In a recent Tidbit, we talked about the era of machine learning we’re rapidly entering and its similarity to the Industrial Revolution in several ways. If we’re in a version of that period, we may see a strong economy coupled with companies laying off people due to machine learning technology, making the employees they do keep more productive than others. In that event, a company may not need nearly as many workers to achieve powerful production.
Hopefully, however, a more optimistic scenario plays out: One in which the economy adjusts very fast and companies recognize that, indeed, they can have much more productive employees. But then, they also recognize that employees can take on much more significant tasks. Not simply perform the same tasks they’ve always done faster.
If employees take on bigger tasks and more extensive projects, the implications are significant for growing consumption and the economy, even if it’s not necessarily the GDP.
See, if your software is twice as efficient today as it was a year ago, even if the hardware is the same, your cost of computing will drop in half as well. Overall, by the time you combine AI models and they interact, you’ll arrive at lower costs. We’re learning now that you can have Bard, ChatGPT or Copilot writing code instead of a $150,000 developer writing code.
Now, you may not need the full-time $150,000 developer, but what about a person who can double-check the work of ChatGPT? While that kind of individual is limited to the speed with which they can function, they can come up with ideas much faster and verify results faster. They’re not providing multiple answers. We’re talking about somebody higher up, so they know what to look for and exactly how to direct it.
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The analogy I’ve given is that if a developer with a skill set ranked as a “7” on a scale of 1-10 gets to be 50% faster and better, then that makes them a “10.”
Similarly, if a developer with a skill set of “3” on a scale of 1-10 is 30% better, it might take them to a “4”.
So, all in all, instead of developers who give you a skill range of “3” to “7,” you suddenly have developers with a skill range of “4” to “10.”
Can you ever have enough of those 10s? I don’t think so.
I recently heard one interview that discussed the notion of a “10X Developer” if there is such a person. The idea of the 10X developer is that one developer, understanding how to utilize the new tools of AI fully, will achieve results potentially 10 times more than another. Suppose this high-level expert can direct AI in creating and running test scenarios. What implications does that hold for junior-to-mid-level developers who currently perform that task?
With these new tools, we might find that there are 100X Developers, even 1000X Developers.
What’s a 1000X Developer? A developer who has robots telling other robots what to do, so that developer is controlling two layers of robots.
In other words:
- First, the developer does a task themselves.
- Next, they direct a robot on how to help them perform that task.
- Third, they direct the robot on what to do independently.
- Finally, they have the robot perform a task while they direct another robot to check that robot’s work.
This kind of developer could be drastically more productive than anyone else, not unlike the kind of extremely high-level individual we typically recruit for at Roy Talman & Associates.
If we enter a new era in which technologies enable evolved roles for your core team, will you know how to hire accurately for what the times call for and not an individual whose skills are outdated? You will if you Talk To Talman First.
Roy Talman & Associates has our finger on the pulse of what you need next and now, so you’re in proper alignment with what a rapidly changing industry calls for and stay ahead of competitors who can only focus on what’s needed in the present moment. Get proactive by having a future-focused conversation on hiring top technical talent with Roy Talman today.