career

Don’t hate the player! Hate the game!

Over years, I noticed that people develop a grudge against coworkers or their bosses.

Often, if not always, this is caused by others goals and job constraints.

Example: “I deserved a promotion, but I didn’t get it because HE/SHE THINKS I DIDN’T DESERVE IT”. Usually this is caused by manager having budget and needing to play bonus allocation tetris AKA calibration. Probably (most likely) if he didn’t have these constraints it would look differently.

Another example: “I hate this guy. He is always against me.”. The reason why somebody oppose an idea is usually because of reasons. Reasons are caused by constraints a person operates in, and past experiences.

Of course somebody may just not like you. That happens too.

Maybe I’m the luckiest employee in the World, but over 7 years I didn’t have boss that sucked. Did I work with some people who didn’t like me? Probably, but I was always focused on solving problems, and cared less about their personal feelings. It also happened to me that I didn’t get promotion/bonus when I deserved it. However, after digging in, I understood why, and it was because of constraints others operated in.

A few years ago, while learning about AI from Peter Norvig (director of research at Google), I learned about Paradox of Rationality – people making rational decisions often end up with worse outcome if they would make irrational decisions. This is foundation of game theory, and obviously happens in life. Did you see irrational outcome coming out of congress lately? Do you think it’s because politicians are stupid? Maybe it’s because of how the game is setup?

Don’t hate the player! Hate the game! Your life will be better 🙂


Facebook Bootcamp is the best thing in the World

After 5 years at Microsoft I joined company, which product I’ve been using for last 12 years :O

12 years at facebook

Before I forget how amazing it was, I wanted to drop a few lines about Facebook Engineering Bootcamp.

When you are about to join typical company you have to make a decision whether it’s a good fit for you. Usually it’s based on 4 or 5, hour long LeetCode sessions with different members of the team. Of course you talk to your future manager, HR is telling you how great it’s gonna be etc.

Facebook does it differently! Your are being interviewed by people from different teams across the company. Not necessary from the team that you are going to join. It’s actually very unlikely that you gonna end up working with any of them. This allows to remove bias, and make interviewing a fair game. Microsoft and Amazon have huge variation between teams. Somebody who wouldn’t pass interview in one team can be a rockstar in other team.

After you pass the interview and join Facebook, you start as bootcamper. You have usually 6-8 weeks to learn facebook engineering systems, and to find a team. You can to talk to as many teams in the company as you want. These are not interviews, but informal chats. Usually short 30 mins meeting, quick coffee or lunch. Some people call it “Facebook Dating” 😀

Once you determine that there is “chemistry” between you and your future manager, or somebody from the team, then you usually work with that team for a couple of days or a week. Like a real work! They give you desk in their open space area, you get some easy task that is related to what they are working on, and you are a team member for the time being.

Don’t worry about good and bad teams. At Facebook there are only different teams 🙂 I was surprised how everybody I met during bootcamp had slightly different interests and all of us decided to join different teams :O

Usually you want to “try” a few teams to have comparison, and to make connections that might help you in the future. E.g., when you will need to work with different team, or when you will be changing teams. This is the best part of the bootcamp. You can literally give you future job a trial run.

I graduated from bootcamp last week and joined Facebook Marketplace Growth team.

I’ll probably drop a few lines about Facebook Engineering systems in separate post, but I’ll just tell you this: imagine that you can have all your wishes regarding engineering systems fulfilled, and it’s better than that 🙂

If you want to learn more about bootcamp check this note 🙂


Leaving Microsoft…

reseting Microsoft PC

Last Friday, September 13th was my last day at Microsoft. Coincidence was that it was Programmers’ Day = 256th day of the year 🙂

It’s been awesome 5 years! I helped to ship the new Azure Portal, turned hackathon project into Microsoft product announced at //build keynote, helped SeeingAI with a few features, and for last two years helped to grow Azure Search. When I joined the team it was a startup. Now, it’s a mature Azure Service. Along with my everyday job I had awesome opportunities to speak at conferences and meetups around the World about my work. During my time at Microsoft I delivered almost 30 technical talks!

Along that journey I met a lot of awesome and inspirational people. Thanks to them my job was my passion. I was very lucky to have awesome bosses. I want to thank Andrew Birck, Ian Carbaugh, Madhur Joshi, Janusz Lembicz and Pablo Castro for everything they did for me. If you end up working for them, consider yourself very lucky!

Special thanks to Steve Sanderson, Scott Hanselman and Scott Guthrie! Their technical talks made me want to join Microsoft, when I was still in college!

Stay tuned for what’s next!


Building Cloud Search as a Service with AI

AI Search

It’s been almost a year since I joined Azure Search team. A lot has changed since then. I joined right after team doubled by merge with Text Analytics team with a mission to add intelligence to search. A few months later entire Cognitive Services (Azure Machine Learning APIs) platform team joined us. Then we hired additional developers to build scalable platform for both Cognitive Services and Azure Search. After that we also got a team of data scientists who are building the actual machine learning models. Now, as the Applied AI team, we are in the center of AI and Cloud at Microsoft.

Azure Search is a search-as-a-service cloud solution that gives developers APIs and tools for adding a rich search experience in web and mobile applications. You get for free things like autocomplete, suggestions, synonyms, results highlighting, facets, filters, sorting and paging. Functionality is exposed through REST API or .NET SDK. The biggest pain, which is infrastructure and availability are managed by us.

While having all of that, we also need a great developer experience. Everybody needs to be able to understand how to build that Search AI pipeline without spending hours on reading docs. This is another thing we are working on. Email me or tweet message me if you are interested in that kind of stuff.

Where are we going?

Cognitive Search

We want to build the best Search as a Service platform that enables developers to add Bing-like Google-like search experience to their websites. No need for hiring search experts who know what inverted index is. No challenges with shard allocation and how to implement master election properly. No need for distributed systems expertise to scale this for large amount of data. Last, but not least: no need for setting up, owning and managing the infrastructure. Everything is being taken care of by the platform. By the Cloud.

Our team is also working on market-leading Machine Learning APIs. We are going to utilize these ML models and enable you to search through not only text, but also through your images, audio and videos.

There is a lot of challenges in that journey. From processing large amounts of data, through doing it in reasonable time (performance/parallelization), to providing efficient user experience throughout the process.

Where are we now?

We already have fast, reliable and production-ready system for full-text search. You can provision it in no-time, scale by adding more replicas or partitions, and monitor using metrics we provide. You can query it with .NET SDK or using REST API. We even have Open Source UI generation tool that gets you started with the latter: AzSearch.js.

To learn more about current capabilities of Azure Search check this awesome presentation by Bryan Soltis:

There are two ways to populate your search index: by simply inserting documents (records) into it, or by using indexer – a mechanism that enables you to sync your search index with your data source (SQL or NoSQL Database, blob storage, etc.).

We have already started adding AI to our search pipeline, by enabling you to run text analytics and OCR on your data. If you are using indexer, you can create a skillset, which can detect people, entities, organizations, locations, key phrases, and language on the textual data. On top of that you can use OCR that can recognize text from your images, and enable you to search through that text. You can also run mentioned text analytics on recognized text. We call this approach Cognitive Search. Here is a quick video by Brian and Corom from our team, with a sneak peak of what’s possible:

Last year we created a prototype of Cognitive Search, using JFK files that went public. You can check out our JFK files website, github repo and below video from Connect(); conference in 2017, where Corom explaines how he built a pipeline to achieve what is possible now with just checking the checkbox:

We announced Cognitive Search at the //build conference earlier this year. Together with NBA we built a website that allows you to search through player’s photos. You can search for players, their shoes or correlations between them:

Similar approach can be used for variety of different scenarios. From filtering your family photos, through analyzing medical records data, to deciding which crypto-currency to buy. Now, all these PDFs and doc documents you have on your hard drive can be used to make an informed business decision.

There are a lot of companies using Azure Search in production. It’s super exciting for me that Real Madrid is using Azure Search. It’s my favorite football club since I was a kid.

How’s the team?

My favorite thing about our team are the people. Every single person is bringing something else to the table, and there is something you can learn from each one of them. From distributed systems expertise, through API design, to building efficient monitoring infrastructure that enables to maintain production cloud service. One of our team members is Henrik Frystyk Nielsen who is best known for his pioneering work on the World Wide Web and subsequent work on computer network protocols. Currently he works on encapsulating Machine Learning models into containers. Our manager, Pablo Castro started not only Azure Search, but also OData protocol and LINQ to Entities. Our Project Manager Lance Olson was one of the founders of the .NET! You can check out what people say about our team on blind! Search for “Azure Search” 😉 There is also a blog post written by Pablo a few years ago: Startup at Microsoft. A lot has changed since then. We went through a few rounds of “funding”, and our team grew. However, we still believe in core values expressed there. For example: every engineer from the team still talks to customers on daily basis either through social media or directly over email or Skype.

BTW: We are hiring!


I am joining Cloud AI team to work on Azure Search

Azure Search

It has been over 3 years since I joined the Azure Portal team. During that time I learned a lot about every aspect of web and mobile development. I delivered over 20 technical talks at different conferences around the World and local meetups. It was amazing to take the new Portal from preview to v1. In the meantime, during the //oneweek hackathon, together with a few other folks, we built a prototype of the Azure Mobile App. After getting feedback from Scott Guthrie who said that “it would be super useful” I started working on the app overnight.

I didn’t know much about mobile development at the time, but I wanted to learn. I didn’t know much about complexities of Active Directory authentication and Azure Resource Manager APIs. I just knew that it would be super cool to have an app that would allow me to check the status of my Azure resources while waiting for my lunch. Receiving a push notification, and being able to scale VM from my phone would be also tremendously valuable.

When I started working on the app full time, my dream came true. I could truly connect my passion with work. I enjoyed the long hours, and late nights we all put to make it happen. The day when Scott Hanselman presented the Azure App at the //build conference was on of the best days of my life.

Now, when the Azure App is released, and backed by great team, I can move to the next challenge.

Machine learning is becoming part of every aspect of our lives. Over last few years, ML crossed a threshold necessary to be extremely useful. I always wanted to be part of it. I took a great Coursera class by Andrew Ng, I started overnight project StockEstimator and I got involved in SeeingAI to learn how Real-World Machine Learning looks like.

Now, I’m taking it to the next level. I am joining Azure Search Team to lead their User Experience. I will be responsible for bringing the product to customers. While using my existing web development knowledge, I will have an amazing opportunity to learn more about Big Data, AI and ML.

Azure Search is managed cloud search service that offers scalable full-text search over multiple languages, geo-spatial search, filtering and faceted navigation, type-ahead queries, hit highlighting, and custom analyzers. You can find more details in this talk by Pablo Castro (Azure Search manager and creator of Open Data Protocol).

The cool thing about working for Microsoft is that you may end up working with person who created HTTP protocol. Henrik Frystyk Nielsen, former Tim Berners-Lee’s student, who shared office with HĂ„kon Wium Lie (creator of CSS), joined my new team this month. What’s even cooler, he is sitting next to me 🙂

In my new office with Henrik:

Henrik Frystyk Nielsen and Jacob Jedryszek

If you want to learn more about all the cool stuff we are doing at Cloud AI group there is an awesome .NET Rocks Podcast with Joseph Sirosh. Check it out!

There is also awesome talk by Joseph from the last Connect(); conference, which includes JFK files demo presented by Corom Thompson from my team (creator of How-Old.NET). In that demo Corom showcases how you can use Azure Search and Cognitive Services to explore JFK files. Super cool! You can see demo in below video, and code on github.

It has never been a better time to work on the intersection of Cloud and Artificial Intelligence!