Bloomberg has a short update on Phantom Auto, a teleoperations startup that has recently partnered with Mitsubishi Logisnext to remotely operate warehouse forklifts.

Phantom Auto was founded by some of the earliest students in the Udacity Self-Driving Car Engineer Nanodegree Program that I led, so I’m excited to see them doing well.

Co-founder Elliot Katz tells Bloomberg that remote operation has “the potential to knock 30% or more off forklift operation costs.” The driver of cost-savings seems to the ability to move jobs to lower-cost areas, since the remote operator doesn’t have to be physically co-located with the equipment.

I imagine that what I’ve heard in agriculture also applies somewhat to logistics, which is that the big advantage of automation (to the extent remote operation counts as automation) is actually increased performance, rather than labor costs. In a field, an automated machine can plant seeds more accurately and squeeze more yield out of the same amount of land, compared to a farm hand. In a warehouse, you could imagine that removing humans from the floor could allow for reconfigurations that would save space, accelerate movement, or otherwise improve efficiency.

I’m also curious how far we can push the migration of in-person jobs into remote operation, and possibly eventual autonomy. Covid-19 has pushed diagnostic telemedicine pretty far in the US, but procedures still require the provider to be physically present. Perhaps in the future, my surgeon or dentist will be operating on me remotely, from another timezone.

Both The Verge and CNBC report that Volkswagen & Argo will begin testing self-driving cars in Europe this summer. That news comes courtesy of a press conference with Brian Salesky, Argo’s CEO, and Christian Senger, a Volkswagen executive.

Announcements about self-driving testing (as opposed to commercial services) have become a little ho-hum in the US, but this seems like a big deal for Europe. So far, Europe has had very little autonomous vehicle testing on public roads, and even less news about such efforts.

Volkwagen is a major investor in Argo, which is headquartered in Pittsburgh, with offices in California and Munich, Germany. Although much of the self-driving software that Volkswagen will test this summer was presumably written in the US, just getting it on the road in Germany will be a meaningful step forward for the European automotive industry.

Cruise is hiring a Staff Software Engineer for Maps. This job looks like a great fit for a cloud architect, even one who has no experience in robotics.

Here are the requirements:

• 8+ years as a developer
• Build, ship, debug, and operate full stack web services
• Distributed systems
• Microservices
• API design
• SOA
• Node.js (or equivalent)
• React or Redux
• PostgreSQL

Now does that list look like a cloud architect, or what?

If you’re a cloud architect, you should be building self-driving cars! They’re amazing!

Email me 🙏

My latest Forbes article analyzes SAE’s recent redefinition of its six-level autonomy taxonomy.

“…it’s basically consistent with how the SAE previously defined Level 3: the human passenger isn’t ‘driving’, but has to be ready to take control of the vehicle when the system asks.

That leaves a fair bit of ambiguity, especially about how quickly the human must ‘receive’ requests to intervene. That, in turn raises the quest of how broad the range of other tasks is in which the human can engage, while still allowing enough time to take control if the system requires.”

I think that ultimately vehicle manufacturers will define Level 3 differently in practice. Read the whole thing.

He amused me.

“Yeah, it’s a hustle.”

Timothy B. Lee, one of the top journalists covering self-driving technology, just published an article in Ars Technica that asks the question, “Why hasn’t Waymo expanded its driverless service?”

Lee covers several different possibilities, from the cost of remote operations staff, to the difficulty of serving areas like Phoenix Sky Harbor Airport and Arizona State University. Ultimately, he zeros in on a theory he calls, “Kyle Vogt’s Insight.”

“In 2017, Kyle Vogt—Cruise’s founder, then-CEO, and now-CTO—wrote a blog post explaining why Cruise was testing its vehicles in San Francisco.

‘Anyone who has visited San Francisco knows driving here is kind of ridiculous,’ Vogt wrote. ‘Our vehicles encounter challenging (and often absurd) situations up to 46 times more often than other places self-driving cars are tested.'”

Credit to Lee, who owns up to some early skepticism of that theory – skepticism Lee now admits may have been misplaced.

“At the time, I didn’t find Vogt’s argument very convincing. I thought that if Waymo could launch a fully driverless service in an “easy” area like suburban Phoenix, the company would gain a ton of useful experience and data that would give it a leg up in tackling more difficult areas…But now I suspect I was wrong. Maybe after millions of miles in the suburbs, Waymo has reached a performance plateau—it has mastered situations that are common in the suburbs, and it no longer sees enough new challenges to continue improving.”

The whole article is worth a read. It’s a fascinating thought exercise by one of the most informed thinkers in the industry.

To be sure, nobody outside Waymo knows why they haven’t expanded Waymo One since they launched last year. Perhaps they’re going to announce a huge expansion any day now.

But if Lee’s hypothesis is correct, then Kyle Vogt’s contrarian insight will go down as one of the canonical contrarian technology decisions – non-consensus and right – in Silicon Valley history.

One of my favorite software engineering mantras is, “Write the code you wish you had.” That sentence is a little bit cryptic at first glance, but once I grasped the meaning, it became a great way for me to get unstuck, especially when writing greenfield code.

The idea is that, when writing code, I frequently encounter situations in which I need a function that doesn’t yet exist. These situations can be paralyzing, because I want to continue writing the code I’m focused on right now, but I can’t keep going unless I write this new function. Writing the new function is a context switch that is mentally expensive and I want to avoid it. So I’m stuck.

The trick, and maybe this is obvious to you, even though it wasn’t to me, is that I can keep writing the code I’m focused on now. I can write down proceed with foo = some_function(arg1, arg2); even if I haven’t yet defined, or even declared, some_function(). I just write it down where I need it and keep going!

Of course, the code won’t compile or run, because I’m calling a function that doesn’t exist. But that’s okay, as long as I have some mechanism to ensure that I define the function later.

This works best with test-driven development, an approach whereby I define my automated tests before I write the functional code. That way, I always have a test that fails and reminds me to define the function I wish I had.

I picked up this mantra, “Write the code you wish you had,” through the Ruby on Rails ecosystem, which is fanatical about testing. I don’t remember who, precisely, first taught me the phrase.

But when I search for those words, one of the first results is this short episode of Developer Tea, by Jonathan Cutrell. He describes a similar mental shortcut, which is to think, “Wouldn’t it be nice if…?” He also suspects the phrase originates with Avdi Grimm of RubyTapas.

Coursera went public on the NYSE on March 31, and since then I’ve been meaning to dig into their S-1, which is the technical term for the financial report they have to share with investors before a public offering. Coursera is arguably the closest competitor to Udacity, where I worked for 4.5 years, so I’m naturally curious.

Here is some headline information.

Ticker	COUR
CEO	Jeffrey Maggioncalda
Founders	Daphne Koller & Andrew Ng
Largest Shareholder	New Enterprise Associates (18%)
Market Capitalization	$5.5 billion
ROI (since IPO)	-7%
Revenue (annual)	$294 million
Net Income (annual)	-$67 million
Net Profit Margin	-23%
Employees	779
Cash + Securities	$285 million
Operating Cash Flow (annual)	-$15 million

Cash

The first thing that jumps out at me is how strong Coursera’s cash position was, at the time of the IPO. This was not a company that needed to go public, in spite of annual loses of $67 million. They had $285 million in the bank, so they were in good shape already.

Perhaps precisely because of that, Coursera’s largest shareholders were NEA and G Squared. The former is a high-profile venture capital firm, and the latter is a somewhat lower-profile growth-stage investor. Andrew Ng held 8% of the shares at IPO, Maggioncalda held 4%, and Daphne Koller was somewhere below the 5% reporting threshold.

Growth

Coursera’s growth from 2019 to 2020 is impressive. 60% year-over-year! Presumably this involved heavy discounting, but their profit margin stayed pretty stable, at about -25%.

Expenses

Their income statement shows gross margin of 53%, which seems low for a technology company. Probably this is due to the all of the payments they make to third-party instructors who build courses sold through the Coursera platform.

Sales and marketing is also a huge expense, amounting to 36% of revenue. I’m curious how much of that is sales to enterprise customers, versus marketing to consumers. Adding 35% sales and marketing to 47% cost of goods sold leaves only about 18% of revenue left to cover all of Coursera’s other expenses.

The risk here is that Coursera’s current losses may not be investments in technology that can be amortized at zero marginal cost in the future. Rather, the losses may be due to ongoing creator and sales costs that will stay with Coursera forever, which would make the business much less attractive, financially.

Products

• Guided projects for $9.99
• Courses for $0 to $99
• Specializations and certificates for $39-$99/month
• University courses for $2000 to $6000
• Bachelor’s or master’s degrees for $9000 to $45,000

The question here almost asks itself. Do they have such a wide array of products because they all work, or because they haven’t yet figured out which ones work?

Channels

The breakdown between enterprise customers and consumer learners is also important.

	Consumer	Enterprise	Degrees
Share	66%	24%	10%
Annual Growth	60%	49%	100%

Enterprise customers require expensive high-touch sales, but are sticky and price-insensitive. Consumer learners have the same drawback as dating app customers – if you serve them well, they get what they need quickly, leave, and don’t return for a long time.

Given that dynamic, the growth in consumer channel is impressive. I guess this might be due to discounting. Consumers tend to be sensitive to price, so it’s possible to generate a lot more demand with lower prices.

The degree channel looks small, but if it can double in size again this year, it will be a real factor in their business.

Conclusion

Coursera has done a great job managing their business, especially when it comes to growth. The big question is whether they can get their costs under control.

I suspect they have a lot of leverage here, because the EdTech market is still pretty immature. The number of competing distributors that an instructor could turn to is small.

Bloomberg wrote a great headline: “The Race to Build Self-Driving Trucks Has Four Horses and Three Jockeys.” The article itself is mainly about robotaxis vs. autonomous trucks, but it’s worth reading for one infographic.

I used data from Transport Topics to create a similar infographic here, but you should click through to the original Bloomberg infographic. That has more detail, such as the specific brands that each company owns, and the brand market shares. For example, Daimler manufactures trucks in the US under the Freightliner brand name, along with Western Star.

I’m also not sure the Bloomberg analysis fully captures all of the partnerships in this space. For example, the original graphic left out the Daimler/Torc relationship (Daimler acquired Torc). I’m also not sure how well this covers geographies outside the US: Plus.AI announced a partnership with IVECO for autonomous trucks in Europe and Asia.

And perhaps the route to building a self-driving truck runs more through partnerships with shippers like Amazon and FedEx, rather than the manufacturers.

But, as somebody who isn’t that well-versed in the dynamics of the Class 8 trucking market, I found this infographic to be a useful way to conceptualize the ecosystem.

“Yandex Self-Driving Group has driven seven million autonomous miles (11.5 million kilometers) since the team was founded in 2017, more than any other company has announced, save for Alphabet’s Waymo.”

I profiled the team in Forbes. Read the whole thing.