The Insider Guide to Careers
Insider information, secrets and tips about getting hired and building careers. For employees and job candidates.
The current market buzz is about creating careers in Artificial Intelligence and Machine Learning. A friend of mine who worked in Silicon Valley for 30 years recently made a job change to get into Generative AI and works as a project manager handling these projects. I asked her if this is not a demotion, and her answer was that this was a long-term investment, and the move would make her resume more attractive. This issue of chasing what it hot in the market is running rampant in guiding both student and professional careers. I will argue that all these moves are disasters in the making and doing this is a sure-fire way to ruin one’s career.
Rise and fall of technologies:
Let us get a couple of things right. Artificial Intelligence (AI) is not new technology, it has been around from the 1940s. Alan Turing worked on it then and later in the 1950s, Marvin Minsky continued the research. Marvin set up the MIT AI Lab which pioneered research in this space. All this hype around AI is not just about the transformative potential, but the impression that there is a virtuous cycle of enabling technologies that will drive AI adoption across sectors. In the 1980s, superconductivity was the holy grail, but went out of fashion. From the years 1980s to the 2000s, finance companies and Wall Street ruled the roost. In the 1990s it was the advent of the internet and internet businesses emerged like Amazon. The Business to Consumer (B2C) companies were famous in the 2000s. Google, Yahoo, Netflix, and a bunch of other companies emerged in that era. Nanotechnology was also a hot technology in the last 2000s. However, the interest in it petered out dramatically like a rerun of the superconductivity craze.
In the 2010s, it was the cloud and SAAS companies which were extremely popular. This was also the time Silicon Valley began displacing Wall Street. The valuation of big tech also began to go up dramatically. During the period from 2015-2020, the crypto craze started taking over. After the COVID scare, the crypto crash happened and all of a sudden, the AI boom emerged. Valuations of companies like NVidia and Microsoft are going through the roof while Google and Amazon are being punished for not being attractive on the AI front. A surprising change of circumstances indeed. Who would have thought that a company like Microsoft, started in 1975, would end up outwitting everyone else including a company like Apple.
As you can see from this quick review, hot trends and media darlings go in and out of style very quickly. If you are a high schooler going to college, it is a difficult decision. Four years back, every Computer Science (CS) student used to have multiple job offers. Seeing this data, a high schooler decides to take up CS as their undergraduate specialty. However, they have no idea what would happen after four years at the point of graduation, as everybody is guessing what the future would be like. Alas, it is these same students who are now in the dumps. The job market turned quickly and now CS students are struggling enormously to find any job. This is why one can never know the future for sure.
Wall Street vs Silicon Valley:
When I was studying in universities like IIT Bombay and Cornell in the period from 2000-2010, everyone wanted to be in Finance. The desperation was palpable everywhere on campus. It was the Wall Street companies giving the highest bonuses. Even the dot com boom int he late 1990s was not enough to dislodge the Wall Street behemoths. The rout of Wall Street began in the year 2008 because of subprime mortgage exposure. There were immense layoffs and big companies like Lehman went bust. All these shook the market. Wall Street never recovered after that disaster. The tech companies meanwhile were booming. Many SAAS and Cloud companies did extremely well. So many multimillionaires were created through IPOs, that even the finance savvy folks now began to think that the route to big money is in startups and tech companies. Wall Street could make you rich and make you slog hard, while tech companies could make you super rich and make you slog less hard. It was a non brainer. There were examples of success everywhere. Let me recall two cases. One software engineer in Palantir had 2.5 million dollars of stock when his company went IPO. Another friend, who was not even in tech, got 100,000 Dollars of stock for an entry level HR role in Doordash. This was right before it went IPO. During the COVID boom, this stock was worth 5 million dollars. There was money everywhere in tech, and Finance could not hold a candle to this sector. Of course, a lot of this is paper money and companies can go up and down in value dramatically. Companies like 23andme, Theranos and others are examples of companies which showed promise only to go bust.
Skills:
As you can see from the writeup above, skills change every year. Just like other fads, AI will also be a fad that will be replaced with something else. The founders of one big tech FAMG company through his foundation has given about 319 million dollars to media. Another FAMG founder has a 100 million dollars prize given to media and to politicians. Do you understand why media is being feted so much, in a world where there is no free lunch? So, do not take media reports about AI too seriously. Nobody knows which is paid news and which is not.
The next waves in innovation will happen in fields traditionally impervious to change like mechanical engineering, production shopfloors, drug discovery, transportation and so on. Software engineers will have no idea how to resolve these problems. Only deep subject matter experts (SMEs) can resolve these issues using the latest technologies. So, intersectionality of skills become important. However, the primary skill has to be from a core engineering discipline. CS will be an accessory skill for future waves of transformation.
Not everyone can be excellent in software engineering or product development. This is the sad reality of life. One can be excellent only in a narrow set of fields and the fields are different for every person on earth. Identify your skills and play to your strengths. To have a great career, you have to be excellent in something and not just average. Those who are trying to fake AI or CS skills will never get anywhere. So be real, logical and long term in your approach.
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