How AI Is Impacting Engineering Leadership
Recap of the talk I did at the Tech Lead conference this week!
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Intro
Had a great time presenting at the online Tech Lead conference earlier this week. The topic I presented was (you guessed it), the title of today’s article: How AI Is Impacting Engineering Leadership.
I shared the two most impactful things I am seeing happening across the industry due to the effect of AI.
The insights shared are based on my view and also speaking with many engineers and engineering leaders across the industry. I also shared tips on what to do to be a successful engineering leader in 2025 and beyond.
In this article, I am sharing the recap of the talk, and you can also watch the recording of it below.
You Can Watch/Listen to the Talk Below
I’ll be doing a similar talk at the Tech Lead Conference in London as well. It will be on November 28. If you’ll be joining, I’d love to meet you there!
For everyone else who doesn’t have a ticket yet, you can get it via my link for 10% off.
Let’s get straight to the recap now.
Impact 1: 51% of Engineering Leaders View AI's Impact as Negative
This is quite an alarming data point from the LeadDev report, where they surveyed more than 600 engineering leaders. You can check my full breakdown on it in this article.
When I first saw this data, I immediately wondered: What is going on here? What’s happening? Why do we see that?
I asked many engineers and engineering leaders across the industry, both from Big Tech and Startups, and I came across some important findings, which will be shared next.
Engineering Teams Feeling Less Motivated Than 12 Months Ago
Before we get into the findings, an important thing to mention also from the report is that engineering teams these days are feeling less motivated than they were 12 months ago.
That's alarming as well. And that's also connected with engineering leaders believing that AI is impacting the industry negatively.
So, let’s go next into why 51% of engineering leaders believe AI is impacting the industry negatively + why engineering teams feel less motivated than they felt 12 months ago.
Sensationalistic Predictions About AI From Known Public Individuals are the #1 reason
It all starts with sensationalistic predictions regarding AI from known individuals. You have probably seen a lot of these across social media or different media platforms.
Example #1: Mark Zuckerberg saying that AI will replace mid-level engineers in 2025
Example #2: Anthropic’s CEO mentions AI could spike unemployment to 10 to 20% in the next 1 to 5 years, and believes that AI could wipe out half of all entry level white collar jobs.
Example #3: Amazon’s CEO Andy Jessy said AI will reduce its corporate workforce in the next few years.
So what do such sensational takes do? They are the reason that company leaders are experiencing FOMO when it comes to AI.
Company Leaders Experiencing FOMO When it Comes to AI
Example #1: Shopify’s CEO enforcing the use of AI with claims:
AI is improving productivity by up to 100x
Including AI usage as a KPI in the performance review
Demonstrating that you can’t do what is needed with AI before asking for more headcount
I shared my thoughts on this in detail in this article:
Example #2: Fiverr’s CEO telling everyone AI is coming for their jobs
Engineering Leaders and Teams Operate Within Unrealistic Expectations
So, company leaders experiencing FOMO regarding AI then trickles down to engineering leaders and their teams, needing to manage such unrealistic expectations.
Here are some of the unrealistic expectations I have heard:
Believing AI is a “Plug and Play” solution
Expecting AI to eliminate all manual work
Underestimating the cost and complexity of building internal LLMs
Assuming AI will just magically understand the whole context of the specific domain
Expecting AI to replace entire teams
Assuming AI will just work without failures
Thinking that there are no ethical, legal, and security risks
Assuming AI will exponentially increase the performance over time
This is the reason why Engineering Leaders perceive AI in a negative way, and also engineering teams are less motivated these days.
Here is the Full Visual Overview
The people who feel this the most are the ones who actually do the work.
It starts with sensationalistic takes, which are the reason why company leaders experience FOMO when it comes to AI, and then engineering leaders and their teams need to operate within unrealistic expectations.
So what to do?
I’ll give advice for both company leaders and engineering leaders next.
My Advice to Company Leaders and Engineering Leaders
Company leaders
It all starts with setting the right goals and not letting FOMO get to you
Don’t try to do full-scale “AI transformation” all at once
Focus on creating a good culture
Engineering leaders
Make sure to educate yourself on how others are utilizing AI tools
Be confident and manage expectations correctly
Don’t just go straight to saying yes to requests like “We need to start using this AI tool or we’ll fall behind”.
Small experiments and then measure the impact it has on productivity
You need to own the AI Strategy and not wait to be “looped in” on it.
More tips in this article:
Advice Particularly For Engineering Directors, VPs, and CTOs
Don't wait to be looped in on AI strategy, instead, you should be owning the AI strategy. You are the strategy.
This is advice from
, Product Leader at OpenAI.
We did a recent collaboration, and this was one of the most important insights mentioned in that article.
You can read the full article here:
Also, he mentioned that the Engineering strategy is actually the same as the AI product strategy. So you should be the one who is dictating the way AI is used across the org.
The reason for this is that engineering leaders understand the whole cycle. And especially the “how” part is very important and can be the difference between doing something in 3 days or 300 days.
And nobody else (outside of engineering) can understand that.
What you need to focus on as well is the what, when, and the why. That is very important, and that takes a bit more business and product understanding.
Anyway, this is very important in 2025 and beyond -> that you, as an engineer or an engineering leader, become more business and product-minded.
And also, this is a really interesting image (below). BOTH the execution and strategy are moving closer to engineering.
From Miqdad Jaffer, OpenAI's Product Leader:
"I genuinely believe AI product strategy is going to be the new leadership skill for engineers, CTOs, and technical leaders. Why? Because you already know how to build.
It’s time you develop the strategic skill so you can answer “what”, “when”, and “why” to build, so you can lead the whole ecosystem."
Impact 2: Engineering Roles Are Getting Closer Together
Now, let’s go into the second impactful thing that I see across the industry. I see engineering roles just getting closer and closer together.
For example:
Engineering Managers to be expected to take on Staff Engineer roles
Staff+ Engineers be able to take on manager hats if needed
Architects → taking on Staff Engineer role or manager role if needed
And a similar trend for PMs and Engineers. The role “Product Engineer” is getting more and more popular.
So, as I mentioned above, becoming product/business-minded is going to be more and more important. And I believe the roles are just getting closer and closer together + the line is going to get more blurred as time goes on.
Here is Why:
We’ve seen layoffs within multiple companies
Fewer people in the company, more is expected from the existing people
Amazon’s initiative to increase the ratio of individual contributors to managers by at least 15%
The tools for development are just getting better and better
The engineering roles (titles) in the future will be more blurred as time goes on
Being good at many things will not be a nice-to-have, but a must-have.
I’ve already predicted this trend in this article, and you can read more insights there:
What to Do to Be a Successful Engineering Leader in 2025 and Beyond?
The more things are becoming robotic around us, the more important human-related skills are going to become.
Leadership, teamwork, good communication, being a great person to work with, empathy, and overall emotional intelligence.
All of these skills can’t be replaced by AI, and you being good at it is going to be immensely valuable to the organization.
And the second part is being good at solving problems: being pragmatic, being resourceful, having a good network of people you can talk to, and ask questions, and also having a list of resources that you can refer to anytime.
And obviously, utilizing AI tools, business understanding, as we mentioned before, and also having a deep understanding of relevant topics.
This is also common these days → I see people coming to the industry with a shallower understanding of engineering fundamentals than 10 years ago.
So having a good understanding of engineering fundamentals is going to make you very, very valuable.
To Help You With This → List of Resources to Becoming a Great Engineering Leader in 2025 and Beyond
Last words
Let’s end this article with the following:
AI is definitely having an impact on Engineering Leadership, but you've got all the resources and tools you need to be successful in 2025 and beyond in this article and in this newsletter.
You got this!
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