| Friday, 23 August 2024 |
An abridged, narrative version of the latest episode of Two by Two, The Ken’s premium weekly business podcast Subscribe here
Good morning [%first_name |Dear Reader%],
Software engineering careers used to be a ladder. You studied for four years, got a job as a fresher, and could virtually take for granted a steady career filled with learning opportunities, salary hikes, and role promotions.
In fact, being an engineer was so cool that we mocked MBAs and MBA-types—“suits”—for their desperation to find that elusive technical co-founder. The one who could translate an idea (hardly a rare commodity) into code and products.
Except, that’s increasingly not true.
A The New York Times story published earlier this week put it best.
“I have a pretty good sense how fast the progress that students should make in a semester should be,” he said. “In 14 years, I’ve never seen students make the kind of progress that they made this year.”
And he knew exactly why that was the case. For the first time, Mr. Ammirati had encouraged his students to use generative artificial intelligence as part of their process — “think of generative A.I as your co-founder,” he recalled telling them.
Many AI chatbots are fully capable of writing code now. So your technical co-founder could be an AI?
Meanwhile, AI tools are making some of the best engineers and programmers even better at what they do. Companies and investors are realising that perhaps they don’t need as many people to write or maintain programs as they did earlier. The real reason hundreds of billions of dollars are being spent on AI is because everyone is assuming a disruptive productivity jump at some point. Allowing one person to do the work, of say, four, or 10.
Where does that leave engineers? Are we staring at the end of the golden era for engineers?
Hello and welcome to episode #6 of Two by Two, The Ken’s weekly podcast that asks the most interesting and often uncomfortable questions on topics we all want to know more about. And we do that through the lens of a 2×2 matrix!
Earlier this week, Praveen Gopal Krishnan, my co-host, and I met with Amod Malviya, co-founder of Udaan and the former CTO at Flipkart, and Kailash Nadh, CTO at Zerodha*.
Both Amod and Kailash have been programmers and engineers for over two decades now. They are also both deeply in love with their craft. Naturally, they are passionate about engineering and have strong views on its future.
Over nearly 90 minutes, the four of us discussed the future of software engineering, and of the engineer.
Each episode of Two by Two is a freewheeling discussion driven by curiosity. As we go along, we try to connect the dots to arrive at possible explanations and answers.
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Is AI a threat to engineers?
We began with a somewhat theoretical, but in hindsight, valuable distinction. Between engineering and programming.
Amod Malviya: I know you mentioned that we should not bring bridge-building into the picture, but I’m going to use that analogy.
Let’s say a person knows how to lay bricks. So bricklaying requires a certain amount of training versus building a bridge.
Are these two identical activities in terms of the skill needed, the ability needed, and the kind of understanding you need to have about systems?
Engineering is what I would map to programming.
The bridge-building—building a bridge, designing a bridge, characterising its parameters—those are things I would associate to engineering.
Amod went on to say that most engineers he knows aren’t remotely concerned with AI.
Amod: And similarly, this idea is very laughable right now, that engineering is equal to programming. What tends to happen is, because people outside of technology view software engineering as programming, they get so excited when they see an LLM produce code.
In pretty much all of my circle, direct and indirect, every engineer I see is actually super excited about it, instead of actually having some sort of an existential crisis. It’s actually the exact opposite. Like what Kailash was talking about earlier, about this leading to huge improvements in his personal workflows.
Every engineer I speak to is actually super excited about it.
Absolutely none of them, even in their wildest dreams, are actually worried about being replaced.
Kailash shared an example too.
Kailash Nadh: At our workplace, we’ve been experimenting. We have one person who’s experimenting with some of these open source AI models. That’s our entire AI machine learning wing. One person experimenting.
Rohin Dharmakumar: To be clear, that one person is not you?
Kailash: No, it’s not. It is one person who was like, you know what, this is so interesting, let me try it.
And we’re like, you know what, let’s try and solve some of these problems we have with this.
Rohin: And just for context, this is one out of how many? How big is your team?
Kailash: So we are 34 people, including our entire product tech, programmer, engineering, design teams. And that’s 34 people over 11 years.
We have very different unconventional views on the size of teams.
We shifted the conversation to engineering careers after a while. Due to the rise of LLM-driven AIs as the proximate trigger, we’re suddenly confronted with questions that cannot be answered by merely trying to do what we’ve done in the past. If “drone work” can easily be taken over by LLMs that drive “drone productivity”, what will human engineers be for?
Over the last 15 years, most tech startups and accompanying business models have encouraged “ladderism” among engineers—progressive and iterative development that didn’t care for fundamentals. Or purpose.
With Amod’s help, we sketched out a graphic that depicted a broad (and oversimplified) arc of technology adoption trends during the last few decades.
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