of this are exponential. Work will not only be divided between skilled and unskilled but between those who can think and those who cannot. Entire careers will disappear for people who are unable to add original thinking on top of AI’s answers. Meanwhile, those who continue to think deeply, to challenge themselves, to use AI as an amplifier rather than a crutch, will build the next generation of companies, products and ideas.

I believe the future of personal growth depends on how you relate to AI. If you treat it like a sofa, it will make you comfortable and weak. If you treat it like a gym, it will make you strong. Asking it to do your work is easy. Using it to sharpen your own thinking is hard. The difference between the two will define who thrives in the next decades.

Intelligence is no longer evenly distributed because of access to books or schools or the internet. Intelligence is now a choice. It is the decision to keep exercising your brain in the age of effortless answers. AI will not kill thinking. People will kill their own thinking by choosing convenience over struggle.

So the question is not whether AI will make humanity smarter or dumber, but whether we choose to be thinkers or followers, whether we choose to become Learning Capitalists in our lives and careers.

Why most AI startups won't survive?

Every week there’s a new AI startup on X, Linkedin or Product Hunt. Another wrapper around an LLM. Another shiny demo that calls someone else’s API. Founders raise a seed round, go viral for a day, and then make quick revenue and will vanish.
The truth is uncomfortable, if your company is just an API call to OpenAI or Anthropic, you don’t own anything. You don’t own the moat, the data, the infrastructure, or the economics. You are just a middleman, and middlemen don’t survive long.

The platform always eats the layer above it

History repeats.
  • If you built a business on top of Facebook pages, Facebook killed your reach.
  • If you built on top of Twitter bots, Twitter closed the API.
  • If you built on top of Shopify plugins, Shopify cloned you.
Why would AI be any different? Right now, startups are building clever UIs around APIs. But the model creators are not your partners, they are your landlords. At some point they raise rent, change rules, or release the same feature natively.

Who actually wins?

Four kinds of companies survive this wave:
  • The model builders. The people training foundation models with compute, data, and talent. This is capital intensive and brutally hard, but it’s where the real moat lives.
  • The infrastructure players. Cloud, GPUs, fine-tuning platforms, data labeling, orchestration layers. These companies sell the picks and shovels for the AI gold rush.
  • The distribution moguls. Startups who have cracked the global distribution game through virality, network or capital will make it big.
  • The real problem solvers. There is no replacement for true customer focused problem solving. If you built a solution that customers need and use AI to make the solution better. You will survive any hype cycle.
Everyone else? They’re features waiting to be absorbed.

But isn’t there room for applications?

Yes, but the bar is much higher than a wrapper. If you’re building an “AI startup,” you need one of:
  • Proprietary data that no one else has.
  • Distribution that no one else can match.
  • A workflow so deeply embedded that replacing you feels impossible.
If you don’t have these, you’re not a company. You’re a thin UI on someone else’s infra.

The hype cycle is brutal

Investors are learning fast. They funded clones, wrappers, gimmicks. Now they want defensibility. They want to know why the platform won’t kill you in 12 months. Most AI startups can’t answer that. 

Model builders will always say wrappers are ok, because thats how they make the money. 

The uncomfortable advice

If you’re building in AI today, ask yourself honestly:

  • What do I control that the API provider can’t take away?
  • What can I defend if the model costs drop to zero or features become free?
  • Am I building something with a moat, or just a feature?

Because here’s the reality, when the dust settles, the only survivors will be the ones who either own the model or own the infrastructure everyone depends on. Everyone else will be a footnote in the history of another hype cycle.

A start-up’s toughest position is a CTO and why?

After spending several years as a Chief in startups, one thing I have understood is that, adaptability is a very important aspect of being on top of the ladder.

Specially being a CTO myself, the amount of responsibility and the adaptability at different stages of the company is tremendous. Although it is not the most celebrated role in the media due to lack of awareness, I believe this role is a backbone for a startup in today’s world. Most of the startups in 2021 are supposedly technology companies. The main aspect of a technology company is the product and its evolution at different phases of the startup.

What changes or evolves so much in the Chief Technology Officer’s role and why is it important?

Stage 1 - The Goto Generalist

"Oh! is the browser not working, ask the CTO"

Yes this is true, when you are a very early stage startup with very limited technology resources and affordability, the CTO is the goto person for all of that is considered a tad bit technical. From the issues related to laptops, to the issues in the product ranging from UI/UX, development, Dev-ops, etc.

There are no limits or boundaries of issues to be handled as they are related to technology. It doubles when you are both the CTO and CPO, which is the case in majority of the startups. When you deal with the core product you start to deal with a bit of the business side too. So now you end up being involved or doing some bit of everything.

Stage 2 - Time to hire and build

Now you got some funding and you are building the tech team and start to deal with many people. Now you are only coding 50% of what you did before but you are still building the overall architecture of product and slowly stepping away from coding. You end up spending more time hiring and managing people than coding and doing the technical part of the job.

Now you have your first customers and now not only do you deal with internal team feedback, you also deal with customer feedback and have to plan the schedule out for features and improvements.

This work doubles if you also are a founder, now you also have to report the financials, product growth stats etc.

Stage 3 - The strategist

During this phase you will not code anymore and then completely be responsible for people. You will not completely be hiring, managing and scaling the team. You will be more business oriented than ever before and you will hardly deal with the technical issues.

Now you will be more focussed on resource planning than ever before and you will build scale up strategies to meet the needs of your customer.

Stage 4 - The innovator

This is probably the most explorative phase of being a CTO. Once you have the right people in place for the key roles in the technology team, then you will be exploring on new innovative approaches to increase the overall customers.

The key roles in a tech team would usually be Head of Engineering, Technology Lead, Software architects. These roles form the crux of the technical setup of the product and if these roles have good hires, it gets easy to scale the company.

While you are confident about the key people then you can get into an innovative mindspace where your goal is to either explore new solutions or techniques to solve or build something new.

These 4 stages have been the evolution of the CTO role in my experience and hence I consider it to be a very demanding position in startups.