How we scaled our startup by being remote first

Michael Risse Contributor

Michael Risse is VP & chief marketing officer at Seeq, a company building advanced applications for engineers to accelerate insights into process manufacturing data. He was formerly a consultant with big data platform and application companies, and prior to that worked with Microsoft for 20 years.

Startups are often associated with the benefits and toys provided in their offices. Foosball tables! Free food! Dog friendly! But what if the future of startups was less about physical office space and more about remote-first work environments? What if, in fact, the most compelling aspect of a startup work environment is that the employees don’t have to go to one?

A remote-first company model has been Seeq’s strategy since our founding in 2013. We have raised $35 million and grown to more than 100 employees around the globe. Remote-first is clearly working for us and may be the best model for other software companies as well.

So, who is Seeq and what’s been the key to making the remote-first model work for us?  And why did we do it in the first place?

Seeq is a remote-first startup – i.e. it was founded with the intention of not having a physical headquarters or offices, and still operates that way – that is developing an advanced analytics application that enables process engineers and subject matter experts in oil & gas, pharmaceuticals, utilities, and other process manufacturing industries to investigate and publish insights from the massive amounts of sensor data they generate and store.

To succeed, we needed to build a team quickly with two skill sets: 1) software development expertise, including machine learning, AI, data visualization, open source, agile development processes, cloud, etc. and 2) deep domain expertise in the industries we target.

Which means there is no one location where we can hire all the employees we need: Silicon Valley for software, Houston for oil & gas, New Jersey for fine chemicals, Seattle for cloud expertise, water utilities across the country, and so forth. But being remote-first has made recruiting and hiring these high-demand roles easier much easier than if we were collocated.

Image via Seeq Corporation

Job postings on remote-specific web sites like FlexJobs, Remote.co and Remote OK typically draw hundreds of applicants in a matter of days. This enables Seeq to hire great employees who might not call Seattle, Houston or Silicon Valley home – and is particularly attractive to employees with location-dependent spouses or employees who simply want to work where they want to live.

But a remote-first strategy and hiring quality employees for the skills you need is not enough: succeeding as a remote-first company requires a plan and execution around the “3 C’s of remote-first”.

The three requirements to remote-first success are the three C’s: communication, commitment and culture.

Lyft is adding gender-neutral pronouns to its app

Ahead of LGBTQ Pride Month, Lyft is adding gender-neutral pronouns to its rider app. Now, riders can select from the following:

• They/them/theirs
• She/her/hers
• He/him/his
• My pronoun isn’t listed
• Prefer not to say

Drivers will be able to see your preferred pronoun, but they will not be able to share theirs. Moving forward, you can expect Lyft to start addressing you and referring to you by your preferred pronouns.

This helps to create space for those to share their pronouns and normalize the practice. Lyft is also partnering with the National Center for Transgender Equality to support with educational and financial resources drivers looking to change their names.

Google Maps adds ability to see speed limits and speed traps in 40+ countries

Google Maps is gaining some features previously exclusive to Google’s navigation app, Waze. The company confirmed it’s rolling out the ability for Google Maps users to see speed limits, speed cameras and mobile speed cameras in more than 40 countries worldwide — an expansion of its earlier launch of these features, which were previously limited to select markets.

The change was noted earlier by ZDNet and, of course, Reddit.

Google confirmed with TechCrunch the full list of supported countries now seeing the speed cameras, which currently includes: Australia, Brazil, U.S., Canada, U.K., India, Mexico, Russia, Japan, Andorra, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Estonia, Finland, Greece, Hungary, Iceland, Israel, Italy, Jordan, Kuwait, Latvia, Lithuania, Malta, Morocco, Namibia, Netherlands, Norway, Oman, Poland, Portugal, Qatar, Romania, Saudi Arabia, Serbia, Slovakia, South Africa, Spain, Sweden, Tunisia, and Zimbabwe.

Google had not been quick to integrate Waze’s best features into its own Google Maps app, following its 2013 acquisition of the popular navigation app. Instead, it seems to prefer using Google Maps as a broader platform for helping people find places including — most importantly — nearby businesses and Google advertisers.

Above: Image credit – Android Police

But last year, some people began to spot incident reports as well as crash and speed trap reports appearing in Google Maps. Those features were not broadly rolled out to all users at that time, however.

Now, that’s starting to change.

Google began to roll out the ability for users in more countries to see speed cameras around two weeks ago, we understand. The rollout is taking place on both Android and iOS. But Android users will additionally be able to report mobile speed cameras and stationary cameras, while both iOS and Android users will be able to see those updates during their drive.

The speed limit appears in the bottom corner of the app, while speed traps show up as icons on the roads themselves.

The features will likely appeal to users who want similar functionality as to what’s available today in Waze, but don’t either care for the Waze user interface (which can be overwhelming if you’re not used to it), or the way Waze chooses its routes.

There has been some confusion over where and when these alerts would be available, as Google failed to officially announce the features’ expansion. Adding to the confusion was the fact that people were seeing the changes appear at different stages of the rollout in different countries around the world.

Despite the usefulness of speed-related alerts, Waze remains the more useful navigation platform due to its ability to crowdsource reports of all kinds — including police ahead, crashes, cars pulled over on the side of the road, gas prices, road closures, obstacles in your path like debris, red light cameras and more.

We understand Google Maps uses a combination of authoritative feeds along with feedback from Google Maps users in order to locate the speed cameras.

This robot learns its two-handed moves from human dexterity

If robots are really to help us out around the house or care for our injured and elderly, they’re going to want two hands… at least. But using two hands is harder than we make it look — so this robotic control system learns from humans before attempting to do the same.

The idea behind the research, from the University of Wisconsin-Madison, isn’t to build a two-handed robot from scratch, but simply to create a system that understands and executes the same type of manipulations that we humans do without thinking about them.

For instance, when you need to open a jar, you grip it with one hand and move it into position, then tighten that grip as the other hand takes hold of the lid and twists or pops it off. There’s so much going on in this elementary two-handed action that it would be hopeless to ask a robot to do it autonomously right now. But that robot could still have a general idea of why this type of manipulation is done on this occasion, and do what it can to pursue it.

The researchers first had humans wearing motion capture equipment perform a variety of simulated everyday tasks, like stacking cups, opening containers and pouring out the contents, and picking up items with other things balanced on top. All this data — where the hands go, how they interact and so on — was chewed up and ruminated on by a machine learning system, which found that people tended to do one of four things with their hands:

• Self-handover: This is where you pick up an object and put it in the other hand so it’s easier to put it where it’s going, or to free up the first hand to do something else.
• One hand fixed: An object is held steady by one hand providing a strong, rigid grip, while the other performs an operation on it like removing a lid or stirring the contents.
• Fixed offset: Both hands work together to pick something up and rotate or move it.
• One hand seeking: Not actually a two-handed action, but the principle of deliberately keeping one hand out of action while the other finds the object required or performs its own task.

The robot put this knowledge to work not in doing the actions itself — again, these are extremely complex motions that current AIs are incapable of executing — but in its interpretations of movements made by a human controller.

You would think that when a person is remotely controlling a robot, it would just mirror the person’s movements exactly. And in the tests, the robot does so to provide a baseline of how without knowledge about these “bimanual actions,” but many of them are simply impossible.

Think of the jar-opening example. We know that when we’re opening the jar, we have to hold one side steady with a stronger grip and may even have to push back with the jar hand against the movement of the opening hand. If you tried to do this remotely with robotic arms, that information is not present any more, and the one hand will likely knock the jar out of the grip of the other, or fail to grip it properly because the other isn’t helping out.

The system created by the researchers recognizes when one of the four actions above is happening, and takes measures to make sure that they’re a success. That means, for instance, being aware of the pressures exerted on each arm by the other when they pick up a bucket together. Or providing extra rigidity to the arm holding an object while the other interacts with the lid. Even when only one hand is being used (“seeking”), the system knows that it can deprioritize the movements of the unused hand and dedicate more resources (be it body movements or computational power) to the working hand.

In videos of demonstrations, it seems clear that this knowledge greatly improves the success rate of the attempts by remote operators to perform a set of tasks meant to simulate preparing a breakfast: cracking (fake) eggs, stirring and shifting things, picking up a tray with glasses on it and keeping it level.

Of course this is all still being done by a human, more or less — but the human’s actions are being augmented and re-interpreted into something more than simple mechanical reproduction.

Doing these tasks autonomously is a long ways off, but research like this forms the foundation for that work. Before a robot can attempt to move like a human, it has to understand not just how humans move, but why they do certain things in certain circumstances and, furthermore, what important processes may be hidden from obvious observation — things like planning the hand’s route, choosing a grip location and so on.

The Madison team was led by Daniel Rakita; their paper describing the system is published in the journal Science Robotics.

CrowdStrike sets terms for $378M Nasdaq IPO

CrowdStrike, in preparation for its Nasdaq initial public offering, has inked plans to sell 18 million shares at between $19 and $23 apiece. At a midpoint price, CrowdStrike will raise $378 million at a valuation north of $4 billion.

The company, which develops cloud-native endpoint protection software to prevent cyber breaches, has raised $480 million in venture capital funding to date from Warburg Pincus, which owns a 30.2% pre-IPO stake, Accel (20.2%) and CapitalG (11.1%), according to its IPO prospectus. The business was valued at $3.3 billion with a $200 million January 2018 Series E funding.

Sunnyvale, Calif.-based CrowdStrike outlined its IPO plans two weeks ago. The company plans to trade under the ticker symbol “CRWD.”

The cybersecurity unicorn follows several other highly valued venture-backed startups to the public markets, including Uber, Lyft, Pinterest, PagerDuty and Zoom. CrowdStrike’s offering will represent only the second cybersecurity IPO in 2019, however. It follows Israel’s Tufin Software Technologies, which went public earlier this year. Last year, for its part, saw the IPOs of Zscaler, Carbon Black and Tenable.

Founded in 2011 by former McAfee executives George Kurtz and Dmitri Alperovitch, CrowdStrike is up against steep competition in the cyber protection space. It’s battling the likes of McAfee, Cylance, Palo Alto Networks, Symantec, Carbon Black and more.

The business’ revenues, fortunately, are growing at an impressive rate, increasing from $53 million in 2017 and $119 million in 2018 to $250 million in the year ending January 31, 2019. In the quarter ending April 30, 2019, its revenues shot up from $47.3 million in 2018 Q1 to between $93.6 million to $95.7 million.

CrowdStrike is also backed by IVP, March Capital Partners, General Atlantic and others.

Online lender SoFi has quietly raised $500 million in funding, led by Qatar

Usually when it comes to big sums of funding, companies like to boast. Online lending startup Social Finance, better known as SoFi, took another tack this morning, quietly announcing in a press release that it has closed half a billion dollars in a single funding round led by Qatar Investment Authority, a Doha, Qatar-based private equity and sovereign wealth fund.

Even in a world now awash with rounds in the multiple hundreds of millions of dollars, the financing is notable. First, it’s the third giant round in recent years for the nearly eight-year-old, San Francisco-based company. Its biggest round to date came in September 2015, when SoftBank led a $1 billion round in the company. SoftBank’s then COO, Nikesh Arora, who was part of the funding announcement, abruptly left the Japanese conglomerate the following year, but SoftBank CFO Alok Sama maintains a board seat.

In February 2017, SoFi raised $500 million more in funding led by the private equity firm Silver Lake, but there would come another twist five months later when SoFi’s founder and its CEO at the time, Mike Cagney, was forced to resign following a sexual harassment lawsuit.

Cagney has since raised a bundle for a new lending company called Figure.

Indeed, the new, Qatar-led round is the first big vote of confidence for SoFi’s newest CEO, Anthony Noto, who joined the company in January of last year after spending three-and-a-half-years at Twitter, first as its CFO and later as its COO — roles he took on after spending several years with Goldman Sachs as a managing director. (Noto also participated in the company’s newest financing.)

Still, the round — which pushes SoFi’s total funding to $2.3 billion altogether — appears to be a flat one.  According to SoFi’s release about funding, its pre-money valuation is $4.3 billion, the same valuation it was assigned at the time of that Silver Lake-led round two years ago.

Seemingly, that owes to competitive pressure in the space, including a flood of non-bank lending companies that includes Lending Club and Prosper for consumer loans, OnDeck for small and mid-size business loans, StreetShares for veteran-owned businesses and CommonBond and SoFi for student loans.

That’s saying nothing of newer online lenders like Affirm, the Silicon Valley startup that’s led by serial entrepreneur Max Levchin and is aggressively chasing millennial shoppers who need loans, or can be easily persuaded to take one, in any case.

Little wonder that SoFi, which also largely markets its services to younger customers, has been rolling out new products, including two no-fee exchange-traded funds that it introduced last month.

The move gives SoFi a way to access the $3.9 trillion U.S. ETF market. The products’ debut also reminded many that when dealing with non-traditional institutions racing to grow their businesses, there can be kinks.

In this particular case, customers of SoFi’s new ETFs weren’t told beforehand that SoFi intended to liquidate their existing ETF investments and funnel the proceeds into its own new funds, as reported by the WSJ. Indeed, one customer with whom the outlet spoke said that the tax bill he’ll owe because of the move will outweigh 35 years of fee savings.

Above: SoFi CEO Anthony Noto.

Allbirds, Everlane investor Maveron turned away more than $70M for its latest fund

Maveron, a venture capital fund co-founded by Starbucks mastermind Howard Schultz, has closed on another $180 million to invest in early-stage consumer startups.

The capital represents the firm’s seventh fundraise and largest to date. To keep the fund from reaching mammoth proportions, the firm’s general partners said they turned away more than $70 million amid high demand for the effort.

“It takes discipline to do something different from the rest of the herd, but we know that we’re not in the business of AUM, we’re in the business of generating cash-on-cash returns,” they wrote. “We know in this market it is hard to adhere to the idea that size is the enemy of performance but we believe in that truth here.”

In a phenomenon dubbed “The SoftBank Effect,” early- and late-stage venture firms have upped the ante when it comes to the size of their funds. Andreessen Horowitz, for example, recently brought in a fresh $2.75 billion to invest in startups, its largest pool to date.

Maveron was launched in 1998 by Schultz and Dan Levitan, a former managing director of investment firm Wertheim Schroder & Co. Schultz, currently considering a presidential run, is no longer actively involved in the firm. Maveron is known for recent bets in startups such as Allbirds, Everlane, General Assembly, Modern Fertility and Eargo.

Fund VII will be led by a team of six, including Levitan, Jason Stoffer, Anarghya Vardhana, David Wu, Cat Lee and Natalie Dillon. Split equally by gender, Maveron says its diversity gives them an edge.

“We’re able to see things others can’t because of our balanced team,” they said. “Last year, 70% of the founders we backed were women and all of those founders were also CEO or co-CEO. Beyond gender diversity, we also have someone on the investment team in every decade of their lives from their 20s to their 60s. That perspective marries the experience and scars of living through multiple market cycles with youthful optimism and connectivity to today’s tastemakers and trends.”

Maveron invests exclusively in consumer startups, with an eye for founders who are “unapologetically non-normal,” who value relationships over transactions, profit and purpose, and who “win the right way.”

Startups Weekly: There’s an alternative to raising VC and it’s called revenue-based financing

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