Idle Time

As a thought experiment, imagine you were restricted to use a single device to interact with the whole digital ether. Exclusively one: laptop, tablet, smartphone, e-reader, you name it, but for the rest of your days, this is the one and only device you would ever be "touching". The good news is that you get to choose, of course.

I have presented this riddle to many friends and, invariably, their answer is always the same: smartphone. To their surprise, my answer is — and has always been: old fashioned PC, precisely, macOS[1].

My answer to this question has its raison d'être, since most of my waking hours go by in front of a computer. Not just at work, but even during leisure time. The computer is the tool I use to funnel my creativity: from writing, coding, designing, reading, communicating… but also my go to device for absolutely everything.

I do not dislike smartphones, I understand you can get plenty of stuff done with them, but for me they never "clicked" as creation tools. My iPhone home screen is almost "factory settings" and the main uses it gets are limited to podcasts, audiobooks, music, messaging and hailing a cab from time to time.

The computer is the machine I grew up with, the one I discovered a whole new world throughout: from DOS to the dawn of the Internet, I learned to love its design, appreciate its craft, but ultimately, I became fascinated by how it worked.

For these reasons, I have always been drawn to the keyboard as an input device, hence keyboard shortcuts are my thing. Although I don’t use them as much as I love them, still today, every time I invoke one, something feels right deep inside.

My approach to remember, use and learn new keyboard shortcuts has always been the same. I do not employ heavy machinery such as Text Expander or Keyboard Maestro. I just try to be aware and spot routines I repeatedly perform with the mouse, until the inevitable thought of "I’m sure there’s a shortcut for that…" pops up. Then research for the shortcut and meticulously log it in a "Shortcuts in Use" note that has been in the works forever.

Believe, after this 500 words introduction detour, the story eventually lands somewhere. As a matter of fact, this post was inadvertently and without permission seeded in my mind a few months ago, when this product escalated to the very top of the Product Hunt ranks. It caught my attention immediately because somebody just "productized" the list I had been curating for years, I loved it.

After a more than deserved "upvote", the product itself inspired a broader examination on how we interact with our devices and the impact they potentially have in our minds.

Before we dive in, please, keep in mind that these lines are not grounded in academic research, there’s plenty of studies available documenting this phenomenon. But rather my personal journey and a humble observation on how to ensure our time is well spent in front of our devices.

My working assumption revolved around the idea of how much of the time spent in front of a computer had actually become idle time. Non-productive time, without a clear task or particular goal to achieve, but rather wandering around, just being with the computer, or well, procrastinating.

For a curious, monkey mind, sitting down in front of a computer with no predefined task to accomplish, will inevitably become a recipe for failure. In my particular experience idle time meant playing around with some app settings, re-reading an article or rethinking the way my filing system worked. Unremarkable activities that directly translated to anxiety.

While in idle mode your mind runs fast, it operates in autopilot, but it is going nowhere. This is a nasty loop, because it feels effortless and comfortable being in idle land, but at the same time you are also aware you shouldn’t be there in the first place.

Well, at this point you might be wondering what keyboard shortcuts have to do with idle time and if there’s even a connection between the two. A few months ago, I was wondering exactly the same. It turns out they have a lot to do with one another and, indeed, such connection exists.

The trick that ties everything together is one of the simplest, silliest things I’ve done lately, that has had a major impact in my daily life: setting aside the mouse to the left of the keyboard.

Its immediate consequence: using the computer now required deliberate effort.

Thoughtless, fast paced, muscle memory mechanics were not available anymore. Therefore wandering was not an option because the ease in which I used to navigate the computer was completely gone. Every single time I was about to fall back to idle mode, I encountered the inconvenience of a lefty mouse, not easy, then the itch immediately vanished.

The computer wasn’t effortless as it used to be, I just unlearned — to put it in Star Wars terms, thus our relationship was changed, forever, for the best. Now every time I sit (well, stand) in front of the computer I have a clear goal in mind. It has earned back its purest creation soul.

It is a funny feeling, though. Everything I could "do" now ties back to my keyboard expertise — or, well, if I want something badly, I know a fall back to the uncomfortable mouse experience is still an option. This has inevitably expanded my shortcuts portfolio in ways I could have never imagined, to the point that I stopped logging the new ones onto my note — and where came in handy :)

Finally, and most important, the anxiety associated with the idle time has completely gone away and I find myself in "flow" state more often than ever before.

That was quite a long story, so, to wrap everything up, I want to go full circle, back to Michel van Heest, the man behind This week I randomly came across his Medium post about the "behind the scenes" story of his product, which I not only clapped the shit out of it, but also reminded me how much my life has improved just by embracing the keyboard.

[1] That’s a subtle distinction though, because the question presumes platforms, which is not entirely fair. I’d rather use white labeled hardware running macOS, than a MacBook running Windows or some Linux distribution. But that’s beyond the point and food for an entirely separate conversation, that won’t be happening in these lines either.

Months and Terms

I have been receiving quite a lot of feedback from my recent post about enrolling the Udacity’s Data Analyst Nanodegree. Unexpectedly, even prospective students contacted me out of the blue asking for some advice on whether they should enroll or not, which totally came as a pleasing surprise.

One of the things that recurrently showed up during these conversations was the fact that I deliberately sticked to the monthly structure rather than switching to the updated term model, given the opportunity.

This is actually a great question, but one that I am not going to answer here. I will instead focus on why I think the term-based structure is a superior approach when it comes to incentivize student retention. On top of that, I will also drop some thoughts about bridging the gap between offline and online education and how to replicate the social aspect of in-person programs into online experiences.

From Months to Terms

All Udacity programs used to be offered as a monthly subscription. The student paid each month and was presented with an incentive to get to the "finish line", thus decreasing drop outs. The incentive was no other than: get half of your money back if you complete the program in less than a year.

It is a clever approach because it seems the student would be primarily driven to finish as soon as possible since money is at stake. The sooner the student graduates, the less money will end up paying. Although after taking a closer look at the issue — but also having gone through the experience myself, I would argue that this is not how incentives ultimately work, at least when it comes to education.

A lot of research has been already published around the topic, but long story short, the takeaway is that extrinsic incentives (getting some of your money back), only work to a certain extent. Udacity’s money back strategy is a paradigmatic example of these dynamics at play. Getting your money back is a perfectly reasonable motivator, but when dealing with hard, creative and non-repetitive tasks, there is something more at stake: we just stepped into "unreasonable territory".

Here is precisely where intrinsic motivators kick in and this is why a term-based model is better suited to recreate the conditions for them to thrive.

A Time Constraint

On the other hand, term-based programs provide something far more valuable than getting your money back: synchrony and a time constraint. Synchrony is all about the sense of community and sharing the learning experience with other students. The time constraint helps handicap the program from a time perspective.

While the monthly model places an imaginary, soft deadline of twelve months to get your money back, it doesn’t set a specific point in time where the program ends. In other words, as a student you can get stuck, indefinitely paying every month until the end of time, without having graduated. The term structure instead delivers a much clearer time framework, because you either graduate within the given term, or you don’t.

A healthier relationship comes out from the fact that if you don’t commit to the given time frame, you won’t graduate. Which ultimately means you’ll lose all your money. A clearer, more transparent and of course, far more effective value proposition.


Finally, and most important, a term based approach brings synchrony to the cohort and the sense that you belong to a larger community, aka. peer pressure.

During my time enrolled at the DAND I felt lonely. I knew more students were simultaneously going through the same experience, but I had no way to "feel" it. Despite there was a dedicated Slack community aimed to bridge this gap, overall, it felt scattered and it was difficult to cut through the noise. Each student was in an entirely different stage of the program and the sense of "class" was nowhere to be seen. You were absolutely on your own.

Terms improve, to a certain degree, these dynamics. I don’t have Udacity’s exact graduation numbers, but the fact that each term starts at a fixed schedule must help students feel closer to the rest of the group, sharing questions, struggles and most important, aligns them around the vision of graduating.

Despite trying to recreate the social aspect of an offline experience through an online program remains extremely challenging and something nobody, as far as I know, has entirely figured out.

Online experiences are exclusively focused on having cutting-edge curriculums, the latest and greatest materials, but still missing the point on how "the 99%" of people learn. These programs are truly amazing, but sadly targeted to the "1%".

Because at the end of the day, life will throw at you a shitload of distractions and other priorities. The lack of offline attachment to other students and teachers make these programs the perfect candidates to be the first thing you will set aside.

Yet this is a separate discussion, way beyond the scope of this post.

Even though, I do believe a term-based program is a step in the right direction, but still far from the place where social dynamics, arguably the most powerful of the incentives — specially for obligers, can kick in.

Udacity Data Analyst Nanodegree

udacity data science nanodegree

Last January I proudly finished the Udacity Data Analyst Nanodegree (DAND) and this is my attempt — I hope in 1.000 words or less, to publish the kind of post I wish I’d read back before I enrolled: relate why I did it, who is it for and, of course, how the experience was like.

Why I Did It?

Despite Udacity’s Nanodegree programs certainly claim to employ their students[1] in the most cutting-edge, on-demand jobs, the main reason I joined the program was to level up my (data) game in my current job as a Product Manager at Ironhack, not to start a new career as a data analyst.

More often than not, I found myself dealing with situations involving data flows I didn’t fully comprehend. The idea of making decisions without a solid data driven foundation backing it up made me sometimes feel uncomfortable about the path I was leading my team towards. Product meeting after meeting, I had this nagging thought of knowing that there was something missing all the time, that we were not getting the whole picture because of our data ignorance, but still, couldn’t see it.

But let me be crystal clear here before we move on: by "data" I’m not referring to the "big data" everybody is talking about as if it was teenager sex. Believe me, very few people deal with truly "big" data. The DAND is also not about "big data", but neither "big data" was what I was looking for. On the contrary, I wanted to address rather smaller things: statistically inclined issues, biases or widely opinionated meetings that were clouding our decisions and ultimately setting the stage up for an HiPPO driven environment.

After an unreasonable amount of research — lets save this for another post, and factoring in my time constraints, a random Wednesday of April I decided to enroll. It was my first attempt to commit to an online program this big, and I must admit, for better or worse, back then I didn’t fully understand what I was signing up for.

In a nutshell, I didn’t aim to become a fully fledged data analyst — despite Udacity claimed you could if that was your goal. I just wanted to bring the data skills to my current job, hoping they’ll help me with these:

  • Ensure our product team was accurately using and making the most out of our data
  • Set up an environment led by healthy and meaningful metrics
  • Back and make decisions supported by data as an anchor of agreement, kind of a source of truth for our team
  • Leave behind this wild guessing mode we were living in and start doing things right :)

The Program

The whole curriculum was broken down into eight modules (seven plus introduction)[2], requiring a dedicated project delivered by the end each one. Each project came with its own submission process — which they don’t take lightly, where a Udacity reviewer inspects and grades your work until it meets the rubric’s criteria. It goes without saying that in order to graduate you must submit and get all your projects approved by the reviewers.

Despite the program structure has changed a little bit since it shifted to a term based structure, the topics it covers still remain mostly the same:

On top of that, each module and project builds on top of different technologies: R and Python for data analysis and statistics, Numpy and Pandas for data wrangling, Scikit Python library for machine learning and of course, Tableau for data visualization. And if it was not enough, certain modules also brought in additional libraries, which made the tech toolkit even more fun — and complex.

The amount of topics and technologies covered during the program is massive. You definitely walk out of the program with a solid understanding on both the fundamental concepts behind the data analysis and the tools a "real" data analyst will encounter in her daily routine.

This a great approach for the program if its ultimate goal is to put their students in a job ready position with the least amount of time. In my particular case though, I felt the program was a little bit too broad, especially judging by the number of "supporting tools" you have to learn from scratch lesson after lesson.

Let me explain: while learning this wide range of technologies (R, Python, Tableau…) is definitely an enriching experience for the mind, it also dilutes the value of the learning outcomes by changing the underlying technology all the time.

If I were to design the program around my personal outcomes, I’d have bet for a single technology, say Python, and build all the curriculum on top of that. The benefits of this approach would have been twofold. First, the students would have achieved a higher level of "code mastery" in said technology, which would have enabled them to build stuff quicker and with more ease, even after the program. Second, by not changing the underlying technology, the program would have been able to focus more on the content itself and go deeper at every stage, letting the technology fade away in the background.

Months after graduating, back to my job — and not working as a pure data analyst, I often find myself scripting some code with Python and building small helpers to automate some nasty, undesirable ground work. But I’ve to admit that I’ve never touched RStudio, Tableau or Jupyter Notebooks ever since. I’m grateful to be aware they exist, but maybe I could have leveraged that time to go even deeper with Python.

But again, that’s just a personal opinion based solely on my own experience. And don’t get me wrong, the program design is superb, but maybe I was probably expecting something the course was not intended for.

The Experience

Finally, how is it like to go through the program? I won’t lie: it is hard. Although the course structure is extremely clear, the materials are first class and all the projects really engaging, still, setting aside the time to work on your own, without social pressures of any kind, remains the most challenging endeavor, even for Udacity.

I finished the program in eight months[4], but I was not consistent with my schedule and the amount of hours per week I was investing, which I believe is the ultimate "hack" to stay on the program’s track.

The main problem I faced would go like this: the amount of effort it takes to re-engage again with the course is (exponentially) related to the amount of time you spend away from it. In other words, the more time you stay away from the program, the more difficult it gets to just go past the Udacity’s login screen. It becomes an ongoing battle against your willpower.

I suffered from that, big time. I remember some time around June where after over a month without completing a single lesson, the thought of dropping out even crossed my mind. I endured, but the chances of not writing this post right now were then higher than you might expect.

On the other hand I also remember periods where I literally opted out of life and did nothing but Nanodegree. I was pretty unreliable with my efforts and, as far as I can tell, getting this right is something that will totally ease your way into the program.

Besides the disconnection from the social experience, which I definitely believe is the most pressing challenge online courses must solve for, the course was really good and definitely delivered on its expectations. The materials were well crafted, the projects had a clear purpose and the support you receive from Udacity is extraordinary at each step of the way.

So, upon graduation, if you were to ask me: would you do it again? I’d say "absolutely yes" if you are looking for a career move to a data related role. The DAND is the perfect bridge to land an entry level job in-field or even as a prep stage before joining an immersive, full-time data science bootcamp.

But as a "career booster" maybe I should have explored other softer options that would have allowed me to customize a little bit more my journey. As a counter to that, I’d also argue that it is easier to see this pattern looking backwards, now that I’ve already explored the data analyst path. A hypothesis I couldn’t have articulated back when I started, because my depth of knowledge on the matter was way narrower.

Well, no matter what, beyond the program specs, overall I’m extremely happy I enrolled (and graduated) the DAND. Because it has not only helped me out at my job the way I expected and planned for from the beginning. It has, unexpectedly, also proved to be an invaluable resource for everyday life and has transformed the way I perceive, through the data lens, even the smaller situations and decisions.

[1] When I enrolled back in April most Udacity programs were paid in a monthly basis and offered a 50% money back guarantee if you graduated in less than a year. On top of that, there were two payment options, the "basic" for $199/month and the "plus" for $299/month. Only the latter offered (subject to certain fine print) "jobs guarantee" and I quote from their marketing copy: "While all of our Nanodegree programs are built with your career success in mind, you must enroll in our Nanodegree Plus program to secure a jobs guarantee. Since then, most of their programs have been gradually migrating to a term-based structure and their approach to "job assistance", that’s just an opinion, has become less aggressive and more loose.

[2] The DAND program structure was upgraded two times during my enrollment. The first one, in September, was a small tweak to the curriculum structure, which I opted in. The second, in December, was a major change where they moved the whole program to a term based structure — mainly in line with the rest of their new Nanodegrees. Udacity kindly offered me to upgrade to the new one, but I personally sticked to the old model since I was about to finish anyway.

[3] Machine learning is no longer available in the new curriculum, all the contents have been moved to its own Nanodegree program.

[4] Ideally you’re expected to finish in six months, but you got half the money back if you did it in less than twelve. Now the program has shifted to a term model though, the option to get your money back if you were to finish under a certain time frame is no longer available.

Detachment Strategy for the Apple Watch

Apple has hit roadblocks in making major changes that would connect its Watch to cellular networks and make it less dependent on the iPhone, according to people with knowledge of the matter. The company still plans to announce new watch models this fall boasting improvements to health tracking.

Every single time I run into an Apple Watch user, out of curiosity, I ask about their experience with the device. Hence I have heard plenty of valuable feedback, beautiful user stories, but also curious challenges they encounter. But without question the main complain they usually bring up — besides battery life of course, is the ability to untether the Apple Watch from the iPhone.

It is a perfectly reasonable claim though. At the end of the day, the narrative for the Apple Watch is about bringing technology closer, creating a more intimate experience without the inconvenience of having your phone in your pocket all the time.

But this narrative breaks down every single time the Apple Watch loses the "connectivity support" from its parent. Which usually happens when you need it the most: hiking, going to the beach or any activity where you would prefer "not to" bring your phone with you.

Some improvements have been made along the way with the introduction of watchOS 2 and the ability to connect the Apple Watch directly to a Wi-Fi network. But in order to get full autonomy the Watch needs to connect to a fully fledged cellular network, the same way an iPhone does. But of course, it is tricky. On one hand, data transmissions through cellular connectivity drain batteries quicker than BLE or Wi-Fi. On the other, the smaller the footprint of the device, the smaller the batteries you can fit inside. If your challenges come from both ends, it follows that from a technological standpoint, we are quite not there yet.

Regardless, there always have been rumors about Apple becoming its own cellular carrier. Which makes perfect sense, since it would allow Apple to integrate the single most important chunk of the experience they are not in control of. It would automatically translate into seamless activation of the devices, cross-country compatibility, simplification of the product line and an endless list of enhancements ultimately benefiting the customer experience.

But it remains an extremely complex endeavor. First of all, closing deals with operators that are now partners. Then scaling capacity to provide data to all devices, in every single region. Google did something similar last year with Project Fi, but the service was deployed in a more controlled environment, only for selected Nexus models. Which not only accounted for less devices, but also targeted a more early adopter type of user.

Where I want to drive this at is: what if Apple rolled out the next generation Apple Watch with a built-in, low power, world wide, cellular connectivity that helped detach the device from the iPhone. Of course I am not talking about a 4G connection here, but something more like (please, I need a leap of faith here): SigFox. The nature of this network would not be intended to watch videos on YouTube, but rather to receive an important notification or send a critical message that can't wait until you reach the phone.

Probably this would be the kind of service only Apple apps could use in the very early stages. Maybe afterwards would be accessible to third parties through a private API with highly strict rules, as it has happened in the past with the rollout of other Apple products. Moreover, the Apple Watch would be the perfect device to start with: it is already targeting pre-chasm users, more willing to support "experiments", and also operates at a smaller scale than the iPhone does.

It is not the exact same thing, but Amazon has been doing something similar for their Kindle lineup for more than ten years now with outstanding results.

I acknowledge there are plenty of flaws in the idea. But wouldn't it be a clever way to bridge the detachment gap of the Apple Watch, while laying the foundation for a world wide network to power every single Apple device in the long term?

The Ironhack Experience

This Saturday the 2nd of April, I will be enrolling the Ironhack Web Development program, in its part-time format. It spans six months: two afternoons during the week and the whole Saturday, accounting for more than 400 hours of accelerated learning.

Despite it is not as intense as the full-time format, the goal remains the same: turn you into a full fledged digital builder, with the abilities to develop web applications by yourself, but at the same time, embracing best practices and learning the underlying principles behind digital products.

As a campus manager, my daily tasks at Ironhack are far away from technical endeavors. My role consists in managing and inspiring the team, but also ensuring we are delivering on our promise of providing the best possible educational experience.

The main difference with our flagship, full-time, bootcamp program — that has already trained more than 500 people with outstanding results, is the part-time format has been specifically designed for people who is currently employed. The materials team has done an outstanding job structuring all the contents in a way that can be digested, but demanding enough so you can still feel the strain that comes with these intense programs.

I have put a lot thought into this decision. We all run busy lives, and it is definitely a huge challenge on top of anybody who already has a challenging job. I acknowledge that going through this experience will inevitably imply saying no to a lot of things, and despite I’ve been told otherwise several times, I am profoundly convinced that enrolling is the right call.

In this post I will explain why I decided to join, and why I firmly believe that everybody in a managing position, technical or not, should join, too.

My Role at Ironhack

As a campus manager, my daily tasks at Ironhack are far away from technical endeavors. My role consists in managing all aspects of Ironhack’s operations here in Barcelona while executing on the company mission. At the end of the day I find myself not only managing and inspiring the team, but also ensuring we are delivering on our promise of providing the best possible educational experience.

My Role at Ironhack

All of this translates into sales, business development, planning and executing marketing actions, leading hiring processes, ensuring we have an awesome work environment, and representing the Ironhack brand by interacting with students and other ecosystem partners. In other words, I’m kind of the last responsible for Ironhack’s success here in Barcelona, but as you can see, there is no coding involved.

Therefore, the legitimate question to ask here would be: “how come learning how to code, will help you succeed at your job, since there’s no coding required at all?”

Alignment With the Company Vision

I deeply believe that in order to achieve greatness, no matter what your job title is, you must understand, embrace and align yourself with the company vision. It might sound abstract, but I have come to realize that for a company to be successful in a market, for an employee to thrive within a company, and in most facets of life, the alignment with the bigger picture is always a prerequisite for success.

Markus Leyendecker — Harvard MBA student and also Ironhack alumni, has already done an amazing job explaining this issue. As he points out in his article Pre-bootcamp: Why would a future Harvard MBA learn how to code? the understatement of the building blocks of your business is key for anybody that attempts to lead any team or company.

If one accepts the hypothesis, that companies, which are at-heart digital, will continue to outgrow the competition, one should realize why I want learn to code. It follows a very basic logical chain: Everyone working at a company should be able to understand what the company is best at: selling the right product to its customer segment. For instance, one would think that a Boeing CEO would understand, at least much better than a CEO from another industry, how an airplane works and which steps of the value chain Boeing excels at.

I could not agree more. But as devil's advocate one could argue that if a company is not competing in the software industry, and say it is selling razor blades, then code should not be a lever for success. Which brings us to the second point: that software is becoming a transversal discipline.

Digital Transformation

As I already pointed out in The Rise of the Hybrid Profile, programming is not only for programmers any more. Instead, it is starting to permeate across all industries, changing the way we interact with products and how customers want to be reached in order to deploy effective marketing actions.

All the components involved in the creation, distribution and sale of a digital product are, in some way, influenced by the same digital ingredient: code. For this reason, the ones who acknowledge this situation and learn the fundamental principles underlying digital products, will inevitably have a considerable advantage when having to deal with this new breed of products.

What this excerpt from my article conveys is that we should approach each market, business or product, from a more holistic perspective. Meaning that despite certain end products will remain hardware based, its surroundings: distribution, marketing, operations and ultimately, the customer experience, will be profoundly affected by the digital transformation that lies ahead.

Coding at Ironhack

Going on with the razors analysis, the only player that comes to mind that is growing like a rocket, curiously enough, is Harry’s. The blueprint for how to enter a mature, saturated market, leveraging technology in order to enhance the customer experience. Harry’s is not a software company, but I would bet that employs plenty of software engineers and their digital strategy is core to understand their success.

Earn Their Success: Speak Tech

The conclusion that derives from this premise is clear: as a manager you will be dealing with software issues at some point. That might come in the flavor of the project that you are working on or it may be the core competence of your team. Either way you will need to prove that, at least, you have the slightest clue of what you are actually managing.

After more than five years involved in product at tech companies, I have seen plenty of issues such as PMs not respected by engineering because they did not have technical chops, or marketers who were literally mocked for not understanding how something worked. Believe me, as a manager, it is a harsh situation to overcome.

We have drawn some kind of line between tech and non-tech, placing more value to the former by default. As a manager, this is a harsh situation to overcome.

I am not saying this is a good thing, but we have drawn some kind of line between tech and non-tech, placing more value to the former by default. If you want to earn the respect of your peers and make informed decisions you will need to understand how stuff works, and the only way is playing by their own rules.

Management entitles lots of things. But at the end of the day you will find yourself making key decisions and you want to do that through the eyes of every person in your team, even better, through the eyes of the company as a whole. You will be setting the table on behalf of a lot of people, and you will only earn their respect you if you know what you are talking about.

Why Am I Doing This?

In my particular case, first of all, I am doing this because I want to experience first hand what it is like to go through our Bootcamp. I think it is not fair that I am rooting for a product that I have never experienced. I have repeatedly seen how we are helping our students pivot their careers and ultimately turning them into digital makers. I know it is amazing and I know it works, but I don’t know what it is actually like to be there.

Therefore, from an evangelist perspective, I am absolutely convinced that by fully understanding the experience not only I will improve my ability to communicate why somebody would benefit from learning how to code. But also get insight and make a better case for who we might be solving a problem to, but we still don’t know it.

From the inside I hope it will help me better relate to the student experience and have informed conversations with them, as we were discussing before, it is like speaking their language. Because I would be able understand what they are going through, I will have a better chance when it comes to earn their respect. And looking into the future, having this shared connection can also be a great way to create stronger bonds that will help enhance the collaboration with our alumni community.

I have repeatedly seen how we are helping our students pivot their careers and ultimately turning them into digital makers. I know it is amazing and I know it works, but I don’t know what it is actually like to be there.

I also expect to gain credibility from the team, mostly in the academic side. Because I would be able to analyze the full scope of every decision I make for the campus, from the layout of the desks, the acoustics of the room to the number of TAs we will need for the next cohort. Only by having a better comprehension of the market, the product, the team and everything in between, I will make the right calls and earn the respect of my peers, by being able to speak their language.

Again it is about understanding and aligning yourself with the company vision, only then you will be in the position to achieve greatness. Learning how to code is a prerequisite to comprehend the full scope of your company, in education, technology or razor blades. Then that’s the ultimate reason why I am going to learn how to code and why you should, too.

The iPhones 6S

I think that’s a trap — a way to be fooled by your eyes. [...] But it was the 3GS that first improved on CPU performance and gave us the first improvements to the camera. The 4S ushered in Siri integration and a much faster camera. The 5S was Apple’s first 64-bit ARM device, years ahead of the competition, and was the first device with Touch ID. For a typical iPhone user on a two-year upgrade cycle, I think the S years are the better phones, historically.

Iteration and refinement are at the core of great product development. A never ending feedback loop with customers that builds the foundation of the best products. "S" cycles are perceived as minor upgrades because of the same look, but I could not disagree more. Despite the most transformative features of the iPhone have been sponsored by S models, Gruber's points on the underlying thesis behind the S cycles are really well thought.

  • Ecosystem: cases and accessories manufacturers count on this predictability and it makes their business more sustainable.
  • Branding: never thought of it, but it's absolutely true. iPhone is more than a phone, it is an iconic device. Keeping its design consistent and recognizable is the most powerful force Apple has in order to retain this awareness.
  • Predictability: manufacturing at "iPhone scale" is almost an engineering and operations wonder. Having laid out the industrial design two years ahead makes it easier for engineering to plan for the new releases.

News, and Apple News

From all the announcements Apple made in WWDC, I thought one of the most interesting ones was the Apple News app, because it’s trying to solve a problem I have encountered myself for a long time. Finding the best content online has always been a painful experience because there is a lot of great content being produced everyday and it is impossible to keep up with everything, it feels overwhelming.

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