If you have opened any social media (or media in general) you already know what I am talking about: OpenAI launched a new model and people found out pretty quickly some cool and weird and scary way to abuse it.

It’s virality at work, it is exactly why people use social media, I didn’t give it much thought (also because I still don’t have access to the model 😕).

And then, as it’s customary, the outrage machine started: people keep shouting about the theft of IP, the hypocrisy.

You know already what I am talking about, this is still people jumping on the bandwagon to get some likes by showing a contrarian view.

So let me jump on this bandwagon!

Howl's moving castle is by far my favorite movie (with Spirited Away being a close second) from Miyazaki.

It’s the first “western” movie he produced and the first “political” movie since the time of Porco Rosso (another delightful quirky movie).

If you lived under a rock so far, go watch the movie because I don’t want to spoil the plot to you.

I was never a big anime fan, contrary to what you would expect from my cohort, but I had watched my fair share of famous and high quality anime series (Ranma 1/2, Cowboy BeBop, Neon Genesis Evangelion, Trigun).

As I started watching the movie I had no baseline about Miyazaki but I knew what “good” looked like.

I was still blown away.

The many characters that you end up loving, the complicated quirky story, the redemption arc, the animation, the pacifist message delivered in an Orwellian way (Miyazaki wrote this movie specifically as a reaction to the U.S. invasion of Iraq in 2003).

You’d think I would be outraged by the meme generate with AI that steal the vibe of those movies.

Well I think that outrage is silly.

Everything is a remix

The story is a remix

When you stop and think about it, isn’t this movie very similar to another one?

Isn’t Disney’s “the Beauty and the Beast” essentially the same story plus a touch of Orwellian forever war?

And isn’t that movie based on a 18th century french novel?

Isn’t that novel based on a folktale classified under ATU 425?

The distinct design has been remixed

There is no doubt that one of the most distinctive traits of Miyazaki are his characters, so recognizable and quirky.

If you have watched Scavengers Reign you might get the feeling that there is a lot of Miyazaki in it, and you won’t be wrong since the creator openly said that he took inspiration from the Japanese master.

And I would argue that even Neon Genesis Evangelion has a lot of contact points with Miyazaki.

So what’s your point?

What makes Howl’s moving castle (and Spirited away, my Neighbor Totoro, Porco Rosso, Kiki’s delivery service) unique and special isn’t the design, the story outline or the music.

Making a movie is about putting all those things together with the right rythm and editing, breath life into those inanimate characters so that I care about them.

It’s not about the tool, think about how minimal and still great is XKCD, this is just a distraction so that OpenAI can hype its valuation and raise more money.

Even if any rando on the internet can produce something similar with AI you have remember the words of Paul Cézanne: "A work of art which did not begin in emotion is not art."

You can never copy Hayao Miyazaki because you cannot distill why you love those movies.

You just do

P.S. For the “but is copyright infringement” folks, I am not an IP lawyer and I am not a Sama fanboy. If OpenAI broke the law they should pay but corporate law drama isn’t what interests me.

If that sounds confusing, here’s a video of Gary:

We had the opportunity to ask Serge van der Zweep about his dogs and his methods of training and he said something that I found surprising.

The first step to raising world champions is to start when they are puppies: you get them close to a flock of sheep and see which one of those pups is obsessed with sheep. All the others we train for something else (border collies make for great agility dogs) or just not train at all and sell to some dog lover.

A popular notion is that you need to train 10,000 hours to become an expert at something, however, that is a myth, and even the author of the study that supposedly proves that in “nature vs nurture” the winner is nurture, wrote a rebuttal.

I think instead that empirical evidence shows clearly that the secret to becoming great at something is an obsession.

There is no doubt that to become great at something you need to practice over and over again, this is how the 10.000 hours myth begins, and sometimes genetics play a role (in basketball you need to be tall, in horse riding you need to be short).

Practice and genetics alone are not enough to explain the astonishing difference between an amateur and a professional in the same field, or between a world champion and a lesser professional.

Otherwise, any tall person could challenge LeBron James or Michael Jordan given enough time. No, there is something else, and that something else is the willingness to push through when it sucks so badly that you want to quit, to make sacrifices that normal people won’t even consider, the drive to be the best and beat all your challengers.

Max Verstappen is arguably the best F1 driver alive and someone who spends an incredible amount of time playing video games. Which video games do you ask? Of course racing games, he just drove a 3-hour nightshift of sim-racing right after winning pole position at Imola.

He is not alone, Alessandro Nesta (one of the best defensive players on the Italian National team) famously strained his left thumb tendon for playing too much football on his PlayStation.

If they were not famous sports players we would call them nerds, wouldn’t we?

And yet, their being nerds is exactly what makes them great. They are so obsessed with their sport that their brain just can’t switch off.

Obsession is the best sign of true passion

It is very common in my job to have conversations with many people about what they want to do next in their job or life.

Oftentimes people try to answer the question rationally, they look at what other people are doing or what is the best way to make more money.

That is a possible way to answer the question but not, in my opinion, the way to have a successful and fulfilling career.

What I look for instead is: what kind of boring work do you naturally gravitate toward? For example, if your manager is away, do you naturally make sure that your team is still working fine? Or do you focus on something else?

I could give you a lot of explanations of why I ended up in the job I do, but you will understand better why I am in management just by playing an escape room with me and observing how I will get the team in line to try to beat the best time.

We should remove the stigma from being obsessed and take back the power of being a nerd

Taylor Tomlinson is one of my favorite standup comedians and, in one of her specials, has a line that I love:

A few years ago, when I worked in that big company you know about, the company started hiring many senior management from outside and asking them to make some swift changes with only a couple of months of onboarding, essentially on gut feelings.

At the time I thought it was madness, so I asked my manager why he was doing that and his answer puzzled me: “Well if they can’t make those decisions fast, what did we hire them for?”

I gotta be honest, I didn’t find that answer satisfying or useful. I thought it was just a defense of lazy management practices.

Until it was my turn

A rule I had to learn the hard way, and that I invite you to internalize is:

If they are hiring you, an expensive senior professional (manager or otherwise), they need someone to come in, fix something and do it quickly.

No company hires external (expensive) senior talent if they don’t a) have something burning and need a “Mr. Wolf” or b) an internal staffing issue so they can’t rely on their people to fix it.

This is why it’s so hard to hire someone senior and why there are so few openings for those jobs (and many being confidential to begin with).

Also why the process of being hired as a senior professional is so weird, often based on “vibes” or recommendations, and sometimes infinitely long.

It’s not about you specifically, it’s about understanding if you have experience fixing the problem they have (and often don’t even tell you about), if you can onboard quickly (you’ll get one month to settle in, maybe), if you are aligned with the direction (that is most likely new, certainly confusing), if you are compatible with the team (they like you).

And if the above wasn’t enough, use a process often ad hoc and done by people who are probably stressed, tired, and confused as much as you.

In hindsight, it’s obvious why it’s so easy to see many new executives, directors, and principals fail miserably and be shunned by their organization. Pulling this off is hard, people expect you to be their lord and savior and many organizations are generally bad at selecting the right people but quick at crucifying them.

So what happened when it was my turn? Did I trust my gut and make swift changes knowing little about the organization? Did I betray the younger me?

Yes, yes I did.

Not because I was wrong at the time, but I now understand that those swift big decisions look big and swift only if you make the wrong ones.

If you are the right person, those big decisions are obvious and the speed is needed to help the people drowning in front of you. They want you to make those decisions.

In a way, I think that we, knowledge workers, tend to overestimate the impact of talking a lot (are we wordcel?) and underestimate the impact of doing a little.

All this to say that that scene from Indiana Jones, is everything you need to know about trusting your guts.

I found a new job, which job isn’t that important for now, if you follow me on LinkedIn you’ll find out.

And I thought it would be nice to share what happened in the last 9 months in which I have been (with various degrees of commitment) open to work.

Before we talk about the numbers, let’s have a real talk

Why nine months? Haven’t you been unemployed for just 3 months?

Let me share a public secret with you: when a layoff is coming, especially in the particular way mine came to be, the company's senior management knows months in advance. We tried our best to avoid the worst, I think we did a pretty good job at that, but I decided immediately that I would be leaving, impacted or not.

So I started looking around early, knowing that for senior positions getting an offer, especially in an economic downturn, might take forever.

I didn’t have any economic problems and I was objectively in a privileged position when compared to many other folks out there.

Yet I would be lying if I said that the past months have been easy.

I started working at age 15 and never stopped, so being in the layoff limbo first, then garden leave, and finally officially unemployed, was the most maddening experience in my life.

What do I do? How many Netflix and Disney+ series can I watch? How many AI side projects can I build? Who am I without a job?

Above all, the most difficult part was the shame of being unemployed. Nobody out there cares, but I always felt a terrible shame in answering the question “So what’s your job?” with “I am in between jobs right now”.

It’s all in my head, but perception is reality and I am sure many of you folks out there can relate…

Some numbers

Before starting, remember that my experience cannot be compared “generally” because:

• I wanted to find an executive position and that takes more time

• I had enough of a safety net (like my wife working full-time and unemployment benefit) to be picky about my choices and manage my career like a professional athlete would do

• I had lots of time and sometimes took calls just for fun and training

Here’s my stats:

• Companies with at least an intro call: 15

• Headhunters I talked to that yielded zero interviews: 8

• N. of companies that I interviewed with (2 or more steps before being rejected): 10

• Offers received: 3

• Median number of steps (both rejected and successful): 6

• Median number of steps (successful): 7

• Reasons given for rejection: Competence (2), Culture fit (2), Diversity (2), Location (1)

Special mention: Canonical

In this piece, I decided to not mention any company because I think that as a candidate you see only one side of those companies and it would be unfair to share any negative view based on my partial experience.

However, I interviewed with Canonical as a sort of experiment after reading so much about how horrible their process is.

So I would like to share the experience to make sure nobody reading this piece makes the same mistake and stays clear of them until they change their hiring practices:

Canonical is fully remote worldwide, so they feel entitled to have a gruesome automated process because they have “too many applicants”.

The process starts with writing an essay about yourself (a written interview) that needs to answer around 30 open questions about your experience from childhood to recent times. As I said before, I had a lot of time on my hands so I wrote a 20-page essay on my favorite topic: myself.

After that, you are asked to do an automated coding test that is essentially a quiz on your favorite programming language then a coding test (that I passed to GPT and solved in a matter of seconds because the questions were extremely dumb), and finally an IQ and personality test.

Keep in mind I haven’t talked to any human so far and you can see the red flags here I hope.

In any case, I passed all of that and finally got to the first human for my management interview. I spoke to a very nice guy and we clicked, would love to work with him, to be honest.

Then I had a general technical interview and a system administration interview, again keep in mind I am interviewing for a senior management position here.

The general tech interview was fine, nothing too difficult and it was a nice conversation.

The system administration interview was, frankly, ridiculous. The poor guy that was interviewing me had to read questions from a script that was essentially a quiz on the Linux command line with questions like: “What does |& mean?”

Needless to say, I hilariously bombed that interview and the guy himself admitted that he didn’t know the answer to some of those questions from the top of his mind.

And let me highlight something here, none of the things I wrote in the essay were used for the interviews, nobody cared to read the essay because going through the pain of writing an essay was the point. It was just a filter for effort.

I subsequently got an automated email informing me of the rejection, no feedback, nothing.

Talking to the guys there, I also got the feeling that Canonical is a horrible place to work and they have super high churn. After going through this experience, I am not surprised.

Don’t take the search personal

I have friends who have been through layoffs and a grueling search for a new job, and we share the same feeling: it’s hard to not take this process personally.

The feedback is personal and if you get rejected by a company it’s easy to feel like you are not good enough and never find the job you want.

My advice is to work very hard on your psychological state and get a therapist if necessary because the process is cruel and brutal. When you are out there you are just a number, they don’t know you and nothing is personal.

The state of recruitment in 2023

You read very often on LinkedIn that you should have relationships with recruiters before you search for a job because they are your best friends and will help you.

Not sure if you ever noticed that this advice is never shared by candidates but only by recruiters, and there’s a reason why:

Recruitment isn’t a socially valuable non-profit, they are not trying to find a job for you out of the goodness of their heart. They are in the business of matching offer and demand, a mix of sales and marketing, this is a valuable job and one that we all benefit from but it’s also a number game.

So imagine if that advice was shared by someone in sales instead: don’t start searching for a laptop vendor when you need to buy laptops but have a relationship with vendors before you need laptops to make sure you are always covered.

It would sound ridiculous.

On top of that, recruitment in 2022/2023 was badly impacted by layoffs and in-house recruiters became busy to the point of burnout, there is no way they can look at all CVs and/or give you more than 15 minutes, let alone any personalized feedback.

So here’s my advice on how to cope with the current state:

Do not engage with recruiters that do not have a role for you

All agencies I talked to that didn’t have a role for me but “will be on the lookout” yielded zero results, never got back to me, or got back to me with excuses.

This makes sense, you are a “lead”, you are a person on a list but they have zero incentive to look out specifically for you. It’s the human equivalent of setting up a job alert on LinkedIn, except with less reach.

So my advice is to decline any conversation that doesn’t have a role behind it, it’s a waste of time.

Do not expect meaningful feedback

In the current state of affairs, the best-case scenario is to get zero feedback, many companies employ a new tactic of sending an automated email saying “You have been rejected because <standard reason> but please click this link to set up a call to get more detailed feedback”. Counting on the fact that nobody will do that.

But there is a worst-case scenario in which you will get some ridiculous feedback, for example, once I was rejected by a startup because I didn’t have enough managerial experience. What are you going to do with that?

So don’t interview to get feedback, it’s a waste of time.

However, if you are lucky and find someone kind enough to give you great feedback, please take that seriously and send them flowers.

They’ll ask about your current salary, be smart

There’s no way around it, recruiters will ask about your current salary. There are many possible reasons for it: they want to understand if you are on target for the client budget, they want to gather the data to sell it later, they want to lowball you later on.

The best thing to do is to try to avoid having the conversation, decline politely, but if they insist, never give your current salary but give an expectation range and ask if they have a range as well.

Do your homework with sites like https://techpays.eu/ (or https://levels.fyi/) and collect your own data, ask people around. Never accept to be lowballed on your salary: “You said 100k 1 month ago” is not a good excuse to give you a lower salary, be strong.

Be kind

I know that many people like to dunk on recruiters, but we are all doing our job. You should always be kind to people and respect their profession. Decline politely or give them constructive feedback. Thank them and understand that, like most of us, they are under a great deal of pressure.

And if you work with a great recruiter, don’t let them go, they are so rare.

The only advice that works requires a thousands steps

The internet is flooded with people giving you terrible advice on how to find a new job:

• Have a great GitHub profile, or whatever the portfolio equivalent

• LinkedIn/Twitter(X) presence

• Go to networking events or cold call the CEO

and the list goes on…

Now, I am not disputing that some of those pieces of advice sometimes work but there is only one advice that consistently works:

Be excellent at your job and have a great relationship with your colleagues.

It’s simple and complicated at the same time:

The only people who know the value of your work are the people who worked with you side-by-side or saw your work up close. And it’s great if those people want to work with you again.

Of course, being excellent isn’t enough, people also need to enjoy working with you. Begrudgingly working with a brilliant jerk isn’t great, and I definitely wouldn’t recommend them for a job at my current company!

Not only that!

If you find a new job in a decent company they will ask for references and/or search for references independently.

And if you did a great job you a) will be in touch with those people and will be able to know about those calls b) you will not worry about those calls because you know they will give stellar feedback about you.

Have you ever heard of the PayPal mafia? Or the various alumni networks of famous companies like Uber? This is what this is about, create your network and nurture that network.

This is it, that’s all it takes: Be someone that smart people want to work with.

But what if you don’t have a network? What if you are just starting your career? Then join a mid-to-large company if possible (it doesn’t have to be a FAANG!), or work your way till you can join that type of company. It might not be fun and rewarding like a startup, but it’s an investment in your future.

Manage your career like a professional athlete

My final advice is that you should manage your career like a professional athlete, you should have a crystal clear idea of what kind of job you want to do and what are your strengths and weaknesses.

You are allowed to change your mind of course but work in intervals long enough that allow you to be good at your job before changing your mind.

Those intervals can be 1 year for a simple IC position but can go up to 3-5 years for very senior roles.

I decided 8 years ago that I wanted to be a successful technology executive, and every single career decision I made was in function of that goal.

Now, having an idea of what you want to achieve is great but you need a way to achieve that.

And the best way is to build optionality.

My advice is that you should:

• First acquire skills that will increase your net worth, to have as much savings as possible

• Then acquire specific experience more specific to the path you want to follow

• At the same time build a network of people you like to work with and who are interesting

This will very likely require you to join a large company that has career opportunities and pays well, or get lucky with a fast-growing startup. And it might take more than 10 years, it’s not going to be a fast and easy fix.

But the reward is optionality: the ability to choose your next job without worrying too much about being broke, you might even take more chances on smaller companies and learn a thing or two about starting a business.

Whatever your path, if you can get to a point in your career in which you can choose to do what you want. Then you are lucky and that’s the sweet spot we all want to be on someday.

Mandatory disclosure here: YMMV, I am a just dude describing his journey with a lot of privilege and I am far from being the average job seeker in technology.

It was the beginning of my experience living abroad, I was going to stay for one year, maybe two years, three if I felt very good about it.

Now I have a house in Amsterdam and a mortgage to repay in the next 30 years.

Nobody forced me to stay ten years, it just somehow happened. I was here and it was warm and cozy (gezellig) and, even when it wasn’t, moving somewhere else was so much effort.

This is how life works most of the time, many of our long-term decisions are made with the idea of “just trying something, I can always go back”.

It’s like Amazon’s free returns policy, they understand that keeping an item I don’t like is less effort than sending it back.

The story of one of my greatest achievements

Nine years ago, I was assigned to a new team in Booking.com that had the mission of figuring out if this Machine Learning thing could be used to improve conversion (make money).

One key component of our strategy was to try to figure out what our users liked, what cities they were searching, which hotels they clicked, which ones they booked, etc etc

This sounds pretty easy in theory: you own the website and it should be pretty easy to extract this data. Except that, for a site with so many users, it’s a large amount of data and a lot of noise to cut through.

Our team was considered an “experiment”, we didn’t have enough resources to build anything sophisticated, but we got lucky: the need to run A/B tests all over the place meant that there was a way to track that information and store it for later analysis. We could hack our way by co-opting that system, it was not designed for it but, as long as we didn’t break anything, nobody would try to stop us.

This was not a complete solution, when we started trying to crunch that large amount of data we discovered that it didn’t work as well as we expected. I broke the system so often that the newly formed “Big Data” team invited me to a team retrospective to understand why I was reporting a new bug every day.

After a few months the infrastructure got much better, it was still a Rube Goldberg machine but, in my experience, all companies build a business-critical Robe Goldberg machine given enough time.

And we made money with this machine, oh boy we did, all our models and predictions depended on the data generated by the machine. In particular, two tables that tracked what was happening in the most important sections of the website.

Of course, that data wasn’t perfect, we had bugs and holes in the data, and I spent a lot of time fixing and turning knobs to make it better.

On the other hand, we were running machine learning models and didn’t need “perfect” data, we needed a representative sample.

We were not stupid, we knew that anything instrumental to the money-making engine was going to be bolted on the wall and labeled as a “magical data table that makes money for free”.

So, to avoid any confusion, we called all the tables with a clear descriptive name: team_horrible_data_log1.

And wrote clearly that this data cannot be trusted, “there will be dragons” and all the long-term nuclear waste warning messages that you can imagine.

Eventually, I left the team, handed over this pile of snakes to someone else, and didn’t think too much about it aside from the occasional question I would get from someone who had the misfortune of touching my code.

Later I was told that there was a plan to decommission those tables in favor of something more robust and generic.

“Good job guys”, I foolishly thought.

Harvey Dent’s prophecy

Three years later, I became the manager of a larger department, there were a few data science and analytics teams in there and I was very surprised to learn that they were very excited to meet me.

I was “the guy that created the tables” and, at that moment, the words of Harvey Dent echoed in my mind:

“You either die a hero or you live long enough to see yourself become the villain.”

I had lived long enough to attend a presentation that showed how my “absolutely temporary and access-restricted tables that were about to be decommissioned a couple of years ago” were not only in use but were the foundation of a myriad of business processes, some of them mission critical.

The arrows in the slide showed the various dependencies, like an infectious disease for which I was patient zero.

I was horrified to learn that now people were working full time on making sure that the Rube Goldberg machine kept working and, at the same time, working on decommissioning team_horrible_data_log.

I tried to explain that this was never supposed to happen, it was all temporary! It was a game we played when we were young and foolish!

It didn’t matter, team_horrible_data_log was now part of the foundations of the largest OTA in the world.

I left Booking.com in 2021, the decommissioning work was still ongoing.

Epilogue

July 27, 2022

My phone chimes, it’s a Whatsapp message from a friend who still works at Booking.com:

What can you tell me about team_horrible_data_log ?

I did not expect it to be received so warmly and, for some people, controversially.

So I thought to expand that concept with a couple of ideas that might be even more controversial.

Convincing someone to give you the job is different from being able to get the job done

Malcolm Gladwell’s “Revisionist History” ran an episode in 2020 called “The Powerball Revolution”. In this episode, Gladwell tries to apply the idea of “democratic lotteries” with Adam Cronkright of Democracy In Practice.

The process is the following:

• Every student who wants to be elected as a representative will just put their name forward

• On election day each applicant will draw a colored ball, and people with the winning color will be elected

This seems counterintuitive right? How is this democratic if the people don’t vote?

The underlying idea is that election campaigns are biased toward people who are great speakers, have good friends, or are popular. None of it matters when it comes to defending the interests of the student body as a whole.

Moreover, they find that many introverts and/or people coming from minority backgrounds will avoid a popularity contest but are comfortable putting their name forward if it’s a random chance.

So they put this to the test in New Jersey and followed how the student representatives group became more diverse and also changed its priorities. In the end, they polled the students and found that their work was much more appreciated as a whole.

And more people in scientific research believe that this is a good idea

This is a powerful idea, and some researchers are advocating to use of the same system for research grants.

In 2022, some researchers from the University of Catania won an IgNobel for their research on the role luck plays in life:

The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, efforts or risk taking. Sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant material success. But, as a matter of fact, it is rather common to underestimate the importance of external forces in individual successful stories.

The researchers ran several simulations to predict the role of luck in individual success (measured by wealth), and in their conclusions, they state:

The model shows the importance, very frequently underestimated, of lucky events in determining the final level of individual success. Since rewards and resources are usually given to those that have already reached a high level of success, mistakenly considered as a measure of competence/talent, this result is even a more harmful disincentive, causing a lack of opportunities for the most talented ones.

Our results highlight the risks of the paradigm that we call ”naive meritocracy”, which fails to give honors and rewards to the most competent people, because it underestimates the role of randomness among the determinants of success.

The strategy do they suggest using? Just give funds at random, and make lots of bets.

And you know who else does that? Venture Capitals.

Wait! The math doesn’t make sense when it comes to re-elections!

An objection that I think is relevant to raise is “ok, I believe you. If I know nothing about the skills of someone, random is better. But once they have done the job for a year or two, I have now enough information to judge them fairly”.

I think this objection is valid and haven’t seen any specific research on the topic of re-elections.

If we look at the simulations ran by the team in Catania, they tried different strategies:

• Random

• Proportional to past successes

• Mixed (i.e. 20% of funds reserved for top performers, rest at random)

They say that the simulation shows that mixed strategies work better than using only past successes but worse than random ones.

My intuition is that, while random is probably the best strategy, humans also need agency and trust in their leaders.

From this point of view, an election with 20% of seats assigned using a classic ballot, limited to outgoing members, and the rest random, would have a better overall perception.

Why don’t we do the same for promotions or hiring?

Create minimum requirements to apply, and maybe do one review to verify the requirements. And then draw at random.

I know it can’t happen

And I know that because it makes me, the proponent of this idea, uneasy. As humans, especially in the corporate world, we like to be in control and smarter than average.

So maybe we would like to use a mixed strategy: pick one person ourselves and the rest at random.

But what if random worked?

And he coined the Planck’s principle:

A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die and a new generation grows up that is familiar with it ...

often summarized as:

Science advances one funeral at a time

I know, I know, Planck’s principle is often criticized because no actual statistics support this claim. But it’s a good way to introduce a problem that is dear and near my heart: the intellectual decline of European countries.

The structural problems of Europe

Europe is getting old, really fast

Let’s take a look at the data from Eurostat, the board of statistics of the EU.

The population of the EU on 1 January 2022 was estimated at roughly 447 million. Young people (0 to 14 years old) made up 15% of the EU’s population, working age (15 to 64 years old) 64%, and Older people (aged 65 or over) 21%.

This doesn’t tell us much, it’s not Nigeria but is also not Japan. The problem with this data is that it lumps together people of very different ages, from teenagers to middle age. So let’s look at how the “population pyramid” changed in the last 15 years.

Now the trend is slightly more clear, the high longevity and low fertility of the European countries means that the population structure just shifted 15 years.

Will this trend continue? Eurostat thinks so and projects this incredibly scary pyramid:

Where the 85+ group is the dominant group, essentially projecting that the life expectancy of millennials is around 100 years and fertility rates will keep declining.

Just to give some perspective, here’s the population pyramid of India in 2020:

Older people are more involved in decision-making

The EU elections of 2019 were celebrated for their record turnout and high share of young voters. Let’s see the data:

As we see in many countries, older people have a higher turnout even when young people are targeted specifically.

Let’s look at public company boardrooms:

And homeownership follows a similar trend, for example, this is a chart for southern Europe:

The troubles of the financial market, changes in the job market, and the reduction of housing supply in big cities all contribute to a poorer younger generation.

Europe is losing ground in innovation and R&D

This chart from McKinsey is pretty depressing!

Europe has a large gap with the United States (our closest military ally and economic frenemy) when it comes to the Tech sector, the highest-growing sector of the last 20 years. If you look at the NASDAQ largest company by capitalization you will see Apple, Microsoft, Alphabet, Amazon, Tesla, Meta, and Nvidia.

The closest European technology company is the Dutch ASML (market leader in high-tech machinery for chip making), with a much smaller market cap.

But there is a sector in which we lead the way!

The European Union invented the “Brussels_effect”, a way to use the biggest consumer market in the world to advance European regulations beyond its legal borders. For example the Cookie Law, GDPR, DSA, and the upcoming AI act that has done incommensurable damage to the startup environment in Europe while doing nothing to stop the American incumbents.

Is this a problem though?

It’s a fair question to ask, I don’t believe there is an expert consensus on the answer.

My feeling is that this is a severe problem and that Europeans are not ready for the consequences that this demographic shift entails.

The older people get, the less they consume, the less innovative they become, and the more they vote. This, combined with the demographic shift, means that our society will end up putting the brakes on every possible change, and the world is changing way faster than 50 years ago.

We don’t need more risk aversion

Older folks are more conservative, not in the political sense (or not only) but in their way of thinking. They have seen crises and think that stability is the only way to go, they experienced the “golden age” and think that there won’t be another, they have a lot of savings and are not keen on betting on those savings.

The aversion to risk is something natural for all humans but in Europe there’s a little extra: the way our common institution works shows how the “precaution principle” (any type of innovation must be stopped unless we can prove that is not a risk) dominates how lawmakers and voters feel about the world, think our response to AI or the rollout of COVID vaccines.

Retiring in 2050

In Italy, they say that even Julius Caesar complained that the youth was lazy and unwilling to work and spend like the previous generations.

What’s new is that now we have a large amount of old people who are retired and not working, and they vote.

The retirement system in Europe is unsustainable, as much as we’d like to think otherwise. It’s a giant Ponzi scheme in which the young pay for the old, hoping there will be enough young people when they are old.

The demographic projections are telling us that there won’t be.

So either the retirement age will go up (a lot), or the benefits will go down (a lot).

And the problem is that nobody will vote for either.

The higher turnout means that every politician will defend the current system and will try to change it as little as possible, kicking the can down the road.

Can we do something about it?

I am not an expert on this, and I apologize in advance for not having incredible solutions to offer. Sometimes we see the iceberg coming and can only brace for impact.

But I will try, although you might find my proposals a tad controversial.

Upper age limit for voting

The original idea around voting rights was that only the people who had a stake in the well-being of the country should be allowed to vote. This is intuitive but problematic, who decides who has “a stake”?

Eventually, through a lot of struggle and battles, liberal democracies got to a system in which the only requirement is to be “mature enough”, therefore imposing a minimum age for voting.

I find this system incomplete, why is there no upper bound? Do people have a stake in the future of their country after a certain age?

I think that a simple (and politically impossible) action should be to define an upper limit for participating in voting and being elected. Even the U.S. is not immune to this, having two presidents in a row, and many senators, past their retirement age.

This solution will undoubtedly be unconstitutional in most countries, so it’s not feasible, but is worth thinking about the implications.

Why don’t we lower the voting age? Why eighteen?

The flip side is that the current voting age is pretty arbitrary, some countries have already tried lowering it to 16 to balance things out. The current younger generation is more informed and mature than past generations, there is no reason to not try.

Challenge our risk-aversion with a real innovation policy

Europe has a lot of history, it went through tremendous catastrophes and exciting innovations, and it has all the ingredients to rise again if we choose to do so.

We could be leaders in renewable energy if we can take the courage and stop thinking about how “our beautiful landscape” is somehow ruined by solar panels or windmills. And that industry would foster innovation in batteries, smart grids, and chip making. We could also embrace nuclear power, but I am afraid that ship has sailed.

The older population also means incredible opportunities for healthcare innovation, we could embrace automation and Artificial Intelligence to help the already overworked folks in the healthcare sector.

All this would require different people in charge, younger and focused on “what can we do right” instead of focusing on “what could go wrong”.

This mindset seems to also permeate Europe’s private companies, and a change in mindset at the public level would have positive effects in the private sector.

A better immigration policy

You would think that an area that is struggling with a population pyramid going in the wrong direction would have a strategy for immigration.

The European Union likes to project an image of an open area, where everyone is welcome. The reality is that there are very few ways to immigrate regularly to the EU unless you have a passport that shows that you don’t have a reason to immigrate to the EU, it follows that the EU also has no policy on immigration as a whole.

Our main strategy so far has been to pay dictators or war criminals to detain as many people as possible and deal with the consequences later. And if people die while trying to reach our borders, too bad they had it coming.

But even once they get inside the EU there is no policy, people can’t work because they are illegal immigrants, there aren’t enough work permits for legal migrants already, and no intention to attract any other kind of migrant.

So we leave the future of new migrants to luck or, worse, to organized crime.

It’s not a surprise that immigration had such a bad rep in the EU so far.

I don’t know what the right solution is, but sure as hell the current situation isn’t sustainable.

Can all this happen? Can we reverse course? I am not sure, but we ought to find out

Today1 I was pondering about the trolley problem, an ethical dilemma that was formulated in 1967, and which has since then ended more than one friendship.

There is a runaway trolley barreling down the railway tracks. Ahead, on the tracks, there are five people tied up and unable to move. The trolley is headed straight for them. You are standing some distance off in the train yard, next to a lever. If you pull this lever, the trolley will switch to a different set of tracks.

However, you notice that there is one person on the side track. You have two (and only two) options:

1. Do nothing, in which case the trolley will kill the five people on the main track.

2. Pull the lever, diverting the trolley onto the side track where it will kill one person.

Which is the more ethical option? Or, more simply: What is the right thing to do?

What I find amusing is that we are very close to discovering the right solution to the dilemma, especially once we start having self-driving cars on the streets at large.

I am sure the folks at Waymo are well-acquainted with the 3 laws of robotics:

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.

2. A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law.

3. A robot must protect its existence as long as such protection does not conflict with the First or Second Law.

And I hope they also remember that Asimov himself had to add a “zeroth” law to make it work2:

0. A robot may not harm humanity, or, by inaction, allow humanity to come to harm.

I am curious about how a Waymo SUV will decide what’s good for humanity when choosing between breaking, with an high likelyhood of crashing onto another car and kill all the passengers aboard, or steering, and kill the people on the sidewalk.

As of now, it will choose to brake and call home for human intervention, but that won’t be forever. For instance, you can’t brake in the middle of a highway, and when that happens, I would like to know how they resolve the dilemma so we can stop arguing.

The AI news here is that self-driving cars are super safe and I cannot wait for a world with fewer cars and far fewer human drivers, but the bar to clear for a robot to be called “safe” will be higher than an 18-year-old getting their license.

I am not sure that, even now, I trust a human driver more than a machine.

Resources to get started

I get this question often enough that I would like to add a couple of pointers here for anybody who wants to understand the current AI technology a bit better but doesn’t want to spend 6 months studying:

• An excellent explainer from Understanding AI

• A deeply philosophical piece from my favorite sci-fi writer Ted Chiang

Why those two? Because they go beyond the practicalities of teaching you how to subscribe to GPT-4 for 20 $/month and try to give you the bigger picture of what’s going on.

Meta tries to make cool-looking Google glasses

It’s one of the oldest trope in sci-fi: the main character gets a device that records their life in realtime, they will use it nicely at first and enjoy this new technology very much. Eventually something will go terribly wrong and the finale will be tragic.3

This hasn’t deterred Zuckerberg from launching some Ray-Ban’s that are ready to upload your life on Instagram.

I think it’s very likely that the project will crash and burn like Google Glass, but they tried very hard to fix one crucial aspect: you won’t be immediately recognized as an idiot when you enter a bar.

The new smart glasses look 90% the same as the most common Ray-Ban. However, I can’t guarantee that the folks at the bar will be happy once you start streaming on Instagram or the NSA starts mining your feed.

So, why include these glasses in this post?

Meta plans to integrate an AI assistant within the glasses. Although, I know that most people will use these glasses for the most intrusive and annoying stunts, I can’t help but think that we could be very close to a life-saving assistant that can advise you on how to cook, fix a squeaky wheel, or even help you change a tire on your car in the middle of the night.

The technology exists, it’s just a matter of putting it all together.

Some pretty solid use cases are emerging

Recently I had the pleasure of participating as a “judge” for hosted by Instruqt, a startup located here in Amsterdam.

Their objective was to evaluate the feasibility of integrating some form of AI into their product and transitioning it to production.

For me, their experience served as the conclusive evidence I needed. Amidst the hype and constant change, certain clear-use paradigms are emerging that everyone should consider:

• AI Code Assistants: This should be self-explanatory. If your company produces some software and you are not using the help of AI (I strongly recommend Cursor), you're falling behind.4

• RAG (Retrieval-Augmented Generation): a technique in which you can feed external data to an LLM to enhance the output. For instance, you could use your entire knowledge base to create a customer-service chatbot. This represents an interesting intersection between traditional Information Retrieval and modern AI. If you're unfamiliar with this, there are plenty of tools available, such as Llamaindex.

• Agent model, OpenAI has invested significant effort into developing its "instruct" models. These are models designed to follow and generate instructions. GPT-4 excels at breaking down problems into manageable steps that can be communicated to humans and acted upon using external tools.

These paradigms are quite broad, but what excites me the most is the Agent Model. It has the potential to exponentially improve a model's output by acting as the 'brain' for a larger system equipped with various tools.

Rapid prototyping and the hyper IT self-service

As GPT-4 keeps getting better and shows strong abilities to perform coding and data-related tasks, it raises the question “Why do I have to copy-paste from the chat?”.

If I can ask GPT how to change a setting on MacOS, wouldn’t it be nice if it automatically made the change for me? Or if I am a Marketing Manager and I want to quickly create a landing page prototype, I know GPT can write the code but I don’t have enough knowledge to put it together. Wouldn’t it be nice if it simply executed the task?

Of course, ChatGPT can’t do that!

It’s a website, your laptop knows better than to allow a random website to change your display settings or access your files.

If only we could call GPT in a slightly different way and permit it to do the work…

This is what Open Interpreter does, I have tried it myself and it’s pretty astonishing.

I believe this will continue to improve, solve a bunch of problems for IT departments around the world, and allow business users to write working prototypes before anyone with any technical knowledge gets involved.

Hopefully, this will also assist numerous startups that lack a technical co-founder in getting off the ground.

Large Language fMRI

Anthropic AI is a spin out of OpenAI, its founders left because they believed that they could do a better job at saving humanity from AGI. That resulted in getting a lot of money from Google and Amazon, but I suspect that those 4B$ they got from Amazon are cloud credits to pay for network egress charges.

A few days ago Anthropic announced a breakthrough in explainability of Deep Neural Networks.

Let me try to break it down in layman terms as I understand it:

• One of the big challenges with DNNs, especially from a safety and regulatory perspective, is that we can’t really say “how” they work for specific inputs

• This means that if we would like to stop our LLM from being racist we can’t just point our fingers and say “here, this is the racist layer”

• Many people in the scientific community had the idea that the reason was the phenomenon of “superposition”: like the human brain, neurons in a DNN fire for multiple, unrelated, inputs. So a neuron can fire when a user submits both a kitty cuddling with their owner and a racist meme.

• Anthropic tried, and proved that it’s possible, to do something similar to a functional brain MRI, a technique used to highlight which parts of the human brain are used when the person is exposed to different stimuli, but for LLMs

This is potentially an important breakthrough, it might allow us to create safer AI and, crucially, improve the public perception of those “black boxes” called robots (and avoid the trolley problem etc etc).

V for Vendetta

Back in March OpenAI released a demo of GPT-4 that included the ability to transform some scribbled drawings into a website completely coded by AI.

Since then, this feature sort of vanished off the radar, until two weeks ago when they announced the release of GPT-4V(vision) — basically, the merge of all models of OpenAI (text, audio, image) into one single interface.

I gotta say, they're playing it a bit fast and loose here, touting a "new" feature when they're just making good on a promise from months back.

Regardless, the buzz about chatting with your phone in natural language is off the charts, but what's truly blowing minds is the sheer power of Dall-E 3. Feeling brave? Take a stroll over to Reddit and feast your eyes on the eldritch horrors folks are crafting with the free version on Bing.

Interestingly, Microsoft has published a technical paper on what GPT-4V can do and it’s fascinating. GPT-4V can do A LOT and the report is 166 pages, one sentence from the report that stuck with me was:

One observation about LLMs is that LLMs don’t want to succeed. Rather, they want to imitate training sets with a spectrum of performance qualities. If the user wants to succeed in a task given to the model, the user should explicitly ask for it, which has proven useful in improving the performance of LLMs

This is quite important to keep in mind when dealing with LLMs, visual or otherwise. This is a summary GPT-4 did, just in case.

I wish I could give you details from direct experience, but I am still waiting for OpenAI to give me access to GPT-4V.

So if you know Sam and could put a word for me…

This was an experiment to try out something different and a bit more editorial, let me know in the comments if you liked it!

And the minutes after that phrase are agony and then she breaks up with you. Then it is shock, you ask “Why can’t we fix this?”, and get angry and frustrated. And some people get depressed afterward, maybe go on a bender.

Corporate style change management

This is exactly a famous model of change management that I have witnessed being taught to executives

Do you see the problem? We assume that any “big” change is like a breakup, and we have to manage the breakup. But that is a terrible mental model to be used for work.

Big changes require swift action

This is something I hear a lot: “We need to make a big and swift change because we value agility” or maybe because otherwise there are leaks, or whatever other excuse you have in mind.

Those are just excuses to cover what is poor planning and poor leadership.

Incremental changes

Your customers hate change. If you go and do a redesign of your website, as good as this design can be, you will get a lot of grief from your most important customers.

Back in my Booking.com days, we could observe this behavior when introducing a change via A/B testing, the customers’ reaction in the first days of the experiment was always tough to predict.

And we were doing small and incremental changes exactly to reduce that impact!

This isn’t any different from organizational changes.

Implementing big changes as a series of incremental changes

The main argument against incremental changes is that it’s impossible to make a big change this way, people won’t like it anyway so what’s the point? Or maybe we fear getting stuck in some of those steps when we get negative feedback.

Many years ago I was a young tech director in one of the business units of Booking.com and, together with my product partners, we decided to do a reorganization. Reorganizations are kind of a running joke not only in that company but in general, and we wanted to avoid people going “oef another reorg”.

So we devised a different plan:

• We designed the outcome we wanted, a big reorganization with many people switching teams and managers changing scope, etc, etc

• We consulted and informed our direct team but told them we won’t execute a reorg, instead, we want to find out what changes we could do tomorrow and would be “free of charge”. Changes that just make sense and do not impact people too much.

• In the meantime, we started communicating our vision. For example, for the technology side, I did a small roadshow to communicate how we envisioned our new tech stack and architecture.

• Every quarter, or more often if convenient, we changed something on one or multiple teams, sometimes riding on some people leaving or needing a change.

• Halfway, some of the changes were bottom-up. The story worked so well that people felt we had to go faster.

• One year later we had our reorg completed, with some adjustments during the year, since everybody makes planning mistakes.

Was one year too slow? I don’t think so. People never actually realized that we did a reorganization, there was never bad sentiment or time lost on endless debates.

It was always of higher quality! Because we could get micro-feedback on the direction and act on that, this is the definition of agile! Make a change, test it, and get feedback.

The other way, make a big plan and let HR change everything, is the equivalent of waterfall planning in engineering, so much for “we need agility”.

What if I have no choice?

Shit happens! And there are cases in which you have to make the best of a bad situation, and you can go back and manage it using the method above.

But most of the time it is not the case!

Have you been acquired? Did your people know you were fundraising?

Is Someone leaving the company? Can you immediately announce a plan to replace them or a credible replacement?

In the end, I think change management is overrated, it takes a lot of work to make changes right and most people just don’t want to deal with it. Even if the outcome sucks for everybody.

This is the bane of any manager, the worst time of the year: long hours to collect feedback, write reviews, attend meetings, fight with other managers, and disappoint your people.

But all of this process is needed to select the best people, we do this for the greater good of the company, right? Right?

The theater of objectivity

For the ones in the crowd that have never been in a dreaded “performance calibration meeting”. Picture this:

In the days before the meeting each manager has prepared some summary of the performance of their direct reports, and mind you, this in itself is a special skill that managers develop, and each organization has its unique quirks.

As you sit in meeting rooms for interminable hours, managers go through each person one by one and suggest a performance score. There is a debate that can become spicy if any manager dares to suggest to lower score! The discussions can sometimes spiral into debates about what constitutes "good performance" across the organization. And yes, things can even take a philosophical turn—trust me…

Now, I lied to you before. Not everybody is discussed in the meeting, and the experienced manager will try to hide, hoping to avoid any scrutiny. Although, achieving that feat is only possible for the best of our kind.

And finally, the managers leave the room exhausted, with the "calibrated list of performance scores".

But wait, things get even more ridiculous when we start talking about promotions. Brace yourself, now we try to predict the future of a person's career based on a distilled version of their past standardized performance.

It's closer to witchcraft than management.

"But why?" one might wonder. These meetings, they're not just for show, right?

No of course not! They exist to maintain objectivity, to ensure that every individual is treated fairly, and that the company's decisions are rooted in reason and impartiality.

Or at least this is what they say.

Is all this process achieving the objective?

All this supposed objectivity masks the inner workings of those meetings because there are people in those rooms with their relationships, biases, and preferences.

And I ask you, dear reader, if you were on the receiving side of this process, do you feel all those processes are fair?

My answer, from inside the machine, is no. Those processes give the illusion of fairness. You can find “strategy guides” for being promoted in certain famous companies, people work with their manager to make sure that they can present themselves in a way that those large committees like.

And at the end of the day, managers aren’t accountable for any of this, for the good or the bad, the decision is taken away from them and diluted in a group decision that can go anywhere.

Often when I discuss this topic with other fellow managers, the attitude is “this process is imperfect, but what’s the alternative?”

Admit that this process is subjective

If all of this is a performance, a ruse, let’s get rid of all of it. Let’s finally admit that this is a subjective process and see how we can go about it.

My humble proposal is to give the leader of each unit a budget they can use for their staff. This budget will be proportional to the business contribution of their unit and can be used to hire/promote/reward the people in the unit. Be explicit and transparent about the decision.

That’s it, that’s all you do.

There are some obvious counterarguments:

• How do you decide how much budget is fair to give? I think this is the larger issue to solve. Many companies don’t have good monitoring of the business performance of each unit, I suggest we spend the time we save in meetings to solve this problem first. But this problem is solvable I am sure that any good CFO would be glad to help.

• People will leave if they work in an area that has little budget! For me, this is a feature, not a bug. Companies need to be deliberate in how they invest and need a way to incentivize great people to work on the most pressing business problems. This is a way to align incentives.

• What if you have a terrible manager who is biased? Then finally they don’t get away with it. You can easily measure churn and complaints, this time without the shield of the group decision.

• This way each unit/department will have a different bar for talent. In my experience, this is the case anyway, but you need to make this explicit and, for example, allow managers to interview people before a transfer, to assess for themselves.

This is a rough sketch of an idea I had bouncing in my mind for a while, I would love to hear your thoughts and if you agree or not with my point of view.

Knowledge workers are no exception, we also have our craft and tools and, once you have done your job long enough, you get tired of doing the same things over and over from scratch, in my job that translates to having several document templates or online resources that I can use when I start in a new job. Those are not “ready to use”, I am not bringing a show around the country, just simple templates I can personalize and use as the base to modernize or introduce some practices.

I know those documents would be useful to a lot more people, I have spent enough time googling for sources before having those documents to understand the pain, and I think more people would love to see how “other managers do it”.

Everything is a remix

Before I share anything, I think is important to point out that those documents are a patchwork of multiple sources, the feedback of multiple people, and my own experience. And I offer them not to be used verbatim but rather as a starting point to develop your own.

Management is situational, and nothing works out of the box.

Engineering progression framework

In my time at Booking.com and Aidence, I had to rewrite the engineering progression framework twice. It seems to also be the most common question I get from other engineering leaders. There aren’t too many resources out there, although there seems to be a small trend of open-sourcing career frameworks, companies just don’t care enough to go through the hassle of polishing it for the general public.

That is why I am a big fan of Dropbox’s career framework, it’s clean and written in plain English. The downside is that is difficult to apply generally to other companies since it’s very tied to Dropbox’s culture.

Gitlab, being open by design, has also open-sourced all their career frameworks and expectations but, not to pick on them, I always find their stuff super confusing.

So here’s my template, it’s divided into two ladders: Individual Contributor and Management.

If you happen to use it, personalize the framework to make sure it fits with your company and, more importantly, use it as the "80%" of individual expectations for performance evaluations or promotions. Bound the other 20% to achieve company/team objectives. More in general, never make the mistake of rewarding people for checking boxes, make sure to always reward business contributions first.

For the individual contributor, you can observe how the first 3 levels are progressing toward a very technical individual that has lots of depth and is very comfortable in their team/area of expertise.

Then at level 4/5, it takes a U-turn and now communication and leadership skills are more important. This is a common way of looking at the role, once your technical skills are really good, the next challenge is to convince the business to do the right thing. And this is for me the secret superpower of any excellent staff engineer. And something I have touched upon before.

The manager ladder is pretty shoer, the idea is that an Engineering Manager is equivalent to a Senior Engineer, seniority-wise. What is maybe unusual is the level of technical skills required by a manager here. This is my view of the role, one I care deeply about, but I understand it might not be your case. I still invite you to read through it and challenge your assumptions.

More in general, this framework is very opinionated, you might feel the need to have some levels in between to make the transition more smooth, in short YMMV.

Architecture design

More and more companies have an internal architecture “Request for Comment”, enough that the Pragmatic Engineer has a full list of them. I never found one that struck the right balance between technical and business, so ended up writing a template.

The basic idea of this template is to ensure that the author would think very hard and do their research upfront, to avoid getting the annoying barrage of “did you think about X” by their peers or manager. The other aspect I deeply care about is making sure all bases are covered, especially the ones that are usually forgotten: cost, customer service, and migration.

Hiring

I wrote a comprehensive guide to “how to hire” in which I touch briefly on a potential template but didn’t include one in the post.

Here you go, you can find the template here.

Other templates

• I like to write memos, and while I don’t have a specific template, I wrote about the simple structure I have used in the past here.

• Incident Response practices and training. In the past, I have trained a lot of people on how to deal with production incidents. Those procedures are very company-specific, but one great resource that helped me a lot is Pagerduty’s incident response documentation. And don’t forget to play a good game of “Keep talking and nobody explodes”.

I have published a tiny Python helper module to clean JSON responses, especially the ones created by LLMs. You can find it here: https://pypi.org/project/json-repair/. The joy I am finding in writing code reminds me a lot of https://charity.wtf/2017/05/11/the-engineer-manager-pendulum/

Second, I have in beta a small demo page to help people create their self-retrospectives, now that the annual perf cycle is coming (and none of us likes that). If you are interested in trying it out and giving me feedback, let me know!

Some day ago I was talking to a fellow CTO who is part of a company that is scaling and now “is the moment to set KPIs for the Technology department”.

I remember the first time this happened to me and I was utterly lost, measuring the work of engineers or scientists is hard, and I didn’t have any good anchor at the time.

State-of-the-art

Nowadays there is a lot of literature on measuring productivity, the problem is, that most of it is utter garbage.

I won’t go too deep into it, you can read the rebuttals written by Kent Beck and Gergely Orosz against the latest McKinsey bullshit to have an idea1.

Gergely’s article contains a lot of best practices and if you are interested in the topic go read it.

I will focus here on my experience landing those ideas into an existing organization.

The obsession with measuring people is old

In the Age of Enlightenment, there was a widely popular view that the world was like a clockwork, precise and mechanical. So were peasants, if you were just able to train them, they would be the same as machines.

The view was widely shared in the army, which focused on training foot soldiers forcing them to memorize the number of steps they had to take based on the command, and in factories, with the same movements repeated over and over with precision.

It was popular among the elites, it reinforced their classist idea that the peasants were ignorant and could only be controlled like dogs or horses, and it was a simple solution for a complex problem.

Once liberal democracies started forming, and the old elites were shattered, a completely different doctrine emerged both in the army and in factories. Mechanization took all simple tasks away, and the role of knowledge workers started to emerge.

But the simple solution for a complex problem remained as appealing as it was in the 19th century, just with a different excuse.

The wish to measure everything is not completely unfounded

I don’t want to say that we should just pay software engineers a ridiculous amount of money and whatever happens, happens. That would be financial suicide.

In my experience is incredibly hard to explain how hard and expensive it would be to accurately measure everything that happens in a technology department.

And then there’s the problem of how difficult is for a manager to gather data or, as I call it, the quantistic theory of management:

The mere presence of a manager observing or measuring something is enough to make any observation or measurement completely useless.

Not because of Goddhart's law, although that doesn’t help, but simply because people will try to be their best selves in the presence of the person responsible for their bonus.

And, going back to the beginning, once I made all those points to the CEO or SVP, the answer was “But sales and HR can easily set targets”

Two bad incentives don’t make a good one

Sales is one of the oldest crafts in the world2 so it seems natural that it has more practice on how to set targets and how to make them work.

In my experience, this is mostly false.

Don’t get me wrong, the oldest incentive of “sales targets” is always there and it works extremely well when everything goes well and those targets are achieved. But as soon as something goes wrong, or when the sales executives are pressed to commit to a specific amount that is challenging to achieve, they will resort to all kinds of alternative metrics: the number of meetings with customers, the number of leads, customer satisfaction, etc etc.

And sales targets alone are a terrible incentive! You can lie to customers to close your contract, you could close contracts that are loss-making, or even just outright fraud. Ask Wells Fargo about it.

Recruitment is even worse, when I was in Booking back in 2016 the recruitment team was put under A LOT of pressure to recruit people with challenging targets on the number of hires.

The idea was that the bad incentive of pushing anybody through the door would be counter-acted by the engineers doing the interviews. This caused a ton of problems:

• More than once during a debrief session I had to justify my rejection to the recruiter in an exchange that became more and more emotionally charged (since their money was on the table).

• My group back then was contributing a lot of interviewers but we were also notoriously stricter than average, so the recruitment team decided to schedule all of us in the same interviews so that they would be the least promising candidates against a wall. Instead of distributing us and risking more candidates being rejected.

• At one point it turned out that one recruiter outright lied to candidates to recruit as many people as possible, then used the big score to leave and find a better role.

All those problems were eventually resolved by changing the incentives but a lot of damage was done.

With this in mind, how do you set KPIs for your department? Because, like it or not, the CEO/SVP won’t just accept no from you.

Size matters

Setting KPIs is a delicate matter, it will upset people and cost you a lot of time.

If your team is below 50 people, you probably don’t need KPIs at all. This is because you, as the leader, must be hands-on enough to know if things are not going well: If your team is not shipping frequently enough, not committing daily, and not releasing as frequently as your industry allows3 you must be aware already, and be able to fix it.

For a small team the KPI of “shipping a lot” should be more than enough. Now you also want to keep an eye on quality, so keeping an eye on bugs, test coverage, and setting up some automated security scanners is a good idea. But, again, at that size, you should be able to talk to your engineers and ask them “Is our code crap?” and get a good answer.

At a slightly larger size, you won’t be able to know everything that is going on so you will need some monitoring, this is how I decided to organize it at Aidence:

First I had to find out what the business cared about and ask the CEO and the CCO, what, at a fundamental level, they needed from me.

They’d probably say something along the lines of ship faster, cheaper, higher quality. That is impossible, so press on to figure out which one of those metrics matters to them: if you are a company that is growing quickly probably pushing features out faster even if with lower quality is a good compromise, if you are in fintech you are very likely under pressure for high quality and low margins, etc etc.

In our case what mattered to the business was consistency, If we say we will push something out in the next release a) we will push it out in the next release b) the next release will come out more or less on a predictable schedule.

But there were also other stakeholders, the CFO cared about the cloud cost expenditure that was growing too fast when compared to our margins, and Regulatory was not happy about the absence of any real commitment to resolve bugs or vigilance tickets.

A lot of wishes…

At that size, you still don’t want to be too prescriptive on your KPI because of Goddhart’s law so I chose to go with a mix of targets and SLAs:

• Cost became a target but not a total yearly budget. We calculated the “Cost per transaction” and used that as a target. Why? Because transactions were the unit we shared with sales, we billed by transaction so the cost to serve a transaction is a good anchor to improve company margins. You can do this too by calculating your unit of economics. If you are using the public cloud is pretty straightforward to calculate cost, if you are using your hardware then you will have to do a bit more work to calculate TCO (Total Cost of Ownership). Disclaimer: I favor the public cloud.

• For security, defects, and regulatory vigilance tickets, we created an internal process with an SLA to monitor (roughly 2 weeks for a high-priority ticket). A hard target was too cumbersome, some tickets might be very hard to close, and in general, if you have a hard deadline for tickets you end up with a lot of “won’t fix”. Incentives again.

• Finally, to achieve consistency in the release we worked a lot in setting up a release process with the target of a release every 6 weeks. In case we ran out of time, we could decide to cut the scope of the release and ship it out anyway. It was a compromise between the inevitable variability of the work in a startup and the predictability needed by the business.

• Whatever you do, don’t use estimation.

All those points above required work, work from my side but also work from my team. This is something that sometimes business leaders miss: each new KPI brings with it a lot of work to set up processes, monitoring, and reporting. So it must be worth it, not just a whim. Otherwise, you are better off not measuring anything.

DORA, SPACE, and other fantastic beasts

If you are familiar with popular frameworks you are familiar with the acronyms of DORA and SPACE. I like the idea behind those metrics and I think that any company with enough maturity should attempt to deploy them.

A word of caution, measuring those metrics can be very hard unless your practices already align with the ones that the authors suggest. For example, how do you measure “change failure rate”? Do you have automated reporting? Do you have someone writing it in Excel?

Follow the money

Regardless of your KPIs and choices, my advice is to always follow the money:

If you can’t explain to the business how your department contributes to the business, you will always be a cost center, a necessary evil for the company. On the other hand, if you can always trace back your contribution to some kind of business metric (best if $$$), therefore able to show the ROI of your team, you will be a place to invest.

Measure systems not people

One last word of advice: don’t measure people but measure systems and the teams responsible for those systems.

It’s a bit counterintuitive because we don’t give bonuses to teams but to individuals. Measuring an individual, without being there side by side all the time, is impossible. How do you evaluate the individual contribution of pair programming or mob programming? What if someone is amazing at improving user stories and is making the team 100% more efficient?

What I find useful, from a systematic perspective is to, in order of priority:

• Evaluate systems: How often this specific product/service/system is released/deployed? How many bugs are reported? …

• Evaluate team performance: What is the cycle time? Is the team functional (from a collaboration point of view)? What is this team's contribution to the system/product/service that they are responsible for? …

• Check-in on individuals: Finally, the people responsible for the team (tech leads, engineering managers) must be side-by-side with their team members to make sense of the above. Is everyone contributing equally? Is there someone hoarding all the knowledge? …

A very rough example. A long time ago one manager was arguing that all his team members were superstars that were contributing exceptionally. I pointed out to him that his team as a whole was underperforming, so the logical conclusion was that HE was the problem of the team. That led to a more nuanced conversation about his team…

In the end, measuring productivity affects productivity, so don’t be overzealous or you’ll be performing only on paper …

I am Stefano, I am an engineer by passion and a manager by trade. I have a lot of shower thoughts and opened this publication because a friend convinced me that it was a good idea to share them.

I try to keep a semi-regular schedule and my writing is a bit rough, my objective here is to give you something to chew on, not wisdom. If you want wisdom there are a lot of other people out there that are happy to take your money.

Hope you enjoy my writings and don’t hesitate to reach out and share your feedback!

Since you all seem to like it when I talk about finding jobs, I thought I’d write one last time about it. Finishing a trilogy I didn’t want to start and that maybe is not over. You can find here Part 1 and Part 2.

In the previous posts of the series, I have looked at hiring and recruitment from the two different, and complementary, points of view of the hiring manager and the job seeker during an interview. What is missing is what happens afterward, when a job offer is extended.

A simple model

A simple way to think about an offer negotiation is to imagine a situation in which:

• You want to badly reach an agreement, because you care about closing the deal or you won’t be negotiating to begin with

• You are ready to walk away from the deal at any moment, because you can close a better deal somewhere else

• You want the best outcome for yourself, obviously

• You want your counterparts to be happy about the outcome, because there should be no losers in a negotiation

This is schizophrenic, none of those points can be true at the same time, yet somehow this is exactly what needs to happen.

Now add some chickens

Imagine you are walking on the sidewalk and there is another person walking exactly in front of you, not an inch on the left or on the right.

If you keep walking straight you will crash into each other, you cannot move to the left because of the cars, but if you step on the right you might soil your new shoes.

And why should I move for this stranger? Why don’t they move?

This is a simple example of what in game theory is called a “game of chicken”, a situation in which each person is trying to get their favorite outcome by showing that, if they don’t get what they want, they are ready to accept the worst outcome for both. Essentially gambling that the other person will concede.

It is a common situation and, in many cases, the main reason for not backing down is not an objective impediment.

How do you avoid playing this game without being the chicken?

The game of chicken is a losing game and it’s easy to say that the best way is to avoid playing the game altogether, but sometimes that isn’t possible.

In many business cultures, the idea that you “win” a negotiation is too ingrained, and winning “the game” is too satisfying.

Let’s see how you can try to avoid this situation keeping in mind that sometimes that is just not possible.

The dreadful salary expectations call

The best way I know to avoid playing the game is to get to know each other and care about the outcome. Not in a personal way, you don’t have to like a person or a company to negotiate something, although that helps.

This is why I always find very annoying questions about salary expectations at the very beginning of a recruitment conversation, they are awkward and annoy everybody (as you can read often online).

Now, there are good reasons why a recruiter might ask about salary expectations, for example, to avoid wasting the time of a full process when salary expectations are misaligned.

And there are bad reasons to ask, to put pressure on candidates to name a low figure and then lowball them on the offer.

But this isn’t right! The incentives are a mess! Everybody is optimizing for the worst-case scenario!

Candidates are incentivized to shoot as high as possible to avoid being lowballed and recruitment is incentivized to negotiate offers down to avoid overpaying.

Advice for hiring managers:

Publish your salary bands! There is no need to be opaque, you can publish wide bands of 50k and just say that the exact offer will depend on the candidate’s work experience. Just ask if the candidate is fine with the published salary band before moving to the next stage. I have implemented this strategy first-hand and it works like a charm.

Will this be a problem internally because you underpaid people? Fix your internal processes before your people leave.

The myth that people don’t discuss their salaries is false, in my experience, people disclose salaries more easily than their food allergies.

Advice for candidates:

My go-to strategy is to avoid answering the question altogether with the following answer:

Look, I think is too early to talk about money, I don’t care about the outcome and you don’t care either, why don’t we postpone this discussion for later? Maybe you have a salary band to share so I can tell you if it’s aligned with my expectations.

Sometimes this won’t work, sometimes you are talking with an external agency that has a specific mandate to ask for your salary expectations or collect data that they will sell later. This is a situation in which they want to play the game, so you will require some high-level strategy:

• Beforehand, collect information about salaries using sites like levels.fyi and/or ask around, maybe you have contacts in your network with similar jobs. You only need a ballpark.

• Don’t give them your salary expectations but craft a “current total compensation” situation (including bonus and stocks). Then just state that this is your current pay and you will want more than that. If you get challenged, never give any copy of your payslip to prove your claims because that is very personal data and is a bad look if a company asks that.

Negotiating the final offer

Let’s say that everything went well and you are ready to make or receive an offer, what’s the best way to close the deal?

For hiring managers:

There are two schools of thought here:

The first one that says that you should never give out your best offer but keep a couple of freebies ready to please the candidate's requests to give them an illusion they “got something” from the negotiation.

The other one, to which I subscribe, says that you should make your best offer and negotiate only if the candidate raises good arguments (i.e. cost of living for their location, one-time sign-on bonuses, etc).

In my experience making offers, this latter method is the best one for a couple of reasons:

• It’s the most honest way of dealing with a job offer. You give someone your best offer, explain to them why and how this offer was put together, and state that this is the best offer you can do (and that is true not a trick)

• It forces you to have a systematic way of making offers, to make your best offer you need to have a salary range specified, a certain way of deciding the seniority, a structured way to deal with benefits and secondary pay

For candidates:

My thinking here is that you should try to negotiate everything. There are no downsides in asking, my general attitude is to challenge every single part of the offer: base pay, bonus, stocks, sign-on bonuses, job title, vacation days, number of days in the office, etc.

This is a way to check what the other side cares about (they won’t negotiate on that) and what is possible to negotiate by policy. It will also tell you if this is their best offer.

Again, try to get insider information on company policies, in many large companies the leveling you will be hired for decides most of those elements, so it’s crucial to get leveled in the right way.

Not all voices in a job offer are created equal, this is my ranking:

1. Base pay

2. Cash bonus

3. RSUs (public company)

4. Job title

What about stock options? Those are a bet that the company you are joining will have an exit and you will be very rich in the process. Handle those promises with care.

As usual, YMMV so don’t take my word for it but do your research.

Should you accept the deal?

Remember this?

You are ready to walk away from the deal at any moment, because you can close a better deal somewhere else

None of the advice above works if you are not ready to accept this outcome.

For hiring managers:

Hiring a person is a very expensive process and an imperfect one. If you think you found the right person, especially if this person comes with trusted references (not the ones they provided but people you reached out to independently or internal referrals), it makes no sense to push them too much.

On the other hand, there are very good reasons to just say “no” if paying this person too much would cause grief internally. I witnessed countless times how one expensive hire caused massive internal requests for raises.

For candidates:

There are good reasons to not negotiate an offer to death, for example, an opportunity to work with exceptional people and advance your career (and so your future income), a mission you believe will change the course of history, or just because you like the people there.

On the other hand, if you can’t find anything satisfying about this company that is not money, then maybe you shouldn’t go there to begin with.

Final thoughts

Negotiating an offer is always a privilege, not everybody can do that either because they can’t afford to lose the offer or because they are too inexperienced to do so. Use this post as a starting point and make up your mind independently, there are also plenty of websites that offer salary negotiation coaching for a small fee, and this might be useful, especially with well-known companies for which they might have insider information.

Leverage your network, I have personally helped people reason around their offers and get one that was more in line with their desires.

There was a lot of theory, obviously, but the highlight of the day was the session with a professional actor who would play any part we wanted to exercise the newly learned skills.

That day I saw grown-ups losing control and yelling at the actress. They knew it was just a training session but the situation got extremely real that they couldn’t control themselves. A testament to the greatness of that actress.

It was so powerful that, a few years later, I put my people through something similar to prepare them for the end-of-the-year review cycle.

And I suggest you try to organize something like this, it’s not difficult to find someone.

Yet one problem remains

You can’t have an actor on call if you want to try out a difficult conversation on the spot, and using your manager or colleagues could be useful but only if they know how to act convincingly.

Wouldn’t it be great if you could train whenever you want?

The difficult conversations simulator is here!

Since I am unemployed I started working on some demos and ideas just to test the water of what’s possible today with modern AI tools and what you can achieve in a short period is truly impressive.

So I created a simulator in which you can try to rehearse your upcoming difficult conversations with a GPT-powered chatbot.

You can find the simulator on my HuggingFace personal space: https://huggingface.co/spaces/mangiucugna/difficult-conversations-bot

How to use it

The interface is quite simple really, on the left side you will find the chat box in which you can write down your text and chat with your character.

What is more interesting is the kind of output that you get while talking with your character. Let’s look at it:

The response you get from the bot in the main chat box includes two types of response: The non-verbal cues, in italics, and the verbal response.

Funny enough, the non-verbal response isn’t entirely my idea, GPT kept not conforming with my instructions by including those non-verbal cues randomly in the response. So I added it in a specific part of the response.

At the bottom of the left side you will find another interesting window:

Here the output is the internal monologue of both GPT and the character, this is such an important part of this simulator!

Not only it’s useful to understand if GPT is drunk, but is something that real actors would give you at the end of the session. You can refine your technique and find a better way to bring a message by using this internal monologue.

Now let’s look at the right side:

In this panel, you see the default settings I left to help you, to have the best experience you will need to be as specific as possible here. Don’t hesitate to try different variations!

Extra tip: If you want the character to sound in a specific voice, provide examples of phrases and tones that you expect.

Disclaimer

This is a demo, so use it at your own risk and for your purposes. It might break unexpectedly and I take no responsibility whatsoever for anything. I know this can probably be jailbreaked to make it say weird stuff, but I don’t care about that since it’s all private sessions.

I also pay for the GPT integration, so if this becomes too popular I might hit some spending limits I have for safety.

Finally, I would appreciate it if you could leave some feedback in the comments, I’d like to hear about your experience if you try it out.

Some technical details

Update Sep-07-23

I have published a python package to deal with broken JSON coming from LLMs. Give it a try here: https://pypi.org/project/json-repair/

The modern stack to produce proof-of-concepts like this has evolved a lot in recent months and I was impressed at how easy it is to build something like that once you figure out the right prompt engineering.

Tech stack:

• Language: Python 3.11

• UI: Gradio

• LLM: Langchain to abstract the integration with OpenAI GPT 3.5

• Monitoring: Mona Labs

• Hosted on HuggingFace (obviously)

The code is public so you can take a look at it yourself, a few things that surprised me:

• Getting GPT 3.5 to respond consistently is very tricky, in particular:

  • If you need a specific type of structured output (in this case I wanted a JSON object filled with specific fields), you need to send GPT as much JSON as possible, especially the messages from the human must be JSON because GPT has a preference to respond in the same format (including language)

  • GPT 3.5 has a bit of an issue with staying in character, using system messages that are sent for every request helps keep it in character by reinforcing the instructions

  • GPT is also very agreeable, so if you need a very disagreeable character you have to push it

• In this build I used Cursor and my only comment on it is HOLY SHIT! I think AI for Coding is finding product-market fit fast! Let me give you an example:

  

  Here I needed to write the function that updates the character information, it was tedious work so I used the built-in interface of Cursor to fill the object. Note that GPT here understood how fields with slightly different names were the same data. (Green is the lines of code added by AI)

Bonus tip, my custom instructions for ChatGPT: recently OpenAI made available a simple way to provide system messages to ChatGPT, called “Custom Instructions”. I use that to refine my experience and I have multiple sets, and I would like to share with you my “generic” set, the one that is good for general use.

In the bottom section called “How would you like ChatGPT to respond?” add:

Always provide a detailed explanation for your response, including the underlying reasoning and any relevant sources to support your answer.

If your confidence is too low, only say "I don't know", don't try to answer the question.

Never mention that you are an AI model, I know that already.

Use this format to answer:

```
{answer}

**Internal monologue**: {internal monologue and your train of thought}

**What other questions you might ask**: {what kind of followup questions you expect from me? What did I miss?}

**Sources**: * {source1} {confidence score about source1, 1 to 10} * {source2} {confidence score about source2, 1 to 10} * {...}

**Confidence**: {score 1 to 10 to indicate that the overall answer is real and not an hallucination}

```

Always stick to this format, it's paramount that you stick to the format

You’ll thank me later.

Ideas for the future

This is just a proof-of-concept, in no way this is something you could bring to the market as a professional product. There are a few things that I would probably do before making a product that people want to pay for:

• Fine-tuning: For now this is using vanilla GPT and it works fine. It would be much better to build a corpus of real-life difficult conversations and produce a fine-tuned model with those.

• Testing other models: I am very curious to test Llama 2 with fine-tuning to see if I could make this work in a much cheaper setup

• UX: Gradio is great for demos but the UX isn’t good enough for a product that people would want to pay for. I also think I should add some more personas so people can test out different types of characters without having to write everything. I’d probably do some of this over time.

If you have ideas and would like to contribute, this is a public space with PR open, so feel free to push some.

First of all, you might have noticed that the title has changed to something slightly more descriptive than the previous one, I also moved the domain from Substack to my own domain: stefanobaccianella.com.

I am trying to optimize things around and see what comes out of it. I am also experimenting with AI and trying to keep up with the daily news in that field, but, oh boy, it’s incredibly hard to keep up with the latest innovation these days.

I have a few posts already scheduled but I want to wait for everyone to be back from vacation.

In the meantime I was invited to a podcast. It was my first time, so you will hear how I ramble, don’t answer questions or lose track of what I was saying. We all live and learn no?

Here’s the link to the episode:

Honeywell was much smaller than GE and run by Cote (an ex-GE executive) which transformed it into a great company that is now worth much more than GE. Cote talks at length about his experience and I was particularly struck by this:

From MD&A:

Lacking any drive to think deeply about their businesses, and unchallenged by leadership to do so, teams held meetings that were essentially useless, their presentations clogged up with feel-good jargon, meaningless numbers, and analytic frameworks whose chief purpose was to hide faulty logic and make the business look good. When you did a bit of digging, you found that most executives didn’t understand their businesses very well, or even at all.

Cote defines this as intellectual laziness. The tendency of organizations to “juke the stats” and lie to themselves instead of diagnosing and solving root problems.

This sounded like something I heard before. In the book “Good to Great”.Jim Collins proposes the principle “Confront the Brutal Facts – but Never Lose Faith” as a core rule of great companies:

Every good-to-great company embraced what we came to call "The Stockdale Paradox" you must maintain unwavering faith that you can and will prevail in the end, regardless of the difficulties, and at the same time, have the discipline to confront the most brutal facts of your current reality, whatever they might be.

However, Jim Collins doesn’t explain how to achieve this, but Cote does.

Again from MD&A:

Cote preaches that managers should instead strive for intellectual rigor, to probe deeply to identify and confront root problems and think creatively and rigorously to find solutions.

[…]

He argues that unless leadership enforces intellectual rigor, middle managers will manipulate their reported metrics while underlying business performance suffers.

[…]

Cote’s formula for success is not some kind of complex 4-D chess […] The focus on avoiding denial and properly diagnosing root causes is reminiscent of the “five whys” technique pioneered by Toyota

The dentist checkup method

Cote’s formula reminded me of the last course I had to pass for my Master's Degree:

It was taught by a professor that, during the exam, would ask you superficial questions to probe your general knowledge of the required topics.

Then, if at any point he felt that you didn’t truly understand what you were saying, he would keep asking questions on the specific topic over and over, going deeper and deeper, until he was either disappointed or satisfied.

Your knowledge on the topic (or lack thereof) would be exposed so well that I have never heard anybody disagreeing with the outcome of that exam.

Over the years I started using this method for decision-making or business reviews. I called it the “dentist checkup”, reminiscent of how my dentist used to find the most impossible cavities in my mouth when I was a kid.

But you can call it “intellectual rigor”, and here are some tips on how to make it work:

• When you don’t understand something, ask a clarifying question. If their answer does not help, don’t assume you are stupid and shut up, ask again until it’s clear to you

• Always be suspicious when someone shows you only assumptions and conclusions, what happens in between is the most important part

• If someone cites numbers and figures, don’t presume their math is correct or their figures are true. Ask for sources or research yourself if something feels off

• When someone has too much material it might be a sign of the “midwit trap”, or Dunning-Kruger effect. Are they overcomplicating for lack of experience?

• If someone is there “just to get a sign-off” and is not interested in having an honest conversation, just say it out loud, this method won’t be useful unless everybody at the table is honest

• There is no shame in asking someone to come back later after they clarified some of the points raised

On a more practical level, if you are in a position to change the way the content is presented:

• Prefer digital pre-reads in which you can raise questions ahead of time, followed by an open discussion on those questions. Giving people time to prepare leads to better discussions

  • Set a max length for the pre-read, see the midwit trap above

• Don’t be a stickler for process, format doesn’t matter, this is about good decision-making. But templates can help.

And of course, those rules should be applied to yourself before anybody else, intellectual rigor starts with you.

Using this method requires care

Asking a barrage of questions can be awkward without an established relationship, people will just assume you are an asshole. Even if it’s the culture of the company, nobody likes to be challenged by a stranger, especially one that is not from the same area or department. Pay attention to your tone, your body language, make sure to establish a relationship, and never make it personal.

The first requirement for this method is that you care. You care about the business, about the decision to be made, and, above all, about the people that might feel hurt by your remarks (even if you are right).

The second requirement is that you are not invested in a particular outcome. The point is to make better decisions, not to fulfill your wish. This is particularly important if you are a top-level decision-maker.

This third, and final, requirement is that there is no hierarchy in the room. Everyone should have a voice proportional to their expertise, not their position in the organization.

Sounds hard after I put all these warnings, but I still invite you to try it out. Try to challenge yourself and others, and see what comes out of it.

Growing up in a modest family in a small town, I never had the impression that finance was something I should care about, my family didn’t have money to spare so it wasn’t part of the conversation. In fact until very recently my definition of “being rich” was to buy groceries without looking at the price.

The first time I became aware of how finance affected my life was, like many millennials, during the financial crisis of 2009-2011, when the concepts of sovereign debts and derivatives trading were the main topic on the news.

Before that, my family's encounters with anything resembling financial services (other than mortgages) were postal savings that were (still are) very popular in Italy as a safe way to store your money. Anyone with any proper knowledge of personal finance would never buy such a product and they do not.

Then I joined a big company and made friends with people that had different interests than me, started learning about this topic, panicked, and ended up spending a lot of time learning the hard way.

I was recently telling this story to some younger colleagues and it became extremely clear that most of them had never thought about this problem at all, and I was not an exception by any means.

Financial illiteracy is necessary for the system to work

My favorite financial writer Matt Levine recently talked about the trouble of small banks in the United States and he masterfully explained how the entire banking system is sustainable only if all of us agree to not think about it:

1. I put my money in the bank because it is convenient and safe, with the understanding that safe means that if I put 100 bucks in my account today I can take 100 bucks out whenever I want, with no exceptions

2. My bank lends that money to companies that want to expand, and to people that want to buy houses, within certain constraints

3. In turn, my bank makes money by charging fees for their services plus the interest payments that they get from lending, investing, credit cards, etc etc

4. The safety of my money is all in the hand of the financial regulators, like the deposit insurance scheme or the minimum capital requirements

It follows that the system works only if you are happy with the fact that:

• your money isn’t really in the bank but is lent to other people for their more or less risky endeavors that will probably pay back with interest (or might lose it all!)

• your money is also lent to your government by buying short/long-term bonds that pay interest (that is far superior to the near-zero interest paid to you)

• with the rise of digital banking, there is no real difference between any bank unless they fail and your money is lost

Once you look at it this way, why would you keep more money in your account than it is strictly necessary to pay bills and groceries? And so, why the system doesn’t fail?

The system failed for banks like Silicon Valley Bank, First Republic, or Credit Suisse, I will leave it here because there are a lot of nuances to this statement so I will just point you to the mandatory subscription to Matt Levine’s Money Stuff.

And I think that we should all become a little bit more sophisticated with our hard-earned money because nobody out there is looking after us, especially when we grow older.

Financial institutions take advantage of financial illiteracy

The problem isn’t just that your checking account is close to useless, the problem is that financial institutions market products that are legal but senseless:

Let’s say that you have a child and you want to start saving money for them so they can study abroad or buy a car when they are 18 years old.

You go to your bank and you are offered an extraordinary zero-fee saving account for your child, that is great, right? Right?

If your bank is ABN Amro you can see what interest rate they pay on that “special saving account”: 1.25%.

With that money, ABN Amro can immediately buy Dutch Government Bonds and earn money in a super safe way or do something riskier and earn even more money.

So you are subsiding ABN Amro’s top management bonuses for the great honor of using this “free” savings account (you are losing money when accounting for inflation).

This is not something specific to this bank or country, this is common to all banks.

So where do you start?

Now that I convinced you that this problem is essential, you would like to know more about it!

This could be scary at first because there are a lot of big words thrown around and it gets overwhelming very quickly.

I have ranted before about the failings of formal education in the Western world and this topic is no exception, unless you have made specific choices in your life there is no way someone taught any of this.

Luckily the world wide web is full of people smarter than me that filled it with a lot of content we can use.

The most complete resource I can point you to is the wiki page of the r/personalfinance subreddit1

For the sake of making this post readable, I will also badly explain2 a couple of concepts that I think are important to know:

• Interest rates, is a broad term that refers to the amount of money you need to additionally pay when you get a loan from a bank. When you hear in the news that “the Federal Reserve raised interest rates” that means that the central bank of the United States wants more money if a bank needs cash from them. Interest rates and inflation (the increase of prices over time) are tightly linked and that is why these days they are both on the news.

• Stocks or shares, the two terms are used interchangeably by most people: if you own shares of a certain company you own a piece of it.

• Public vs private company, a public company is a company for which you can buy and sell shares in a public stock market (like the London Stock Exchange or NASDAQ) to anybody that wants them at the right price.3 You can still sell shares in a private company but it will be much more difficult to find someone since there is no public market to use, and there will be conditions attached to it.

• Bonds, a way for companies or governments to get a loan from the general public instead of banks, with the promise of paying the money back at a certain date and with a certain interest rate. The higher the interest rate, the higher the risk that you will never see your money again. The U.S. Treasury bonds are considered the safest bonds in the world and also the ones that pay the least amount of interest.

• Equity compensation, is a way for a company to reward and motivate their employees by sharing a “piece” of the company. Nowadays it is common in public companies, especially for technology workers, and in cash-strapped startups that can use it to lure more senior employees by offsetting lower salaries. The two commonly used types of equity compensation are Restricted Stock Units (RSUs) and Stock Options. If a company is publicly traded, your equity compensation is equivalent to cash, if it's not, you'll have to cross your fingers and hope for a liquidity event that pays back those stocks.

• Diversification, is a way to lower the risk of losing your money by investing in many different, hopefully unrelated, companies or products (diversified portfolio).

• Passive investing, is a form of long-term investment in which you create a diversified portfolio based on several rules and then touch the portfolio as little as possible for many years. The most famous passive investing products these days are index funds and ETFs.

My strategy is to be boring

Here’s how I interpreted the advice I have read online and discussed with friends, your mileage might vary so please take it with a grain of salt.

Budgeting

You will find plenty of documentation on how to build a personal budget, especially on a more specialized subreddit dedicated to FIRE (Financial Independence Retire Early), and how aggressive you can be on your budget.

I do not subscribe to the movement because I am not planning to retire early, but financial independence is important to me. So I am a more light touch on the way I manage my money:

• Spend 1/3 of my income on fixed expenses (mortgage/rent, various bills, groceries, etc)

• 1/3 goes into savings

• 1/3 is free to be used for free time and maintenance of the house

Additionally, I have a floating line in my bank account, the day before I get my salary I will move all the money above the line into savings.

You should see this budgeting on an annual basis, otherwise, it would be impossible to plan big expenses like a vacation.

At the casino the house always wins

The failure of any player at a casino is to think that they can beat the house, this is exactly why I don’t spend any money picking stocks in the stock market.

Picking stocks is a fool’s errand even for professional investors: Warren Buffet (one the richest man alive) made a 1M$ bet that a general index fund would outperform a very famous hedge fund (an investment type reserved for the wealthier people that promises “smarter” management of the money when compared to the “dumb” index fund) and he won.

So I followed Warren Buffet’s advice and simply buy shares in an index fund that tracks the MSCi World Index and that is it.

I put money in it once a month as a way to reduce volatility (see DCA), and the reason why it works is because no matter what you do the biggest law of finance is the power of compounding.

Diversification

Age is important!

The strategy above is 100% stocks and, make sure to read prospectuses, it has an investment horizon of 10-15 years with an average risk of losing money. This is a good strategy when your retirement age is still far away, as you get older you want to start investing a bit more in Bonds ETFs for example. If you are much younger than me, maybe you want to be even more aggressive instead, and go for something riskier. There are plenty of guides out there to help you out.

Invest in owning a house that appreciates over time

I also own a house and have a mortgage on it. If you have the means to buy a house in a location that makes sense to you (something that has become a luxury in many big cities) do so and take a mortgage on it, as long as you can sustain the payments in your budget. Although there are mixed opinions about this advice in the econ community.

Pension funds are tax exempt

I have mixed feelings about pension funds, while it is a way to save money for the future in a tax-efficient way, I don’t trust that our current pension systems will be sustainable by the time I am retiring. Maybe it’s just because I share with my fellow millennials a pessimistic view of the future.

What about crypto?

As I said already, the house always wins so if you want to speculate on something be my guest.

You should have more questions than answers in your head right now

After writing this up, I realized that this post got a bit complicated with a lot of external links to click. Take it as an introduction to the topic and spend time doing your research using the links provided and the ones you will find and don’t trust my word on any of this.

Note: this is not financial advice! Talk to someone competent if you want advice.

I have something to confess, I love doing interviews. And I don’t mean the part in which I am the interviewer, although I don’t necessarily dislike that part of my job, but the part in which I am interviewed.

Why is that? You might ask.

1. An interview is a moment in which I get to talk about myself and the people on the other side have to listen to me

2. Being a hiring manager for many years, I don’t take interviews too seriously, I know they are extremely biased and that most companies don’t prepare their interviewers adequately and therefore are bad at picking the right hire

Nonetheless, I always prepare for an interview, especially the kind of interviews that are more suitable for story-telling (e.g. STAR or SOARA) because that is a performative interview and requires some level of preparation.

You can see the list that follows as some kind of checklist, some kind of pre-flight check, to make the best of your performance.

1. Ask your recruiter

Any decent company makes sure that recruiters make the time to prepare candidates and very often you don’t have to ask. But just in case, this is what I have seen available in the wild:

• Most common, a 15-minute prep meeting with the recruiter in which they will go through the topics of the interview and give you some example questions. Sometimes they will go a bit deeper into the interviewers, their role, and what they expect to hear from you.

• Print material, sometimes companies will prepare some kind of description of the job and the interview stages. If those are available try to rack up as much information as possible. Meta is famous for having amazing prep material

The objective here is to collect as much intelligence as possible so that you can use it in the next steps of this checklist.

2. Prepare to reverse interview the panel

You’d be surprised how many companies will mention in the hiring decision meetings “the candidate spent time researching the company”, it might sound silly to you (and in a way I agree) but this is used as a signal to understand if you are serious about your job search.

So spend some time going through the company website, and LinkedIn pages, and read about their mission, history, financials, and latest news.

So that you can prepare a barrage of questions for the panel aimed at understanding if you want to join this company and impressing on them the idea that you have been thoughtful about your research.

You cannot imagine how many times people ask irrelevant or dumb questions that they read on LinkedIn like “What doubts do you still have about me after this interview?”, as if an interviewer would tell you the truth at that moment.

Instead, think about what you learned about this company and what you are curious about, also take notes during the interview if you can, to go back to certain points that were raised by interviewers.

Some tips on what I do:

• Often an interviewers ask a hypothetical question on a problem you might face in your job and you can feel that this is something that they are facing in reality. A good question to ask is “You asked me how I would solve X, is this a problem you are currently facing? How are you dealing with it?”. This has the benefit of showing that you are actively listening to them and also showing you what kind of mess you will have to clean if you get hired.

• Check the most recent news on the company, especially financials and product-related, so that you can come up with something very relevant like “I read the latest earnings call, and the CEO said that you are working on project Superman to focus on AI. What do you think of that? I read the timeline and it seems very ambitious” or a simpler question like “Are you worried about competitor X growing faster than you in the Y market?”. Again this is two-sided, it shows that you have been doing your research but also shows you how engaged people are in that company: do they have a PR-approved answer? Do they have a genuinely excited answer or a genuinely not-excited answer?1

• If you are interviewing for a startup or scaleup, ask very detailed questions on reporting lines and team structure. You can learn a lot about how they think about it. Do they have already 6 managerial titles in a startup of 100 people? Red flag. Do they say “titles are not important” but they have 3 VP of Engineering and 4 Principal Engineers? Red flag.

• If you have been an interviewer before, use your experience to spot yellow/red flags in your conversations and dig deep into those topics. It’s already hard to join a decent company, try to find everything that you can in advance.

The bottom line is that those questions don’t have to be smart but relevant. For me interviewing with a company is a journey of discovery in which I decide only at the end if I would like to join if they make an offer, never at the beginning.

3. Facts are nice but stories are better

“Never let facts get in the way of a good story” might be a bit too much in this case but it’s important to remind yourself that if you want to keep your audience on the edge of your seat you need to have a good story, not only good facts.

Hopefully, your CV will contain a bullet list of achievements that you are proud of:

• Reduced loading times of the main landing page by 50%

• Achieved business targets and increased revenues by 10% totaling 1M$

Those are your conversation starters, now you need to have a story around those numbers.

It’s understandable that, if you are not used to storytelling, you might be thinking at this point that this advice is completely useless for you. Don’t despair! I have some easy tricks to build your story:

• Start writing down a bullet list of the main salient point of the story in reverse chronological order. Why reverse chronological order? Because you minimize the risk of writing down completely unrelated events.

• Now get those bullet points and map them out on the best structure for storytelling that I know: Dan Harmon’s story circle. I can already hear the objections here, but trust me and try it out yourself.

  

• Now you have a decent structure is time to tell the story, and there is only one way to learn how to tell the story. Practice telling this story, add emotions and details, no need to come up with something that isn’t true, this is real life, just make sure this is a nice consistent flow that is easy to follow and is not too long.

• Make sure your story checks all the boxes of the STAR/SOARA interview style so that they find it satisfying from a formal perspective

• Practice, practice, practice. You can take a few minutes to tell a story, but practice this with real people if possible, you can judge from their eyes if you are losing their attention or not.

4. Have decent answers for obvious questions (even the dumb ones)

Whatever the company there are always several questions that you can predict in advance, either because the recruiter told you already about it, or because of your role and experience.

Make sure to prepare decent answers (stories) for commonly asked questions like:

• How do you spot talented people and help them grow? (Yes even as a senior individual contributor)

• Can you tell me of a time in which you made a mistake? How did you solve it?

• If we ask people that have worked with you in the past, what would they say about you?

• If you look back at your career, what is the single achievement that you are most proud of? Why?

• What motivates you to do your best work?

It’s tricky to come up with answers on the spot if you have not prepared in advance and/or you don’t have a lot of experience interviewing. So really try to think hard about what questions are kinda obvious. Even if you don’t get asked the same question you can find a way to weave these stories into the answer and bring the ball in your court.

Don’t forget to prepare answers to dumb questions! This is a big weakness of mine, when I think of being asked clichés like “Why do you want to join our company?” my skin crawls and my brain refuses to even think about an answer to that question. But I am a professional and I prepare for a question like that or “What are your biggest weaknesses”.

Always prepare some positive, but not too positive, answers that don’t expose you to follow-up questions. Something like “The reason why I am excited to join Evil Corp. is because I believe that this is a company in which I can learn a lot and at the same time I feel that some of the things I have learned in my past experiences could add value in the team”.

5. Story of your life

Every interview starts with an introduction, this is a great moment to highlight something about you that is a strength and that you want them to remember.

Again go back to using the story circle, but this time think more carefully about where to start, depending on your age, your graduation might not be that compelling even if you graduated at Harvard. Instead, find a moment that you think is a watershed moment of your career, and start a bit before that.

For example, I always start my intro from the moment I moved to the Netherlands, then move forward to the present and then briefly talk about what I did before moving to the Netherlands.

Your story needs to be tailored to the company you are talking to, I had multiple roles across my career and, while I could just skim over those equally, I always spend a bit more time on roles that I think are relevant while I skim over to others that I don’t think are that important.

Practice and practice again, the story should be short, enjoyable, and crisp.

Also, listen to your interviewers’ introduction to find something you can relate to, try to weave that into your story, and point out commonalities to make them feel closer to you.

6. Stay in character

I cannot count how many times people have told me that “we are lucky” in Technology because we don’t have a dress code. Every time I have the same reaction, take a deep breath and start “Actually…”

Because we do have a dress code, just that everyone is so used to it that they don’t notice. An example to prove my point, look at Mark Zuckerberg in a suit and tell me if that looks natural or if you feel that something is wrong.

This is sometimes used as a marketing tool, for example, in a famous coffeeshop in Amsterdam where everybody is dressed elegantly and the security has a bowler hat), but unless you have a very specific plan, stick to the dress code and expectations.

I always dress for an interview with either a hoody or a sci-fi/movie-themed t-shirt and jeans (unless I’d interview for a bank I guess). So that the interviewers get what they expect, they expect a tech guy and I am giving them the tech guy.

What if you normally dress differently from your professional dress code?

No judgment from my side, just keep in mind that you are now potentially surprising them and it’s better to not avoid the topic but rather try to make a joke on it.

You have prepared the way you dress, now you have to prepare the way you come across.

I wish I could say that it didn’t matter if you are an introvert or extrovert, if you are having a good day or a bad day, but it does. Especially in a remote setting, I cannot count the number of times I heard “The candidate wasn’t energetic/engaged” and this will affect you negatively.

This is a performance! So you need to practice the ability to channel your energy and start smiling and be sociable the minute the call starts. I know is hard, it’s very energy-consuming for me as well.

I have learned the technique by doing comedy improvisation and it’s probably the hardest tip I am giving here: practice at home alone the ability to go from calm and relaxed, to jumping and screaming, and then back to calm and relaxed (you can see why I am advising to be home alone). When you are comfortable with increasing and decreasing your energy at will, you just need to channel that energy for the interview and keep it up.

Let’s close this up

I cannot stress enough how much an interview outcome is driven by your expectations and feelings, it is hard to care about something and at the same time not worry about the outcome and there is no “sure” strategy to get a job.

I have three final pieces of advice for you:

• Find a friend or an ex-colleague to practice mock interviews. It’s so crucial to prepare in advance and it’s not something you have to do for every company, once you have your story straight it gets easier

• Embrace the messiness of the process and remember that most companies suck at this

• Go through the interviews thinking that you are the one deciding whether you want to join this company or not

Good luck!

Some time ago I wrote a post called “The silent killer of big companies” on how I explain the theory that the lack of visible and measurable impact on the business creates perverse incentives in big companies.

This time I want to use a different lens, because I believe we are now able to see a real world example of the Innovator’s dilemma and it would be a shame to not dive into it.

How Google became Google

Some of you might be too young to remember, but finding something on the internet in the 90s sucked big time.

The web was dominated by portals that were curated into categories and making sure that your site was reacheable by someone was an hassle (and not very succesful). Then Brin and Page had the intuition that, if we could define how relevant a site was, then people could search for some keywords and find sites that contained the keyword and were high quality.1

All of this served on a clean page that looked sleek and even had a cocky button called “I am feeling lucky” just to demonstrate how good the algorithm was.

Everyone loved it and, even in the middle of the dot-com bubble, Google became a sensation.

This is not enough to explain how Google became Google.

To grow they needed a way to make money, monetize that excitment, and they looked at what else sucked on the web: advertisement.

It might seem crazy today but at that time you would find large ad networks just rolling any kind of ads in any kind of site, it was literally just reproducing the advertisement of newspapers. You can also imagine that click-through-rates (CTR) for those ads were quite poor and there wasn’t so much money made with ads on the web.

So the intuition was, in hindsight, pretty simple: what if we could increase the CTR by serving better (more relevant) ads? Advertisers would pay a lot of money for this.

And they were right! Spawning an entire new industry and supporting the spectacular growth of some companies that learned how to accurately use this tool to increase their revenues in a scientific manner (looking at you Booking.com).

More eyeballs == More money

This new model meant that all that Google needed to do was to make sure people used its search engine as much as possible, so they could scientifically link user attention and time spent using Google to revenues.

This is why Google decided to modernize a bunch of services and give them away for free (Gmail, Chrome) because the user interactions and their attention was all it needed to grow their revenues.

The company entire goal was to feed the engine, the entire organization was bent over feeding the engine.

And Google became the behemot we know (and love?).

20 years later Google is still feeding its engine

Compare Alphabet’s (Google holding company) revenues with similar tech companies (source: https://www.visualcapitalist.com/cp/big-tech-revenue-profit-by-company/)

Now look at Microsoft, Google main competitor:

Or Apple:

What do we see?

Google has never developed a true alternative to ads, only 10% of its revenue come from a different business (Google Cloud) that is loss-making and heavy from an operational perspective. Plus another 10% comes from services that Google is slowly killing (Nest and Fitbit).

Microsoft on the other hand is much older than Google but it was able to save itself under Satya Nadella and diversify away from Windows and Office, creating a much more robust split.

Even Apple has a strong financial services revenue stream with Apple Pay.

The purest form of addiction

Google is not alone in this vulnerability obviously, I worked for many year for Booking.com and until the day I left the growth engine is still the main focus of the company, but what stands out is how blatantly Google has tried and failed to diversify.

Killed by Google

Google prides itself for his ability to kill projects that are not working, but something has gone terribly wrong if you do it so often that someone makes a popular website about it. And I think that Google Domain being sold off is a great example of where things go wrong inside Google:

• Google Domain is a wildly successful product, with tens of millions of domains registered and hundreds of millions of revenues

• It is impossible to lose money on a product like this, the infrastructure requirements are trivial, you only need a few lawyers to deal with law enforcement and court cases related to those domains but that is priced in the domain registration fee2

• It is a product that follows the usual strategy of Google, give you a service that normally sucks so that you can use the closely related services (Google Cloud Platform)

But it got killed anyways, even worse, they killed also Cloud Domains.

This doesn’t make any sense, or does it? Any avid user of Google’s services can see a common thread across all product offerings, Google spends as little as possible on Customer Service and dealing with their customers.

And I am convinced that, in Google, any product that needs any kind of operational excellence mindset is seen as a needless hassle that isn’t worth the money. What’s 200M$ when ads make 60B$?

Perverse incentives

Google is the company that kickstarted the LLM revolution with their seminal paper “Attention is all you need” and used the transformer technology to improve Google Translate but didn’t invest heavily into disrupting the search engine.

So another way that big companies can fail is to get addicted to their growth engine in a very successful industry and never develop the skills to be successful in any other way, making the company extremely vulnerable to market shocks or by the action of competitors.

Those companies recognize the risk and they get scared of losing.

Any bad press is to be avoided at all costs, any mistake coming from innovation is unacceptable, every dollar must be spent toward the precious engine. So they fill their ranks with lawyers, PR professionals and make sure process is the dominant force in their company. All to defend the status quo.

And this is how innovation dies, how a company like Google can die.

But there is hope.

Google has recognized the threat and reorganized their AI/ML divisions heavily and started pushing a lot of GenAI products to protect their core.

Will they again kill this effort in a year from now? Only time will tell..