A software engineer’s fear of AI systems taking their job away

In a private Facebook group, a software developer expressed fear about losing their job to AI systems that can write code. As a software engineer who has been thinking about this for a while, I posted a reply to that post. I am so proud of that reply that I am persisting a copy of it here (with some minor edits). 🙂

Go back a few decades. When people moved from assembly language to high level languages, there could have been a similar fear. (I don’t know if there really was, but I think we can draw a parallel.)

You suddenly didn’t have to painstakingly write optimised assembly code and manually link different assembly modules. Compilers and linkers were “good enough.” Tasks that needed three human programmers now only needed one. Experts in different machine architectures were not needed anymore; any high-level-language code can be compiled to run on any architecture.

If you were an assembly programmer, you were right to be terrified of losing your job to compilers. But then, if you just learnt how to code in a high level language, you became a lot more productive. You just had to look beyond machine architectures and see where you could add real value.

I don’t pretend to know how many software engineers will lose their jobs to the new AI systems. But I am fairly confident that today’s programmers will have an easier time adapting to the new world than a non-programmer learning to vibe-code today.

It’s entirely in your control whether you stick to the “old ways” or adapt to the new paradigm. Are you doing something to stay relevant? Ask yourself that, and keep adapting and improving until you have a satisfactory answer.

Random thought: Learning is thinking

Learning is thinking.

Many consider reading, writing, listening to lectures, participating in discussions, etc. as learning. However, they remain only as tools that enable the actual learning, which is thinking.

Surrender: responding to life without a bias

My life coach recommended The Surrender Experiment to me. I have been reading the book ever so slowly.

My primary takeaway from the book so far is to accept life as it happens without the influence of my own personal preferences. The following quote captures the core of the advice:

From now on if life was unfolding in a certain way, and the only reason I was resisting it was because of personal preference, I would let go of my preference and let life be in charge.

For a couple of days, it seemed obvious what I had to do. But slowly it started to be confusing. If on a Sunday I feel like eating at a fancy restaurant, is that my own personal preference, or is that life offering me a fancy meal (in the form of a spontaneous thought)? I didn’t have an answer.

Then it occurred to me. Accepting life means living spontaneously; pausing to question every single choice is anything but.

If always acting by one’s personal preferences is the south pole of the earth, purposely acting against one’s preferences is the north pole. The direction may be different, but they are qualitatively the same; you are still on the same plane; you are still anchored to the earth. What we really need is to rise above the earth. Rather than basing your actions on your preferences, you should ignore the preferences.

Respond to the situation that life presents. If the response aligns with your preferences, so be it. If the response is against your preferences, so be it.

Dream big to realise your potential

I am a credit card enthusiast. I often browse through credit card offerings to see if there are better cards than what I currently have.

Earlier in 2024, I got the Infinia credit card from HDFC Bank. This is sort of like “winning” the credit card game. There is no clearly better card an Infinia holder can upgrade to. (While there may be more beneficial cards for some people based on their spend patterns, it’s hard to do better than Infinia for most people.)

My “credit card optimisation” game pretty much ended when I got the Infinia, with me winning the game. However, I still habitually explore other credit cards every now and then. As expected, such explorations end with a reaffirmation of what I already know: there aren’t many cards I can upgrade to. The time spent looking at credit cards is wasted time, more or less.

But why do I still look at credit card options even when I know it’s not a productive use of my time? I think it’s because I don’t have anything more productive to do.

This is where the advice to “dream big” shines through. Dreaming big and working towards achieving those dreams is an effective way to realise your potential. Had I dreamt of doing something more meaningful than simply collecting credit card rewards, I wouldn’t be wasting time now browsing credit card brochures.

Where GenAI tools struggle

A tricky, niche, tax question. Basic clauses that apply to the majority of taxpayers in the country are described and discussed everywhere on the web. But this specific question is not.

Since GenAI tools are the new panacea, I asked Gemini about this. It said something that was clearly wrong. I thought its “deep research” mode may do a better job. I asked the same question again but in the deep research mode. It did a lot of work and eventually spit out a report, which was also unsatisfactory.

There are nuances in tax rules that need to be considered for answering this question. Most web sites don’t care about this nuance; Gemini, which uses information from the web as its source, also couldn’t understand the nuance. It produced an answer without solid justification.

I then did a regular Google search and found a site that said the opposite of what Gemini said. I asked Gemini a follow-up request to include information from this new page.

My expectation: Gemini will reconcile the differences between the sources and improve on its previous answer.
What Gemini did: Gemini simply overwrote whatever it had said before with what was in the new site.

Gemini did exactly what I do when a code reviewer is forcing me to do what I don’t want to do, but I am tired of arguing. I just do whatever the reviewer says and move on. Gemini doing that to me did not exactly instill confidence in the report it had generated.

While GenAI tools are great at many things, they are not exactly good at answering niche questions based on conflicting information from different sources.