AuthorRohit Chauhan

The basis of white collar work is changing rapidly

In the early 2000, with the internet and google, the grunt work around finding information was removed. Value add for any type of work shifted to putting together this information in a valuable format

For investors, this meant that bulk of your effort shifted from finding information to synthesizing it to arrive at an investment decision. The front end of the workflow – Finding annual reports, data points which used to be manual was now available at the click of button.

In the same manner, for jobs like coding, we have repositories for a lot of the boiler plate code. A significant part of such jobs is now is in glueing these components together to achieve the desired outcome

Paradigm shift

The launch of LLMs in 2022 is changing the core of all white collar jobs again. The difference this time is that it is faster and moving up the value chain at the same time

I was initially curious about these new tools and started experimenting with them in early 2023, as I did with the internet and google in the past. For those who saw the early internet, these tools felt like the dial up connection of the late 90s – slow, clunky with limited usage

Google and broadband in the early 2000s made the internet what it is today – cheap, easy to use, ubiquitous. I am seeing the same transformation in the LLMs, but at 10X the speed

The early chatgpt was Realtime and good at answering questions for which the answers already exist on the internet (and thus part of its pre-training). With the launch of the O1 and now O3/O4 models, we have reasoning models which can ‘understand’ your questions, plan the tasks and decide which tools to use to best answer these questions

This is a paradigm shift on how computers work

All other software tools follow a fixed information flow via logic embedded by the developers and system designers. In contrast these tools operate more like us, than traditional systems. They are becoming autonomous agents

Burying head in the sand

There is a lot of chatter around the implications of these tools on the future of work. I will not get into which jobs will or will not get replaced. Time will tell

A few things are, however, clear based on the current state of these tools

• The base models continue to improve rapidly based on new algorithms and more compute
• We have new reasoning models which continue to improve based on reinforcement learning techniques
• The cost of these tools continue to drop exponentially (almost 90% per year)

This means that the cost of performing routine tasks and synthesizing information is dropping rapidly. If the major part of your job is to use existing information and put it together in a different format, you face competition from these tools which can do a good enough job at 5% of the price (and dropping)

This does not mean we are doomed to irrelevance as the tools get better. However it does mean that we need to re-think what is our value add (to get paid well)

This is similar to waves of automations in the past – Farm and factory workers were not happy when machines replaced human labor. They fought this change tooth and nail. We will see the same happen with white collar work.

A lot of pushback is on the following lines

• The work quality of these tools is poor (same as weavers complaining about the quality of hand-woven cloth versus the machines)
• They are taking work away from hard working people
• It is unfair

I am not denying the pain these tools will cause in the workforce, but burying our head in the sand is not going to change reality.

Change your workflow

I personally think we should all take these new tools seriously and start learning as much as we can on how to use them. The next step is to breakdown your own workflow into what can now be done more efficiently using these tools.

Let me take investing as an example

The job of portfolio managers/Investors/Research analyst shifted from finding information to synthesizing it in the last few years. There are screening tools, financial websites, charting tools available where we can get all the necessary information in a few minutes (which used to take hours and days in the past)

The main job for us was to put synthesize all this information and arrive at the final decision – should I buy the stock, how much of it and at what price ?

As an investor, we get paid for our decision, not for the effort we put it. If we can reach a high-quality decision in a few hours versus days then it’s even better. In such a case, these new tools are a great benefit to us. We need to drop the mindset from our school days: grade = amount of homework. In markets, it is always quality over quantity

In the past I would read up a lot of documents and think of questions to answer. I would then dig further for the answers, but generate new questions at the same time.  Invariably there would be a point of diminishing returns after which I would decide with 70-80% of the information

I am no longer constrained

My job as an investor is to read the necessary documents as a starting point and come up with a list of questions. I can feed these questions to one of the LLM tools and  get a detailed answer. I can dig into this output, push my understanding forward and generate a new set of questions

The result is that I can have a better understanding of the company and its industry in a much shorter period of time. What can be better than that?

I will dig deeper in my next post into how I have changed my workflow and incorporated these tools.

The most important change for all of us, including investors, is now to come up with high quality questions. We are getting to the point where our computers will generate better answers than most humans

I came across this word recently and resonated with me. On reading about it, I realized that I have always admired this behavior and strived for it. So what is agency?

As per google,

In a person, “agency” refers to the capacity to act independently, make free choices, and exert power to shape one’s own life and experiences. It’s about having control and influence over one’s actions and the outcomes they produce

In India, we call this jugaad

As I look back on my own life and those around me who have done well, I find almost all have had high agency – a drive to improve their life

In my generation, India had started opening up and we experienced the first technology revolution – Internet. A lot of young people in the late 90s joined IT services companies (making switches from other careers), some started online businesses, some moved to the US and some like me started a blog on investing on a whim

I enjoyed reading and investing. Pre-internet it meant getting annual reports from brokers and reading the newspaper. There were no Indian blogs (only US based such as the Motley fool bulletin boards). When I found this new medium, I started writing my own thoughts for no particular reason

Today its called content marketing, but then it felt like writing to myself with no one reading it

One thing led to another – I eventually started an advisory with my friend – Kedar which we have been running for 12 years. I still get surprised to hear from people that they have followed me for years and were reading what I was writing. I never realized that this would happen

The new revolution

We now have another shift in the making – Artificial intelligence. I am equally excited about it. As in the late 90s I get the same tingly Spidey sense of something exciting.

How will it evolve and where will it lead us?

I don’t know, but as I did earlier, I am learning about it and playing with it

I am sure it will be an exciting and fun journey as it happened with the internet. I keep saying to anyone willing to listen to do the same but be less timid

We wrote the following to our subscribers

When and at what level will the market bottom?

what should be the cash level in the portfolio to ride out the bear market?

These are wrong questions to ask. Let me explain –

I wrote about preparing for a downturn in my prior note. We have developed a process based on the study of the past bear markets and our failures. The key point is that we ignored some risks in the past which hurt us when the market cycle turned.

We have identified the following risks and managed them as they intensified towards the second half of 2024

1. Valuation risk: We exited/trimmed several positions in tranches as stocks went from under-valued to fairly and then overvalued. We did not exit these positions in one shot as we wanted to take advantage of the momentum
2. Position size risk: There are positions we want to hold through the cycle. However, this poses the risk of opportunity loss if the size is too large. We trimmed some of these positions so that we can hold the balance with less stress
3. Sector concentration: we reduced positions if they were based on the same theme and sector. When a sector goes out of favor, it can impact the stock for a long time
4. Poor performance: In some cases, the performance of the company was weakening and we exited as the risk reward was no longer attractive

One additional element this time was to review the indices and breadth to gauge the market cycle. As the cycle weakened in Q4, we actively reduced our risk.

In summary, we were focused on managing risk and not predicting what will happen to the market.

Half the battle

We are now at 45%+ cash level which is the highest ever and it is NOT burning a hole in our pocket. This cash level is an outcome of the process

It is easy to feel smug at this point. However, this is only half the battle. Equally important is to re-enter the market and not get locked into a bearish outlook.

We will not depend on market forecast or expert views for it. We have looked at this phase of the market too in the past cycles and have a process of initiating or raising our positions. Some of you have asked how long will it take?

We don’t know. That can only be known if you can predict the market (We can’t)

Graded entry and exit

We had a gradual exit out of several positions to reduce the aggregate risk as the market weakened.  We will re-enter in a gradual manner too driven by our buy process

The buy process for a stock will be based on its fundamentals and risk reward equation. It does not require for us to forecast when and at what level the market will bottom. Fixating on the market level is a waste of time. We are focused on refining and executing our process of finding and entering new positions

This time around, the cash level will also be a result of executing this process

I started my career in Marketing and switched to IT (consulting). The pay was 2X and the stress was half of that. I had also come to the realization that I did not enjoy sales/marketing. Reading and learning was the thing I loved, and IT provided a great opportunity for that. Investing was the other area where I could the same and earn at the same time

I joined one of the Large IT services companies and was deployed on an ERP project. I had no clue about the technology. I tackled the problem the same way I had handled it as an investor

I went online, downloaded the implementation guides, manuals, notes – whatever I could find and started reading them. At first, they made no sense. However, by the third reading (cover to cover), I started getting a hang of it

The next step was to get into the software and practice. I became good at it within a year.

On the next project, I had some juniors working with me who were in the same place, I was a year back. To my surprise, when I asked them to read all the material, cover to cover, they balked at it. Till the end of the project, they kept reaching out to me for help and just coasted along

Most people avoid lifelong learning

At the end of this episode and a few years later, I realized a couple of things

• These colleagues did reasonably well in other companies and moved into managerial roles. It just showed that learning was not key in moving up the ladder and most companies did not care for it.
• There is a perverse system where a lot of IT service companies do not reward for deep expertise. As a result, they end up with a layer of management who have outdated technology skills. It is not their loss though as they tend to fire such resources when they get bloated
• Curiosity and drive to learn is not as common as I thought. Most of the people I know would rather coast along without pushing themselves

Why people avoid learning

Initially I was puzzled why people avoided learning when it was fun, and you were better off in the end

I realized that the process of learning makes you feel stupid. I recently went through this phase when I was learning technical analysis and poker a few years back. Even now, I get the same feeling on a regular basis. This is not a question of intelligence. No one likes to feel dumb and as a result people avoid learning new things

This will be a major hurdle in the future for a lot of people as new AI based technologies go mainstream. I have gone down that rabbit hole in the last 2 years and can see massive changes on the horizon.

Unfortunately, a lot of people will complain and find reasons to avoid the discomfort of learning. I am lucky that I am comfortable with feeling lost and stupid most of the time. I have 25 years of practice in it