Spoiler alert: career shift ahead!

“Hey, didn’t you do a pivot to AI some time ago?”

Good memory! Indeed I did.

I willingly threw myself into the world of Generative AI, fully. I was excited. I thought I knew what I was getting myself into. Of course, I knew there is a hype cycle going on, I knew there would be hyperbole and grifters, but that was the challenge: I’m rational, I can cut through this! I can dig and find what’s real and what is not! I have a PhD for crying out loud, if that equips you with anything, it’s the skill of critical thinking and rigor.

To quote myself in my announcement post:

This is going to be awesome.

I was wrong.

As it turned out, after only a few months operating so close to the “heat” of a booming industry, I was anything but energized.

Expectations are enormous; promises border-line absurd; and reality extremely hard to evaluate.

I found that a lot of this industry runs on beliefs, echo chambers, and FOMO. Everything is presented as a constantly moving target. The moment you settle on some strategy in one area, some new product launches, or some vendor’s executive makes an even more outrageous claim on a podcast, and the circus continues.

Some may thrive in an environment like this. I do not, as became painfully clear.

The deeper I dug, the more disillusioned I became. I devolved from an optimistic, trusting person to feeling like Zeffy the AI Snake-Oil Salesman Slayer, drowning in a dystopia built on poorly-disguised doomsday-cults masquerading as shamelessly exploitative unicorn companies.

Once I noticed it started to affect my personal life, I knew I needed out.

It happens. It’s not anybody’s fault. I’m alright now.

We live and learn.

So, what’s next?

I did some soul searching: what gives me energy, what do I enjoy? Am I going to roll the dice again, or take a different approach this time? While if the perfect opportunity would land on my lap I likely wouldn’t say no, let’s not assume that scenario.

Thus far, whenever companies hired me as a Head Of, Director, or VP, I was made responsible for a part of the organization and got to work on interesting engineering leadership challenges:

• Adjust the organizational structure and size
• Identify and coach a next crop of leaders
• Increase product mindset and change engineering culture
• Increase the pace of delivery
• Establish practices around recruitment, people growth, incentives, goal setting

I was somewhat shocked to realize that over the past decade and a half, I’ve now done this in eight different companies, ranging from small start-ups, to scale-ups, to organizations part of large multi-nationals. Every time I saw some things that were unique, and many that were not. I saw similar patterns emerge, and familiar traps. I applied and wrote about what I learned, and tried new things.

While I never joined any company to leave it, over the years I had been around. As a result, I had gotten skilled at being airdropped into a new organization, quickly grasping the lay of the land, and starting to contribute.

Perhaps it made sense to double down on this skill and experience. While I never thought I’d say this, perhaps the answer was...

Consultancy

I love helping people and organizations with their problems. I’ve seen a lot by now, so I bring experience to the table. I’ve actually done the work, so should be credible. I’d like to believe I communicate well. I’ve established a network over the years. And essentially all my work engagements have ended on a good note.

Sounds like a pretty solid foundation for starting a consultancy business to me.

This is part one.

The second part is that I love writing about all this stuff. Over the years I’ve written many dozens of essays and articles. Many of which have made an impact on people’s approach to their work (or so they claim). Many have suggested I should write a book, or otherwise commercialize this somehow.

So this is the second part — the potentially scalable one, which should nicely synergize (look at me, whipping around managementese) with consultancy work.

I’m in the process of restructuring my content and publishing it on a rebranded site, which I think I can be a valuable resource for (aspiring) leaders in tech. One worth paying for. More on this soon.

As I do, I shopped these ideas around a bit. The most common question I received is: how can I help?

Obviously, the most obvious way to help me short term, is to hire me as a consultant. So, let me abuse you, my audience, for a bit of a pitch:

Do you need my help? Would you, or people in your organization benefit from leadership coaching or mentoring? Are you looking at a tough reorg, struggling to keep people on mission, and could use some fresh, outside perspective on an interesting management challenge? Do you have a temporary engineering management gap to fill? Let’s have a chat.

The second way would be to tell your network about me, share my content and services. This can also take the shape of a recommendation on LinkedIn.

The third way will come a bit later, as I'll launch something around my writing content soon.

Thank you for being on this journey with me. Interesting times ahead!

For the past years I’ve been spending a lot of my time thinking (and writing) about the human side of engineering. Topics like leadership, management, psychology, humanity. The trivial things.

But I cracked that nut. Done. There’s just not enough space in this post to fit the answer.

So it was time to move on to something actually challenging.

Since the opportunity arose, I decided to switch my role to become Head of AI Engineering. While there are definitely still management aspects to this role, only a minority of subjects to my management shall henceforth be humans.

Bow before me, ye AI subjects.

I wonder if at some point such jokes will be considered speciesism. I may be setting myself up to be canceled or worse in a few years. If you never hear from me again, call my wife.

In all seriousness, the role is all about accelerating the company’s transition to fully embrace AI in every sensible way. In the product to the customers’ benefit, but also internally. A big part is to advance engineering practice using AI tools, and ultimately to leverage AI in every part of the organization. Quite the nut.

One of the (many) intriguing aspects to explore in this space are that LLMs (Large Language Models) have a surprising amount of overlap in behavior with humans. More so than any “traditional” computer algorithm thus far.

Still, some of you will say: “LLMs ain’t people, they’re just stochastic, probabilistic token predictors; fancy auto complete. What’s the point of comparing them to humans?”

Of course, you would be right. Academically. But who wants to be academically right? You can dismissively describe many things in a similar fashion: computers are just fancy calculators. Humans are just thermoregulated biological units optimized for pattern detection. Burn! Oh no he didn’!

While all technically accurate (let’s say), not super helpful.

Ultimately, the question is not what it is, but how we use it in valuable ways. And AI — love it or hate it — has value to provide.

Working more with LLMs over the last months has clarified a couple of left-over issues I’ve had with humans.

One example: the challenge of context window management. LLMs have a hard cap in how many tokens (think: words) can fit into a conversation. This is called their context window.

Humans have similar constraints (although it’s harder to identify the exact limit): how much stuff can we productively keep in our heads? How much context do we need, what is too much, when do we start to get confused? With LLM it’s super obvious we have to strategically manage this. I would argue that with humans we do too, but do we ever really think of it that way? Thus far, I have naively argued that “more context is better.” But is it? If you keep dumping more context information on people, do they not simply get lost in TMI? Perhaps we should also more strategically curate this? 🤔

Not my problem anymore. I’m all about AI now.

You get the point, though. There’s stuff to learn here. Both on the AI side, the human side, and their overlap.

Welcome to my (new) world.

This is a head (of AI)’s up that I will be talking, writing and videotaping myself a lot more talking about AI going forward.

And obviously, you can also expect a ton more absolute banger AI jokes. None of them LLM generated, because thus far LLMs are terrible, terrible joke tellers. That’s why the world still needs me.

Still.

Anyway, that’s some context for your window (see? banger AI jokes).

I hope you’ll join me on this journey. Nevertheless, if you’re somehow AI allergic, this may be a good time to (mentally) unsubscribe. Your loss though. Because I repeat: AI jokes. I mean come on.

This is going to be awesome.

Meta comment

Since people are going to ask: none of this post was written by AI, although I will admit I did have ChatGPT generate a first version of it.

After ChatGPT’s first try, I proceeded to delete 99% (I kept “the human side of engineering” phrase at the beginning — I liked that), and crafted everything by hand. Like an animal. I then had AI critique it — devil’s advocate style — but it completely missed my signature sarcasm — so no valuable dice.

Famous last words, but I intend to keep it this way. I think (based on what people have been telling me to my face) that the reason everybody (and I mean everybody) reads my stuff is because it’s me. I am (and I quote:) cool. While little of what I’m proclaiming in these posts is technically new, what adds value is my particular way of framing things, with my signature blend of hilarious dad jokes. Try that, ChatGPT. You personality-less... LLM, you.

That said, the bland draft that ChatGPT produced did encourage me to finally write this post. I find this to be a common pattern in what AI tools have to offer: even if you don’t end up using it all, or even a little of what they produce, they are a surprisingly effective way to have the energy to just start, to do things you would otherwise not even attempt. Courage.

AI. Quite the nut. Let’s get cracking.