The History of Remote Work

A look back before we zoom too far into the future...🚀

#FutureOfWork #WorkforceFuturist

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https://t.co/4SxOJDx8HG

~8yrs ago (Dec’12) I got a job @Google. Those were still early days of cloud. I joined GCP @<150M ARR & left @~4B (excld GSuite). Learned from some of the smartest ppl in tech. But we also got a LOT wrong that took yrs to fix. Much of it now public, but here’s my ring-side view👇

By 2008, Google had everything going for it w.r.t. Cloud and we should’ve been the market leaders, but we were either too early to market or too late. What did we do wrong? (1) bad timing (2) worse productization & (3) worst GTM.

We were 1st to “containers” (lxc) & container management (Borg) - since '03/04. But Docker took LXC, added cluster management, & launched 1st. Mesosphere launched DCOS. A lot of chairs were thrown around re: google losing this early battle, though K8 won the war, eventually 👏

We were 1st to “serverless” (AppEngine). GAE was our beachhead -- it was the biggest revenue source early on but the world wasn’t ready for serverless primitives. We also didn’t build auxiliary products fast enough. Clients that outgrew GAE wanted “building block” IaaS offerings.

1st to hadoop (map-reduce ‘04) but our hosted Hadoop launched in ‘15. AWS EMR was ~200M ARR by then. 1st to cloud storage (GFS ’03), but didn’t offer a filestore till ‘18! Customers were asking for it since 2014. Didn’t launch archival storage or direct interconnect till v. late.

Two years ago on a weekend, I built a tool to make it easier to evaluate Twitter accounts. Since then 36590 people used it to analyze 55390 different Twitter accounts.

Over the last months @mmkaradeniz and I made a new version. We launched it last night:

@accountanalysis doesn't use machine learning or AI „magic“. Instead of telling users if an account is authentic or not, it helps them to evaluate the accounts themselves.

It visualizes the different features (date, time, type, app, etc.) of Tweets to make them interpretable. /1

@accountanalysis The core concept is still the same, but it looks much better and is easier to operate. Not only for the users, but us developers as well. Enabling us to continuously roll out new features in the future.

Side-by-side screenshots of the old and new version. /2

@accountanalysis Some people had questions what different charts displayed and how they could be interpreted. There are now explanations for all charts, that can be toggled on and off at any time. /3

@accountanalysis The selected/retrieved Tweet count moved to the top to make it clear that not all Tweets of an account are analyzed. 3200 is the API limit by Twitter. It's possible to get more through the Premium API, but I don't think people would pay $100+ for the analysis of one account. /4

Originally, tweet length was 160 minus username length. One day, I turned to Jack and pointed out that I got one more character than him. He said, "That's not fair. We should standardize." I agreed. He said, "How about 140?" I said, "Sure." And he updated the code.

Last year, we upgraded tweet length to 280 and guess what? Use of 'please' is up 54% and 'thank you' is up 22%. I love that! Also, people are asking more questions and having more conversations. All this, and the majority of tweets are still under 140. It worked.

A long time ago I coded up a feature for SocialCoder which converts a link - any link - to a short URL. I use it all the time for sharing links to volunteer profiles and to volunteer opportunity listings.

The feature doesn't care what the link contains, it just hashes the URL, including any query params, and returns a shortened code.

More recently, around Christmas time, I added another feature where I can click a button to send a template notification to a charity that their new listing has been reviewed and published. I call it a next-steps email.

For the past few weeks, its all been working well. Its nice to keep automating things that previously were done by hand.

Fast forward to today.

A new opportunity listing is posted by a charity.

I review and publish it, tweet about it, then click a button to send the charity an emailed notification of next steps.

(1) Since some people laugh at Cardano project and it's peer review aspect, let me share a story from work for all of you
(2) There is company called Databricks and they open sourced recently a technology called: https://t.co/gpZyKKiMVD . This technology is super important

(3) In BigData delta allows one to perform DELETE and MERGE operations contrary to Hadoop + Hive where this is not possible, seeking through many partitions finding customer data to remove and then rewriting it is not only expensive as an operation but also very dangerous

(4) This promising technology is something that many companies, which have big data turn into as they need to be GDPR compliant.
(5) I was always reading and accepting all details from their website as given and the "truth"

(6) There is however an amazing Principal Developer at our company that found some of the claims from their website as dubious, e.g. ACID claims on such a distributed file system
(7) It turns out this is not the first time this company advertises something that is simply not true

(8) on another occasion this company made untrue claims about Cassandra database and this then became source of disputes e.g by dr. @martinkl - my fave expert in distributed systems
(9) All professional developers also know of course famous Jepsen tests ->