When I started studying computer science in 2003, working for a Big Tech company was a dream almost impossible to reach for me. I was born and raised in Spain, and that’s also where I went to college. Studying over 5000 miles away from the tech scene of Silicon Valley had an interesting effect on me, I’d watch Apple’s tech events and Microsoft’s product announcements as if they were Hollywood movies. I could never imagine myself being part of them.
The main reason why Big Tech companies felt unreachable was because none of them had software development centers in Spain. The only way of working for companies like Microsoft or Google as a Software Engineer was to move to another country, which made the dream feel more unattainable on top of the already challenging interview process. A lot of talent was left untapped in Spain, and a lot of engineers who dreamed of an opportunity in Silicon Valley never got it.
It’s Saturday morning, and my phone has been burning for the past few hours. Just after I wake up, I stare at the screen and I have several messages from my parents, who live on the other side of the world, telling me that they miss me and that they are ready to talk.
As an immigrant in this country and with all my family living in Spain, this is not an unusual situation at all. Keeping in touch with your loved ones across different time zones and geography is challenging enough already. You have to add the technological breach existing between their generation and mine to make a perfect cocktail for frustration and bad quality communication.
If you have never heard about Deutsch + Gosling’s fallacies of distributed computing, you are missing out big time! I encourage you to check them out here. Those delusions are widely considered in the distributed systems field as some of the most painful assumptions any junior systems designer, or architect can make. I like to call them “career-limiting choices”.
When I first learned about these eight fallacies a few years ago, I decided I needed to keep them around. I wrote them in a piece of paper and taped it outside of my office. The piece of paper is still there, except that it now has eleven statements – I guess some random folks added a few more fallacies.
As a product manager, it is critical to have a meaningful roadmap with a backlog of work. Being able to ideate and constantly iterate makes our products better. However, it is critical that we are able to find which of our ideas are going to be the most impactful ones. Over the past year, my team has been working on refining how we approach this and found some things work better than others. The following are some of the things we found really useful.
1.Understand the goal – the first thing you must do is to really understand what is the goal you and the business are trying to achieve. If there is any misalignment you must align before continuing. It was amazing how many times we went and implemented things where the goal was not understood, or it was misaligned. Having understood this from the beginning would have saved us a lot of time and resources. Understanding the goal will take you to different paths, for example, a goal of driving adoption will lead you to do different things than driving for revenue or usage. If you do not understand this, you will cycle and leave things to chance.
The past couple of weeks have been a big roller coaster for MoviePass. I got to experience the Thursday July 26 outage when I was going to see a movie with a friend. We were upset but decided to go for happy hour instead which turned out to be great. The next day we found out it was because they had run out of money which indicated that the end was near. MoviePass was able to get their emergency loan and service was restored. On Friday my friends wanted to see Mission Impossible but the option was grayed out however, after refreshing several times, I was able to get a ticket with an outrageous $6 surcharge. This grayed option turned out to be a change in plans where new movies were not going to be offered anymore. This was a breaking moment for me. I had to make a decision to stay or not before I would be charged the next month.
How many times have you heard that Artificial Intelligence (AI) is humanity’s biggest threat? Some people think that Google brought us a step closer to a dark future when Duplex was announced last month, a new capability of Google’s digital Assistant that enables it to make phone calls on your behalf to book appointments with small businesses. You can see it in action here:
No joke. Google Assistant will start making phone calls to small businesses to make appointments on you behalf. It's called Google Duplex. The AI caller even adds uhmms and hmms #io18pic.twitter.com/r5Ie33YFEc
The root of the controversy lied on the fact that the Assistant successfully pretended to be a real human, never disclosing its true identity to the other side of the call. Many tech experts wondered if this is an ethical practice or if it’s necessary to hide the digital nature of the voice.
Last April I decided to take a big jump from building enterprise software to building consumer products. I am very grateful to have found a place that would allow me to learn the ropes of the consumer business without sacrificing any of the internal goals. This past year has been a great learning experience with big learnings and here are my key takeaways.
Enterprise vs Consumer? What’s the big deal?
Building enterprise software is a different beast than building it for consumers. They share several core components such as requiring a secure, reliable infrastructure and following best software practices including sprint models. However, I see three key differences.
Difference 1: Knowing what your customers want
In the enterprise world you go out and talk to your customers and it’s fairly clear what they need. Even building roadmaps is fairly easy. In the consumer world it’s not as easy. Because you are building software for millions of customers you can’t talk to all of them, so you have to find proxies to it. Unfortunately, many times these proxies are not perfect hence you require to test a lot (and I do mean a lot). On the good side, because consumer software is used right away you get instant feedback and know if you have a success or a fail.
I looked at the “Buy Bitcoin” button and paused, was I ready to do it? had I read enough articles explaining what is blockchain? 2017 had just closed after an all-time high for cryptocurrencies, and according to many enthusiasts, it was just the beginning. I felt like I was missing out, so I pushed the button and sat back. I felt confident, but in reality, I had no idea what I was doing.
I passively consumed news about Bitcoin for years, but I never went deep enough to properly understand the technology behind it and its potential. Even though I followed the ultimate rule of “investing only what you can afford losing”, the truth is that I only began to comprehend blockchain technology after I already got my feet wet. I started losing money shortly after my first order completed, these are the 4 lessons I learned since then.
1. A big Bitcoin dive can drag the rest of the crypto market with it
There is so much speculation around cryptocurrencies and so many people investing in them without having a clue, that a moment of panic can snowball into a sudden market crash. A Bitcoin crash can affect many investors’ confidence in other cryptocurrencies (or altcoins), dragging their price down as well.
Many altcoins are variants of Bitcoin with small code differences, making their prices change practically in parallel to Bitcoin’s.
I have been waiting since college on RFID’s failed promise to deliver a walk-away checkout experience, and Amazon finally made it possible. After reading my co-blog writer’s experience in the Amazon Go store I had to check it out for myself and was excited for it. All my friend’s pictures were of long lines, but thankfully I am a morning person and there was no line when I got there. My goal was to pretend I had no idea what it was or how it worked. My experience overall was good, with the exception of the on-boarding process. I was greeted with a condescending “oh, you don’t have the app?” and was asked to stay aside. My T-Mobile reception was very poor so it took me a bit to get started. Once I downloaded the app and signed into my Amazon account everything was smooth. Mission accomplished! In this post, I’m not going to talk about the actual store (Ivan did a great job already) but about the implications of the first tangible and successful AI automated store.
Automation has always been part of our history. Automation has helped us evolve into the society we have now. Such as, automating how we grow and crop food so we can have a good food supply, the industrial revolution to make things faster and cheaper, the assembly line to make them even faster and cheaper, and finally computers to automate processes and tasks. Now, AI is here and it will automate all of our productivity.
2017 has been the year of the smart speaker. Amazon’s Echo Dot and Google’s Home Mini are currently selling for around $30, which makes them a popular Christmas gift. Using an Artificial Intelligence (AI) has never been cheaper and it’s finally reaching critical mass.
Companies are investing on AI more than ever: natural language recognition still has to improve a lot, but the current algorithms are already impressive. My favorite example: it’s now possible to ask “how long would it take me to get to Starbucks on 15th Ave?” and get an accurate response with the right assumptions. What a time to be alive!
All of this progress comes with side effects: having to learn how to talk to a machine. Often, people start talking without the wake-up keyword, and sometimes they forget to check if the device is actually listening, getting confused when there is no response to their inquiry. Talking to a machine is not easy and usually, very unsatisfactory.
Perhaps that dissatisfaction is what makes us be less aware about our manners when addressing an AI. What would you think if someone interrupted you mid-sentence with a sudden “STOP”? What if someone kept giving you orders relentlessly, never pausing to thank you? That’s how most of us talk to AI’s like Alexa or Siri, never saying “please” or “thank you”.