The Strategy Memo #4

1. From tech to Academia

"Hello Stranger" you might say, as I know it's been a while since my previous edition, but as my grandma always use to say "Better late, than later", so let's get down to business.

Many changes have happened over the last couple of months that lead to this hiatus, including my 180 degrees move from tech to academia, and on this edition I wanted to work out exactly the main differences I've seen so far to hopefully shed some light over it for all of my tech colleagues that most likely see the academia as a black box - just like me.

One of the core changes comes down to the own nature and approach when it comes down to learning. In tech, and I'll assume corporate in general, there is clear preference towards practical and technical learner, to which I'm no exception. We're looking for knowledge that can be applied on the short-to medium-term, that's why the teaching approach that fits better with us tends to be the one filled with cases from real companies, so that in the end we understood that this knowledge can be leverage further down our career, with a clear ROI.

In academia though, we tend to see broader theories and concepts that not necessarily have a clear applicability on the spot. This difference though doesn't mean that one is better/worse than the other, but simply is linked to the expected outcomes you want to leverage from each. As in academia you're goal is to produce knowledge, it means that the process will be longer, require far more bibliography, format and peer reviews, but in the end of the day you're building knowledge that will last far longer than technical skills. As an example here I'd even call out that in 2025 in one of my classes in my masters of Business Research at Universitat de Barcelona we're still reviewing Michal Porter's papers and dissertations, and even during my business course at Business Training Company we were analyzing one of his frameworks.

Interestingly enough though, is that for some research-heavy industries such as Pharmaceuticals, Manufacturers, and Artificial Intelligence, the bridge in between these 2 is not that distant. OpenAI which figures as one of the most prominent tech companies nowadays is on top of it all a research company, employing and partnering with top research institutions (e.g. universities) to push its model developments further.

Bottom-line here is that each person has different incentives and goals when it comes down to learning, and based on those, a more theoretical vs technical approach might be the best fit :)

2. OpenAI "App store"

Its quite interesting to see how the company has diversified its operations over and over again over the last couple of years, expanding into Agentic AI, Zapier-style automations, Consulting and now in Distribution. With that said, I'd be quite concerned if I've build my whole business value proposition around it being a GPT wrapper - as sooner rather than later they might verticalize this business as well :)

Now with the movement of ChatGPT apps from the "GPT store" which I honestly haven't see that much value before, given the constraints to the GPTs you could develop natively there, a major change starts happening within the distribution industry, where the whole experience of integrating your company to the titan, can become seamless. When this was announced a few interesting things happened - #1 Companies feature in the release saw a significant uplift in market cap ; #2 GPT put its first feet in joining the exclusive club of app distributors, leveraging its massively 800m users.

The question though when it comes down to this, disregarding wether it will work out or no, its related to the rules and transparency we'd see in this new "App Store". As discoverability increases in LLMs vs Google / App store, how smaller and independent developers will survive versus status quo players - how the model will weight out Booking, versus new incumbents? We'll need to wait and see

3. Super Pumped: Inside Uber’s Wild Ride 🚗

If you're looking to get into the backstage of one of the most iconic and controversial tech companies from the last decade or so, I cannot recommend you more Super pumped.

Some of the key items highlighted there can help paint a more accurate vision of the ride-hailing industry and how Politicos, Board and corporate finance play a major role when it comes down tech, either enabling the company further or blocking its full potential.

1️⃣ Public Policy

The history of the ride-hailing industry could not be told without a deep emphasis on the role Public Policy teams, and the company's approach towards governments for its first ~ 8 years of operation. Pushing into grey areas of regulation, and disregarding pushback in the main incorporation of the values "move fast and break things" can bring short-term benefits, but has high risks on the company's long-term sustainability

2️⃣ Digital Surveillance

There is a fine line in between optimizing for the company and stakeholders main interests, by collecting data to improve the overall user experience, and capturing and leveraging sensitive user-data in the company's behalf. "Greyball" initiative is a great example of when companies go too far in this sense, and even other tech companies have to call it out and draw stronger lines.

3️⃣ First-mover advantage

In Brazil, when Uber launched, it was synonymous of the standard Private drivers, that usually fit into the Uber X category. Interestingly enough though, they were not the first players operating into this segment, as they've started with the "Chauffeurs" /black category first. Other companies, including Lyft got there before, but Uber due to its network effects and access to capital was able to piggyback on it, and leverage it far beyond the first "innovators".

4️⃣ The board role and dual class structures

For those that always struggle to understand how the board of directors oversee company's operations, this is a great walkthrough of how these entities are formed, and how founders might fight work arounds, to ensure majority when forming their boards, by leveraging dual class / super-voting structures, which is the case of Uber and Meta. In the same lenses, we see how this structure might seem a good idea when the company is performing well, and a bad when it isn't - bringing jeopardy to it.

5️⃣ Venture Capital

Uber is definitely one of the first companies to start flying high in terms of private financing rounds, leveraging quite well the momentum post the big tech IPOs, when non-convention players wanted to get a piece of the tech markets and its dreamy returns. At the same time though, the easiness of access to capital, with weak accountability mechanisms, including for a couple of years an absence of a CFO, led the company to make short-term investment decisions with low to no-return in sight.

Bottom-line if you want to get into the nitty gritty of one of the most competitive industries in the world, definitely check it out

4. Careless People

Few books have hooked me, intrigued, and disgust me as much and at the same time as Careless People: A Cautionary Tale of Power, Greed, and Lost Idealism by Sarah Wynn-Williams.

I came across this book as a recommendation and cannot vouch enough for how relevant this book should be for anyone working in global tech companies, or any other global companies with as much impact on society as tech.

The author was an-executive at Meta, for years, leading global policy agenda together with regulators. An ex-UN with a strong vision on how the social network would actually impact the world for the better - if I wanted to.

Despite the biographic behind the scenes factor of this book, which is gonna be quite interesting for anyone on the field to feel like they are - to quote Hamilton "In the room where it happens", what is most astonishing is the expose of how key leaders across our industry when faced with ethical and moral dilemmas have chosen over and over again the careless path, with a clear sense of disregard for the responsibility of their actions.

In a world where big tech executives gain more and more relevance globally, their roles swiftly (or not) lean towards the ones of a kingmaker, as they have the tools & resources to shape how people behave and think, leveraging data on some of our most vulnerable and dark moments, and here I reference the research presented by the author on how Meta was selling targeted beauty ads to teenagers aged 13-17 years old based on moments where they were feeling vulnerable with their bodies e.g. when deleting a selfie after posting.

This carelessness of the company doesn't extend only to their users, government impact and so on, but can also be felt in their culture when an employee convulses in the middle of the floor and their boss ignores, or when someone is framed in a performance review as "unresponsive" when they are on coma and a maternity leave quite after.

I share all of this as an intro to call the attention to the relevance of these topics and invite you to go over this amazing book and be as astonished as I am. After doing so, you're gonna be asking yourself the same questions, which hopefully can drive you and your companies to the right direction --

• Am I being careless?"
• What would happen beyond the bottom-line uplift if I do X
• What are the unintended consequences of my actions
• If my product/service has any sort of negative consequences on society, how I will address it timely?

Well, hope you enjoe this edition, and see you again in 2 weeks!