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I have a similar take. I suspect at some stage “software development” will mean feeding business requirements (with some degree of precision) into the algorithm
by mypastself 4y ago
I have a similar take. I suspect at some stage “software development” will mean feeding business requirements (with some degree of precision) into the algorithm and letting it handle logic, resource provisioning etc. The last traditional programming jobs to go will be legacy software for critical infrastructure, defense, and financial institutions.
Communication skills and business domain knowledge will become far more important than what we consider “tech skills” today.
I doubt the world’s appetite for software will decline even when one person manages to develop in a day what used to take a team of people months. We’ll have a lot more work to do, and a lot more people will join the field.
However, on average, it might become a much less lucrative and prestigious profession.
- yunohn 4y ago> I suspect at some stage “software development” will mean feeding business requirements (with some degree of precision) into the algorithm and letting it handle That’s just a higher level programming language… And we all know that it doesn’t solve things.
- mypastself 4y agoIt actually does solve a lot things, in the sense that there’s a lower barrier for entry. A lot of lower-level programming skills are being abstracted away and obsoleted. My prediction may be wrong, but it’s based on the extrapolation of the trends you’re referring to.
- yunohn 4y agoHigh level languages like Python abstract away boring specifics like memory management and implantation data structures. Natural language programming via GPT instead abstracts away the actual functioning. I’ve seen colleagues use snippets from chatGPT that are horrendously inefficient despite being “simple” prompts. They look fine at first glance, but work only 50% of the time.
- mypastself 4y agoOh, there’s no doubt this particular AI software is flawed. But I don’t think there’s anything inherent to AI that renders it unable to master specific frameworks or algorithms in future iterations. The timeframe is up in the air, though.
- yunohn 4y agoI’m not convinced it’s an AI quality problem - rather, the difficulty of translating natural language into machine requirements. This is an age-old problem, not even restricted to Computer Science.
- comfypotato 4y agoI agree with the other comment responding to you. Consider SQL. A typical select statement with a join and a sort would have taken a team of people months to implement in an application-specific proprietary data-storage structure (perhaps a red black tree). Now it’s a trivial line of SQL. Like the top comment said, this has not eliminated those teams’ jobs.
- ltrojanowski 4y agoThe one difference I see is that SQL is still predictable in it's output. I don't think feeding requirements into an AI is at that state yet
- mypastself 4y agoInteresting you should mention SQL, because a lot of non-tech business people I’ve met have rudimentary SQL skills nowadays. Database administration is a dying field.
- comfypotato 4y agoI was speaking of the engineering teams that existed before database administration was formalized as a field at all. Mainframe, batch processing, and written in C: proprietary company-specific applications. Analogously, it may not be long before crud websites are created, end to end, by non-tech people with mostly natural language. That being said, today’s crud web developers won’t be out of work. Their experience writing/designing code will be put to use in more complex, potentially yet-unseen applications.