In our previous Talman Tidbit, we spoke about how the acceleration of machine learning models could lead to a new Industrial Revolution.
In conversations I’ve had with several of my colleagues, specifically about programming, we see three different scenarios that could emerge over the next three years if such a new Industrial Revolution were to occur.
Scenario A: Laying Off Lower Tiers Of Technical Talent
Currently, in a functioning software development environment, there are a number of small projects that are good training grounds for junior developers. GPT4/Copilot might take over these projects. As such, there will be drastically fewer juniors hired by these shops.
What about those junior-level programmers who are already employed? What if that group becomes more productive and elevates their skill levels? You might think this equates to greater job stability – and perhaps, in some future cases, that may be true.
However, consider this: Even if we increase productivity across the board, not every programmer will be more productive at the same level.
For instance, on a scale of 1 to 10, if a programmer has a skill level of “7” out of 10 and another programmer has a skill level of “4” out of 10, you have a multiplier effect that if people learn and the multiplier is more significant for a greater number, the “7” programmer might be multiplied by 50% but “4” might get multiplied by 30%.
Everybody gets better, but the gap between the top and second tier widens.
Consequently, in the longer term, some companies may see the “4” skill level programmer as a liability and want to begin laying off some of them. After all, the company won’t be hurt that much because its cumulative productivity is still likely to improve.
Scenario B: Tech Hoarding That Favors Machines Over Technical Talent
Companies become “hoarders” in hoarding technology. They gather more and more machine learning tools to deploy for programming,
This sets off a chain of events in which companies are laying off technical people based on what we’ve seen happen at Google, Microsoft, Amazon, Twitter, Facebook, etc. There’s not a large gap between technical talent here to consider as much as favoring machine learning applications as much as possible.
Talman Advantage #4: Better Positioning For Your Best Opportunity
The reality is that, in so many situations, that “perfect job opportunity” may not be formally listed by a company. In that instance, where some may simply fire your resume off to an HR person’s email and hope for the best, Roy Talman & Associates takes a more creative and purposeful approach.
If an opening isn’t currently available that’s an ideal match for you, we’ll discuss the kind of role with you that you would be interested in and potentially prepare and present a very specific case to that particular firm to create a unique role for you. That’s called a recruiter that goes further for you – and why you need to Talk To Talman First.
Scenario C: Overhiring, Followed By A Course Correction.
Companies with minimal backlog don’t need to do much more. After rapid-fire hiring and simultaneously overestimating the backlog, they discover that they may not need 20-30% of the people they currently have. Therefore, they simply lay off technical talent. This scenario is mostly about keeping the status quo and maintaining things the way they are,
We’re currently seeing layoffs in this scenario, where nothing changes and things get done faster. It represents a type of course correction.
Let’s face it. Some larger companies overshot their expectations and overhired based on very high projections. Even so, the largest of them had the money to overhire. How could Twitter function with 7,000 employees when they’re now functioning with less than 2,000?
The answer: They had the money coming in and the idea was to grow, grow, grow. So they took on all kinds of projects while unclear whether such projects would produce great results or not but that they might as well try it. And they didn’t have to work hard or get many wins to justify trying, with interest rates being basically zero.
Where Will We Be Three Years From Now?
People might not even try to do many projects because it would take two to three years to complete. The problem with something that takes three years? By the time year one is over, customers may not want or need it. Or it may take longer or shorter than three years, which can drastically shift planning.
So it’s tough to predict what will be useful three years from now and how to be in the correct position at the right time, working for three years to get to something that makes sense to people down the line.
We may not have a crystal ball ourselves at Roy Talman & Associates, but we do have the next best thing: Knowledge on how to keep companies prepared for the internal and external possibilities that can influence hiring the very best of the best technical talent. We’ve been excelling at that for decades.
So if you’re questioning which way the economic winds are blowing and how that might impact your hiring decisions, don’t speculate. Be confident with a plan. Talk To Talman First.