I don’t spend much time thinking about clothes or appearance. What I think about is fit: whether my skills and instincts match the role I am in. So today when every social platform is sharing people in 1980s attire, I ran a different experiment. I asked what I would have been doing if I existed in 1980s Pakistan instead of today.
There was no prominent software industry then. No internet, no local computer companies, and a personal computer was a rare and expensive import. The Department of Computer Sciences at Quaid-i-Azam University was established in 1976. Initially it was only Post Graduate Diploma in Computer Science and later in 1985 it had MS and PhD degrees.
So the version of me from that decade would not have been writing code. But the instincts I use every day now, understanding a system and organizing people around it, existed long before software did. I just had to find where they would have landed.
Engineering, not software
Mechanical, electrical, or civil engineering would have been the closest match to building things that work. PTCL, still called Pakistan Telephone and Telegraph then, was expanding infrastructure across the country. That kind of systems-based, technical work would have pulled me in, even without a screen in sight. The instinct to understand how something works and make it better does not need software to exist. It just needs a system.
Civil service or public sector administration
A surprising number of technically minded people in that era ended up in administrative or bureaucratic roles. Not because they loved paperwork, but because that is where the large-scale coordination problems actually lived: roads, utilities, education systems. If your real skill is organizing people around a shared outcome, government service was one of the few places with a canvas large enough for that kind of work.
Academia and research
Universities in Pakistan were already producing engineers and scientists, and places like Quaid-i-Azam University had access to advanced computing facilities even then. Being close to research projects and early technology adoption was possible if you were in the right academic circle. Teaching itself was a respected, stable path for someone who understood technical material and liked explaining it clearly. That instinct is the same one behind the mentoring and community work I do now.
Family business or local trade
A lot of technically curious people in that decade built or scaled something practical: electronics repair, machinery import, industrial supply. Not because they set out to run a business, but because that is where hands-on problem solving met actual demand.
The pattern underneath
Looking at all four paths, the subject changes but the work does not. Mechanical instead of digital. Administrative instead of product. Academic instead of community-led. But in every version, the actual behavior is the same: understand a system, organize the people inside it, and make it run better.
Technology is the subject, but organizing people and solving problems is the constant.
Running the same experiment forward
If I can run this experiment backward into the 1980s, I can run it forward too. AI is now doing a growing share of the work that used to define technical careers: writing code, drafting documents, analyzing data, even parts of design. The natural question is what happens to someone like me when the subject changes again, this time from human-built systems to AI-built ones.
I don’t think the answer is a new job title. I think it is the same constant, applied to a new kind of system. AI can generate options fast, but it cannot decide which problem is worth solving, or judge whether a solution actually fits the people who have to live with it. Someone still has to do the discovery: ask the right question, read the room, decide what tradeoff is acceptable, and take responsibility for the outcome. That work does not disappear when a machine can write the code faster than a person can. If anything, it becomes the whole job, since everything downstream of that judgment can now be produced in minutes.
So in a future where AI writes most of the output, I expect to be doing what I already do now, just with less of my time spent producing and more of it spent deciding. Framing the problem correctly. Coordinating the people and systems around a solution. Owning the outcome when the AI-generated option turns out to be wrong. The tools will keep changing. The 1980s proved that once, and AI is proving it again.
Technology is the subject, but organizing people and solving problems is the constant.
If you strip away the decade and the tools, most careers built around problem solving would look the same at their core. The interesting question is not what field you end up in. It is whether you can name the constant that shows up no matter which field you land in.
What would yours be? Would like to find your Ikigai?
If you want to talk through product, team, or delivery problems, reach out here.
Tahir Shahzad
Tahir Shahzad is a Product Manager, Product Owner, and technology consultant with over a decade of experience helping startups and organizations build products people actually use. If you are working on a product problem worth solving, reach him at tahirshahzad.com/contact/
