[00:00:00] Hey guys, and welcome back to the Easier Said Than Done podcast. Today I want to talk to you about the latest layoffs announced by Microsoft just a couple of days ago in Seattle, well across the global workforce because there is a lot of media spin around it and I wanna just help you
understand what's actually going on, and I will walk you through my process of figuring out what's real and what's not. Because we live in a world with a ton of spin and a lot of BS out there, a lot of marketing, a lot of poor journalism, a lot of sensationalist, hype based reporting.
And I will show you how that's done in most blogs. So, just as a little bit of context Microsoft earlier this week announced that they're laying off about 3% of their workforce globally. Which is approximately 6,000 employees.
And the media's saying that software engineers and programmers were the most affected by these job cuts. Technically correct, but we will go into that in a little bit more detail. Technically correct, but not by a long shot. Most of us read stuff like that, myself included.
Welcome to Easier Said Than Done with me, Zubin [00:01:00] Pratap, where I share with you the tens of thousands of dollars worth of self development that I did on my journey from 37 year old lawyer to professional software engineer. The goal of this podcast is to show you how to actually do those things that are easier said than done.
And the media's saying that software engineers and programmers were the most affected by these job cuts. Technically correct, but we will go into that in a little bit more detail. Technically correct, but not by a long shot. Most of us read stuff like that, myself included.
We read "most of" as "all" or "largely", or, you know, SUBSTANTIALLY all software engineers. Right? But we'll go into that in a moment. The key point here is that. Despite the headlines focusing so much on AI replacing software engineers, the reality, and let me share the screen with you from the reports
the reality, as you can see from the screen share is that it's actually 53%
so just to put that in context, 53% of people are in engineering related roles, right? Software engineering [00:02:00] related roles, which means 47% are not software engineers. Effectively that's half right. Now, this 3% thing is like a rounding error.
To me it's half is software engineering, half is not software engineering. So who are these people, right? Who are these half that no one's talking about? Why are we all obsessed about the impact in software engineers when half the layoffs, and if you remember in 22 or 23 or whenever it was.
Oh no, actually it was 23, 24 I think when Google and the others were laying off tons of people, it said, oh, it's, you know, mainly software engineers. From memory, I think I remember doing the research on that one. It was less than half were software engineers. That wasn't AI related. That was just post pandemic downsizing because they'd overinflated their numbers during the pandemic.
So you know, less than half of those were software engineers. This is how the news and media wanna report it. And what is more scary than ai, replacing a profession that is considered to be very hard, that is considered to be extremely difficult mentally and stuff like that, right?
It is. Software engineering is hard and you know, [00:03:00] before that I was a lawyer. That's hard too. Being a doctor is very hard. Heck, these days being anything is very hard because it's really stressful to do any sort of work, right? So why is it that all the emphasis in software engineering and no one's talking about the 47%?
I haven't seen any breakdown about who the other half is. Like, who are these people? What kind of work? Right? Because the media loves to sensationalize stuff . That's the reality of this. This what's going on here, right? If 53% of people are laid off, you know, make it the largest affected department. Now, when we read things like largest affected department, yeah, okay, 53% is technically mathematically the majority, but 47% is not
a small amount. Right, and that makes up everybody else. Right now in a company where most of the employees are software engineers, it is not surprising that when you cut it proportionately, most people will be software engineers. It's just math. It's not that there's something targeting software engineering specifically, it's just math.
If, if 50% of the [00:04:00] company is software engineers and there's a 50% reduction in head count. There's gonna be a 50% software engineering hit, right? Like it's just math. So it's not specific to software engineering. Now of course, the media's gonna say, well, you know, it doesn't come as a huge surprise. Microsoft Satya Nadella, you know, 30% of the company's code is now written by AI.
Whether that's true or not possibly true, but keep in mind, software engineering is not just about writing code. I've been saying this for years. It's, it's not about writing code, but. If this doesn't come as a huge surprise because Satya Nadella said this, about 30% of the company's code now being written by AI, I'm gonna say it came as a huge, HUGE surprise to the 47% who are like, Hey, we don't write code.
Why are we being let go of? This is the way I'm encouraging you guys to think. Okay, if it's no surprise that 30% of the code is being written by ai, therefore shouldn't all of these people have been software engineers? Why is half not software engineers? Right. I'd say that's the huge big surprise.
Right. So this is how the media [00:05:00] connects an other story with this story and makes it seem connected. Yes. A ton of code can be written by AI, right? A ton of copywriting can be done by ai, a ton of video. I use AI for video editing, right? It's going to affect all knowledge work, and that's my number one takeaway for you guys today.
I want you to understand that this narrative that is only software engineers, that is at risk is very misleading. AI is fundamentally reshaping the landscape for any knowledge work from project manager to sales, to law, to medicine, to HR, creative roles, all of them are being affected. So don't get sucked in by this.
Oh my God. Software engineering is risky. Any knowledge work today is risky.
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this narrative that is only software engineers, that is at risk is very misleading. Oh my God. Software engineering is risky. Any knowledge work today is risky.
It is going to be changed by ai, but I have some good news for you in a little while, right? Don't think that software engineering is particularly risky. I would say software engineering is a little bit less risky than the average job because there are things you can do about it to improve your skills.
Okay? There are things, there are sort of value niches you can generate for yourself to protect yourself. But let me be really clear. AI is going to reshape all knowledge work, not just software engineering. As you can see [00:07:00] from this sort of rubbish, kind of, you know, the way they, they present this right now, if you look at the actual full story which is linked to, in that one, that's this one, right?
And it talks about the same thing. 6,000 workers, about 53% you know, is, is gonna be software engineering roles, right? And this, again, they've connected it to the code. Makes no sense because if, coding is what's being replaced by AI, why are 47% of the people who got, laid off, not coders, right?
Here's what it really comes down to. It's trying to reduce redundancies while empowering employees to spend more time, right. And more meaningful work. I think that makes a little bit more sense. Right. 'Cause I see this at work. You know, in, in how I work as well is because of AI making me a lot faster,
since I know what I'm doing with the engineering, I can use AI to get a lot faster, I can get more work done. On the other hand, what happens to the smaller companies that aren't growing where you don't need more work done? There are lots of companies, I've worked in them in my past where the growth is not so huge
that you need a ton more work done. So what do you do in that situation? Yes, you will reduce the headcount because wages are the most expensive part of a [00:08:00] company's profit and loss statement, for most companies it's the single largest expense item, right?
Labor.
And so if your company's not growing a lot. And you don't need 10 people to do the job anymore because three people plus AI can do it, which is what efficiency means. That's what productivity is, right? More output of work for fewer units of input. Then that's why they're gonna lay off people is because the company's not growing that much.
They don't really need to produce more and more work and velocity outta their employees. All they need to do then is cut headcount a little bit, replace some with ai, and then have the humans manage the rest of that with AI and themselves. 'Cause they're now able to be more productive. Like it's just math when you think about it, right?
And, and that's what it comes down to. Now here's the good news, right? AI is now pretty mainstream, right? About 75% of global knowledge workers. And by the way, I'll link to this. This is a really great article. Interestingly, ironically, perhaps it is also from Microsoft, right? Where it talks about how this is from 2024, though as you can see, it's, it's a whole year old, but nothing's changed in [00:09:00] my view, other than the numbers, the trend.
The trend line is still very clear, right? So AI is used by 75% of knowledge workers. This was in 24, and it continues to be the way now, right? AI is helping workers manage workloads. Because the reality is, I think whether you're in a software engineering or any other profession today.
Work is kind of overwhelming, right? It, there's a pace, there's a volume, there's all these channels of chatter, there's email, there's slack, there's this, there's that. It's kind of overwhelming and people are feeling a little bit burnt out by that. In fact, if you look for the word burnt out here, you'd see there you go.
You know, 68% of people are saying they're struggling. The pace of work, the volume of work, 47.6%, again, that's almost half feel burnt out. Email overload. That's for those companies that use a lot of email. Other companies use things like Slack and Asana in addition to email, and that's a lot, right? Emails are read under 15 seconds.
Typical person is read about four emails for every one they sent. Like it's huge amount of data coming in and out, right. Meeting and after hours work are holding study at the post pandemic highs you know, [00:10:00] 60% of the time in the, like, it's pretty serious stuff, right? It's pretty, but AI is trying to help reduce all of this.
So whether it's the tech industry or other industries that are all undergoing transformations because of the arrival of AI, quite similar to the transformations that happen, you know, in the, in the late nineties with the arrival of the internet. I was around for that one too. Yeah, I'm that old.
Or before that in the eighties with the arrival of the pc, I was a toddler at that time. Right. So, you know, business processes, the needs of departments are being redesigned. Heck, I remember a time when you know, in in the law firms you had pools of typists and stenographers who would do the typing because the you know, senior associates and partners, you know, from the seventies and eighties and nineties weren't used to typing.
They typed with one finger, right? And now you don't really see a lot of that anymore because most people have now grown up with typing as teenagers. And so they don't, they're fast typists and so they don't need that. So there is reshuffling that happens anytime technology becomes mainstream and AI is becoming mainstream.
AI is definitely automating. Routine, [00:11:00] repetitive tasks. It's helping us draft things. It's helping us check our email, it's helping us summarize documents. It's helping us put together the basic framework of plans that we then, so now that we have the structure, it's done some of the structured thinking for us now we just fill in the meat and potatoes into it.
And so this work shift increases velocity. It's not just in engineering, it's across all knowledge work, right? A lot of AI agents, the more AI start to speak to each other and make independent decisions, they're able to do things like, you know, note taking at meetings expense, automated expense reporting, sales, lead generation handling sales calls, right?
With, with synthetic AI voices, all of this is now starting to happen. So all that, all that means is across the board, AI is changing the way we work, but there are huge skills and opportunities. So if you look at let me see. If this would, yeah, here you go. So there is genuine talent shortage, right? This report finds genuine talent shortage.
About 55% of leaders are, concerned about how they're gonna fill roles. And you know, as someone who's hiring this continues to be [00:12:00] on my mind as well. It's hard to find good candidates, especially good candidates for where you need to go. 'cause you as a manager, I'm always thinking about.
Where I need to be in 12 months, 24 months. I'm trying to skate to where the puck's going to be, not where it is right now. And that means I'm trying to anticipate what skills will I need in 12 months that I can start nurturing today. And, you know, the reality is having AI skills helps. And now what does AI skills, don't get misled by all this AI skills simply means depending on your job.
It, it quite simply comes down to can you use AI to make yourself better and faster at your job compared to your competitor. Now for some people, chat GPT is enough, right? For people like me in software engineering, that's not gonna be enough. We need to be able to use it in our development environments.
We need to be able to use it in other ways, in, in our IDEs, in our terminals, et cetera. Right? So it really depends on your job. There are people who need to do a lot of Excel spreadsheets. They need to be good at the AI interfaces that do good Excel, you know, help them with Excel, for example, right? So it's different.
There are specific tools for different industries and domains. So AI aptitude is definitely becoming an important part of experience . Now this [00:13:00] report had something interesting. I think it was 70, I wanna say 71%. Oh yeah, here we go. Right. So 66% of a leader say they wouldn't hire someone without AI skills.
Again, like I said, trying to think forward, 71% said they'd rather hire a less experienced candidate with AI skills than a more experienced candidate without them. Now, this is a tricky one because I think it would also depend, depend on the domain and whether this person's an individual contributor or not.
For example, executives are less likely to have full on AI skills and someone more junior to them simply because the age and the time. So for them, you know, in, in key strategic decision making roles, I'm sure the experience counts more than their ability to do AI because they'll simply get someone in their team to do that for them, right?
We see this all the time in our work. The more experienced people may not be hands-on on the tools because they haven't gotten updated skills with the latest tools, but because they have all that depth of experience and their team has all these abilities with the tools, they're able to function really, really well because
the executives or the key decision makers, key skill is in judgment and, and, and decision making [00:14:00] and managing the team and so on, right? And this is the big difference between being a leader or a manager and an individual contributor, you know, in, in, in that hierarchy, so to speak. So that's why I guess junior candidates may have an edge.
77, 7% of the leaders say you know, early in career talent will be given greater responsibilities. What that actually means is that, you know, younger folks can get more done because of AI and therefore they'll be given more, greater responsibilities. I don't believe this is the full truth though, because from what I'm seeing, what's lacking, what's a real rarity these days with AI is actual critical thinking and judgment.
Right. And within three to five years in, into your career, you will need to have strong, critical thinking and, and judgment skills. And if you're relying on the AI to do that for you, you're not building that muscle. So, you know, I, I personally. You know, while may, maybe a lot of leaders say this, I believe that's a mistake.
It's not how I would do things. I would want people who, if there was an electricity outage and they don't have access to the ai, they can still make decisions and know what to do and do the job manually if need, when need be. Like, that's what I'd be looking for, [00:15:00] you know? So. You know, that's a sort of an overview of the skills and opportunities in this new career landscape.
And, and I would encourage you guys to think about AI as a potential career accelerator, not just a threat. And it's not just about software engineering, whether you're in engineering or something else. If your job relies on a computer for at least 50% of your duties, such that if you didn't have a computer, you would be prevented from discharging your duties from doing your job.
You know, then you're probably a knowledge worker. That's my definition by the way. It's just my rule, right? If, if, if you're not able to be productive in your job unless you had a computer at least 50% of the time, then you're probably a knowledge worker. And I would say you know, rather than worrying about AI replacing your jobs, which it will in some senses, in the sense that it could replace part of your job, it's not likely to replace your career though.
And this is why I keep emphasizing with my students in the Inner Circle program. There's a huge difference between a job and a career. Right. A job has certain functional definitions. You could do the same title in different companies, but the [00:16:00] job may be slightly different. So, so jobs can be quite different, right?
Your career on the other hand, is a collection of your skills and your impact, and so that you can absolutely control about. That's what you really need to be thinking about, not a specific job. And you can use AI to significantly enhance your skills. Whether you want to be an an engineer or something else, it doesn't matter.
But even in engineering there is a huge, huge appetite for people who can do less code but have more impact, and engineers are very well equipped to do that because. Personally, you know, I subscribe to the school of thinking that engineers should be lazy. We should try and avoid writing code as much as we can.
That's my personal philosophy as an engineer, right? We want to write the least amount of code as we can. If we can solve problems without code, that's better, as long as you solve the problem well, because code should only be used when it's the best solution available for a given problem. When it's not we shouldn't do it because there's a lot of maintenance burden, there's a lot of effort, there's a lot of time, and it's an expensive resource and so on.
Right? So, I would say companies are clearly trying to, in invest in upskilling [00:17:00] employees. The many of them are giving them access to AI tools. Some people won't some companies won't. And the companies that do try and embrace AI will pull ahead simply because of the productivity boost that AI could do.
But you know, apparently at the moment, I think it was, you know. Oh, here we go. It's right here. You know, about 45% of US executives are not currently investing in AI tools. That's, that's a pity, but I think that'll change. But, you know, this happened when the PC was happening as well. This happened when websites were a thing.
You know, initially many businesses and companies are like, why would we ever need a website? You know, what's, what's that gonna do for us? This is in the mid nineties. I remember this, right? So, you know, that's just, that's just kind how it is. In terms of new hiring imperative, here are some graphs.
Aptitude does take center stage. These are sort of some of the statistics we talked about. 66% of leaders would not hire someone without some AI skills. It's unclear what AI skills are, so don't get too het up about this stuff. Don't get, don't leap into action about it. AI skills means very, very different things, right?
For software engineer, AI skills means something completely different. For an AI software engineer, AI skills [00:18:00] means completely different things from a regular software engineer and so on and so forth. It's an endless variety of what's AI skills mean. So analyze it in the context of your career and your career goals, not just your job, your career.
Remember there's a big difference.
Look, I, I think I wanna leave you with this, right? Ultimately, when you look at, you know, articles like this, you know, 53% of those are laid off software engineers, largest affected department. And it's because Satya Nadella says that 30% of the company's code is not written by ai.
No, that's not what happened. Again. If that, if, if it is all about the code, then shouldn't this be much higher than 53%? Shouldn't this be 90% laid off were engineers? No. Instead, almost half were not engineers, right?
Like it's, it's literally staring you in the face. What happened to that half? If they're not coders why did they got laid off? Laid off? Why did they get laid off? You know? It's because it's not just code, that's just the sexy pieces that the media outlets wanna focus on because it's fun to talk about a complex profession that people seem to, you know, put on a pedestal and say even those [00:19:00] guys are at risk.
Like, that's makes great news, right. But it doesn't make for reality. The reality is all knowledge work is gonna be affected. If you are a knowledge worker, you are going to be affected if you're not already. So you might as well get into the part of the world where you believe you're most future proof. I personally believe having tech skills, I.
Whether you end up becoming a software engineer or not, doesn't really matter. Having those skills and that way of thinking will futureproof you because not many people are gonna do that, have those skills. In addition to everything else, it's like there was a time, a big time in human history, several hundred years when only a small percentage of the population could read.
They will literate, and those that were literate got really good opportunities for generational wealth for a long time. Now we take literacy for granted in much of the developed world, but it wasn't like that. You know? And in, in many senses, being able to work with code, being able to understand or read a little bit of code, being able to understand a little bit of how computers are programmed, being able to use AI in a slightly more advanced way than their competition
[00:20:00] these are all competitive advantages, right? These are all forms of literacy that sets you apart in the marketplace, and you've seen the data, it is of interest to the hiring side.
So with that said, I just want to emphasize to you guys, don't go by everything, the news says, without being critical in your thinking.
If 53% of people are software engineers, that means 47% of people that Microsoft laid off weren't software engineers, which means it can't just be because AI is writing the code because that 47% of people weren't writing code. So then why did their jobs go right? Simple critical thinking. Alright guys, hope you found some value in this. Links will be in the show notes and if you are looking to transition into software engineering or building your own tech startup, or you just want to acquire engineering skills to, to future proof yourself, reach out to us.
Brian and I do the Inner Circle program. It's very small. It's kind of by invite. Because we also work full time and we don't want to have a ton of students. We wanna keep it really focused on a few so that we can get outstanding results. Links in the show notes. Feel free to, to reach out. We are happy to help if we can.
And if we can't, we won't pretend that we can either. Alright, [00:21:00] see you next time. Take care guys. Bye.
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