Nine lessons on how Niantic reached a $4B valuation

We’ve captured much of Niantic’s ongoing story in the first three parts of our EC-1, from its beginnings as an “entrepreneurial lab” within Google, to its spin-out as an independent company and the launch of Pokémon GO, to its ongoing focus on becoming a platform for others to build augmented reality products upon.

It’s not an origin story that serves as an easily replicable blueprint — but if we zoom out a bit, what’s to be learned?

A few key themes stuck with me as I researched Niantic’s story so far. Some of them – like the challenges involved with moving millions of users around the real world – are unique to this new augmented reality that Niantic is helping to create. Others – like that scaling is damned hard – are well-understood startup norms, but interesting to see from the perspective of an experienced team dealing with a product launch that went from zero to 100 real quick.

The reading time for this article is 16 minutes (5,150 words).

Build on top of what works best

Everything Niantic has built so far is an evolution of what the team had built before it. Each major step on Niantic’s path has a clear footprint that precedes it; a chunk of DNA that proved advantageous, and is carried along into the next thing.

Looking back, it’s a cycle we can see play out on repeat: build a thing, identify what works about it, trim the extra bits, then build a new thing from that foundation.

Source: Tech Crunch

Madrona Venture Group launches $100M acceleration fund

Seattle’s Madrona Venture Group has long been one of the most prominent early-stage funds in the backyard of Amazon and Microsoft. Now, however, the firm is starting to look beyond the Pacific Northwest with the launch of its $100 million Acceleration Fund, which will expand its geographic reach to the entire U.S. and give it a vehicle to invest in later rounds.

The new fund will see Madrona make more investments at the Series B and C stage. While Madrona has made a wide variety of investments over the years, including some into consumer services, its focus has long been on enterprise cloud companies, ranging from Apptio to Smartsheets and Heptio (which VMware recently acquired). We’ll see a similar focus with this new fund, as Madrona managing director Matt McIlwain told me, with an emphasis on cloud and applied machine learning companies. Unlike Madrona’s current focus on the Pacific Northwest — and Seattle in particular — this fund will also invest in companies across the country.

“Our long-time strategy has been early stage, broad-based technology, Pacific Northwest,” McIlwain told me. “We call it an acceleration fund because we want to differentiate it from what some people call opportunity funds, which is more of a ‘put more money into my existing company.’ This is not that. This is new money into great companies that have reached that initial product-market fit and that want to accelerate their growth.”

Madrona also expects that these companies have reached product differentiation and founders and key executives that can sell those products.

McIlwain noted that Madrona has selectively made some of these investments in companies like Tigera, Snowflake and Accolade over the years already. This new fund gives the firm a dedicated vehicle to invest in companies where it believes it can add more value at this later stage.

“When I joined Accolade almost four years ago – the mission was to accelerate the company’s growth by finding the best talent to build a world-class product and distribution team,” said Accolade CEO Raj Singh “To do that, you need world-class partners. Having worked with Matt McIlwain and Madrona on both the Apptio and Amperity board of directors, reaching out to Madrona was high on my priority list on day one. And they have lived up to my expectations – helping with customer acquisition, critical hires, key partnerships, and invaluable counsel.”

McIlwain told me that Madrona has yet to make its first investment from the new fund. “But we’re eager to find that first one that’ll be special enough,” he said.

Source: Tech Crunch

Tesla sued in wrongful death lawsuit that alleges Autopilot caused crash

The family of Walter Huang, an Apple engineer who died after his Tesla Model X with Autopilot engaged crashed into a highway median, is suing Tesla. The State of California Department of Transportation is also named in the lawsuit.

The wrongful death lawsuit, filed in in California Superior Court, County of Santa Clara, alleges that errors by Tesla’s Autopilot driver assistance system caused the crash that killed Huang on March 23, 2018. Huang, who was 38, died when his 2017 Tesla Model X hit a highway barrier on Highway 101 in Mountain View, California.

The lawsuit alleges that Tesla’s Autopilot driver assistance system misread lane lines, failed to detect the concrete media, failed to brake and instead accelerated into the median.

A Tesla spokesperson declined to comment on the lawsuit.

“Mrs. Huang lost her husband, and two children lost their father because Tesla is beta testing its Autopilot software on live drivers,” B. Mark  Fong, a partner at law firm Minami Tamaki said in a statement.

Other allegations against Tesla include product liability, defective product design, failure to warn, breach of warranty, intentional and negligent misrepresentation and false advertising. California DOT is also named in the lawsuit because the concrete highway median that Huang’s vehicle struck was missing its crash attenuator guard, according to the filing. Caltrans failed to replace the guard after an earlier crash there, the lawsuit alleges.

The lawsuit aims to “ensure the technology behind semi-autonomous cars is safe before it is released on the roads, and its risks are not withheld or misrepresented to the public,” said Doris Cheng, a partner at Walkup, Melodia, Kelly & Schoenberger, who is also representing the family.

In the days following the crash, Tesla released two blog posts and ended up scuffling with the National Transportation Safety Board, which had sent investigators to the crash scene.

Tesla’s March 30 blog post acknowledged Autopilot had been engaged at the time of the crash. Tesla said the driver had received several visual and one audible hands-on warning earlier in the drive and the driver’s hands were not detected on the wheel for six seconds prior to the collision.

Those comments prompted a response from the NTSB, which indicated it was “unhappy with the release of investigative information by Tesla.” The NTSB requires companies who are a party to an agency accident investigation to not release details about the incident to the public without approval.

Tesla CEO Elon Musk would soon chime in via Twitter to express his own disappointment and criticism of the NTSB.

Three weeks after the crash, Tesla issued a statement placing the blame on Huang and denying moral or legal liability for the crash.

“According to the family, Mr. Huang was well aware that Autopilot was not perfect and, specifically, he told them it was not reliable in that exact location, yet he nonetheless engaged Autopilot at that location. The crash happened on a clear day with several hundred feet of visibility ahead, which means that the only way for this accident to have occurred is if Mr. Huang was not paying attention to the road, despite the car providing multiple warnings to do so.”

The relationship between NTSB and Tesla would disintegrate further following the statement. Tesla said it withdrew from its party agreement with the NTSB. Within a day, NTSB claimed that it had removed Tesla as a party to its crash investigation.

A preliminary report from the NTSB didn’t make any conclusions of what caused the crash. But it did find that the vehicle accelerated from 62 mph to 70.8 mph in the final three seconds before impact and moved left as it approached the paved gore area dividing the main travel lane of 101 and Highway 85 exit ramp.

The report also found that in the 18 minutes and 55 seconds prior to impact, the Tesla provided two visual alerts and one auditory alert for the driver to place his hands on the steering wheel. The alerts were made more than 15 minutes before the crash.

Huang’s hands were detected on the steering wheel only 34 seconds during the last minute before impact. No pre-crash braking or evasive steering movement was detected, the report said.

The case is Sz Hua Huang et al v. Tesla Inc., The State of California, no. 19CV346663.


Source: Tech Crunch