Alan Wells

A clear articulation of Elon’s clearly stated direction at Tesla re/ working in the presence of one’s teammates in the office, on the factory floor, etc. It’s simply a matter of optimizing productivity, creativity and results, in my experience. That’s doesn’t mean there aren’t workable exceptions for some companies. It’s a choice. His choice is clear. My point? “choose carefully and wisely”. It’s really hard to push on this ime. It’s way harder to have the market put us out of business because someone else slept on the factory floor to drive results and we chose not to. 🙏🏼🇺🇸🚀 https://lnkd.in/gK8Xaven

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The Stoke Space team in Seattle has built a rocket company faster than many people can build software. Morgan Beller breaks down how this is helping them capture a huge opportunity: https://lnkd.in/gc5jv2-c 

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Uber CEO Dara Khosrowshahi resigns from self-driving truck startup Aurora’s board The deal in 2020 involved Uber handing over its equity in ATG and investing $400 million into Aurora, giving it a 26% stake in the combined company. Khosrowshahi joined Aurora’s board as part of the deal. A major reason for the step is citing a desire to focus on his ongoing responsibilities as CEO of Uber and reduce external board commitments, according to a Friday regulatory filing. This may channel more focus and growth-focused results in Uber's future.

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Watch this funny video of a Waymo getting stuck in a doom loop driving endlessly around a roundabout. AVs still have some kinks to resolve. “You have to wonder where the teleoperators were during this meltdown. If you weren't aware, robotaxi companies like Waymo employ round-the-clock teams of remote technicians that take over vehicles when they get stuck or go haywire. Maybe they weren't alerted of the issue, or maybe it genuinely took them some effort to wrest control back over the robotaxi.” Wonder indeed… why didn’t the teleoperations step in sooner here? Upshift is launching a teleoperated car subscription service in January. We won’t drive you in circles! Subscribe to a car that comes to you, drives you around, runs your errands, and valet parks itself. Learn more and join the waitlist at https://lnkd.in/gemiY4Sh

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What do self-driving cars and AI agents have in common? Brooke, the founder of Coval (YC S24) and a former engineer at Waymo, came on the pod to explain. They seem different, but both face similar challenges. Whether it's a car navigating busy streets in SF or an AI agent managing complex customer interactions, both systems need to process real-time data, learn from their environment, and adapt their behavior accordingly. Self-driving cars are "agents on wheels"—deciding when to stop, go, and adjust based on what they see on the road. AI agents, meanwhile, are navigating decision trees, learning through simulations, and improving their ability to respond accurately to task as well. The testing processes are also alike. Like self-driving cars compare their performance to real-world human drivers, AI agents are evaluated on how they solve tasks compared to human operators. Both systems run thousands of simulations, tweaking and refining their responses to ensure they can handle unpredictable, non-deterministic scenarios. That's what Coval does. They help companies do simulations on their agents to help them run more effectively. Fascinating stuff. Our chat together made me feel like I was in the future. The learnings from testing self-driving cars are now being applied to AI agents, showing how interconnected these cutting-edge technologies are. The podcast will be out shortly - till then, this clip does a good job explaining this concept.

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Waymo grew from 100K rides per week to 150K rides in two months. At 7.8M rides per year this is nothing compared to the 10B rides Uber provides. But here is the catch, Uber's costs are more or less fixed. Google's are going to come down exponentially. The cost for an AI team will go down very fast if expressed per ride. Given no drivers are needed and vehicle costs are coming down as well, it is just a matter of scaling up for Google to steal away clients from first Uber but afterwards also public transport, second car ownership and finally first car ownership. In 2025, Waymo can easily go to 1 or multiple millions of rides per month. 2026, 10-50M and in 2027, 1B per month. Giving that Tesla will want to launch in 2025 and scale in 2026, consumers will be the big winners. https://lnkd.in/e4rcAH6D

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The newest issue of The Pragmatic Engineer found a surprise uptick in eng hiring in the typically slow summer season - I'm curious to see how the macro environment impacts this uptick as we head into the fall, but I remain hopeful. I asked Gemini to give me the tldr of the article to share with my team (sorry, Gergely Orosz) and found it missed one of the most interesting pieces of the article. Gemini's highlights - Unexpected surge: Tech recruitment has seen an unusual spike in June and July, contrary to typical trends. Increased demand: Startups, especially AI-focused ones, are driving the hiring uptick. Global phenomenon: This trend isn't just limited to the US; Europe is also experiencing increased recruitment activity. Reasons for hiring: Companies are backfilling positions, investing in growth due to improved financials, and responding to increased VC funding. Challenges remain: While the job market is improving, finding qualified candidates and offering competitive compensation remains difficult for many companies. What I found most interesting - The nature of the backfills: the article finds that a lot of new headcount are actually backfills of folks that were "over-slashed" during rounds of layoffs. Not entirely surprising with the "trim the fat" and "rebuild lean" mentality, but interesting nonetheless. Either way, the uptick is encouraging (and don't always rely on Gemini's tldrs). #hiring #startups #VCbacked #softwareengineering

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GM's head of software Baris Cetinok did a great job communicating almost everything about General Motors' in-car software strategy except this: what a customer gains in day-to-day usability by sacrificing Apple CarPlay in GM's latest EVs. Automotive software absolutely needs to be better. More integrated inside the vehicle, as well as more end-to-end integrated with external data sources like weather, charging, traffic, even cultural inputs. But GM nor Rivian or any of the OEMs who are trying to break away from CarPlay can ever muster a response to the very obvious customer question, which is "Why did my old car support all my phone's apps, and my new car doesn't?" There are only two outcomes to this strategy: OEMs who abandon CarPlay will eventually relent due to loss of sales or they will relent due to the lack of fleet-wide subscription revenue for their integrated, proprietary systems. Locking customers into a single software platform makes as much sense as locking customers into a single vendor of tires. It's a dead end. The only question is how much money will be wasted trying to implement a financial strategy that not a single customer on the planet has actually asked for. https://lnkd.in/gpbzkZSH

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Notion vs Glean reminds me a lot of Tesla vs Waymo... Just like I think Tesla is going to solve the 'software' problem of autonomous vehicles before Waywmo solves the 'hardware' problem... I think that Notion is going to solve 'enterprise knowledge search' before Glean solves the problem of document and knowledge creation... Why? A couple reasons: 1) Just like Tesla, Notion has a huge advantage when it comes to the amount of underlying data and documents to train on... They already have 100M+ users, and likely 10x that in terms of the number of documents, files, etc. in team's workspaces. 2) It's very hard to change people's behaviour re: where/how they create 'work'. It's why a lot of companies have come and gone in that category... As exciting as Glean's AI writing assistants might seem, most people are just fine (or even prefer) a good old fashioned editor/writer. I could be way off here, but this will be an intersting one to follow. Thoughts? Where am I getting it wrong? #ai #enterprise #knowledge #management #notion #glean

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We’re in the transition phase from value creation through human labour to value creation through machine labour — labour being the key word. The jobs that’ll be replaced first are the most laborious. Three areas stand out: 1. Movement of People & Goods Autonomous vehicles. Wayve, Tesla, Waymo. 2. Movement of Parts Warehousing and robotics. Figure, Tesla. 3. Movement of Information AI agents. OpenAI, Anthropic. My back-of-the-napkin calculation suggests that over 250 billion human hours are spent each year in these areas. From delivering packages to component fabrication or intra-company accounting, we’re headed toward a future where over a billion people will need to rethink how they spend their working time. What’s interesting is that training for these laborious roles is incredibly skill-specific, making them particularly vulnerable to automation. In a way, they’re very non-human tasks, requiring situational awareness within the capabilities of today’s machines. This suggests a stark truth: each year, 250 billion hours of human life are spent enduring non-human behaviours to make a living. The issue? Many adjacent roles face a similar risk, pushing unprepared workers into potentially major career shifts. I think we’re dropping the ball when it comes to preparing today’s workforce for this shift. And we’re certainly failing the workforce of the future through outdated education. The shift to machine labour is happening. It’s glacial — slow, unstoppable, and world-changing. On balance, I think it’s a net positive. Fewer laborious, non-human jobs being done by people. But we need much greater emphasis on preparing people for that change.

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The latest edition of The Driverless Digest has just been published! Highlights from this week: 🤖 Waymo now at $45 Billion valuation but how do they stack up to Uber at a public market cap of $150 billion? 💵🔥Zoox to launch in San Francisco and Las Vegas. 🤖 Waymo working on scheduled rides feature which is great for customers but read why I think it’s only going to hurt their utilization. Check it out here - https://lnkd.in/gNywsSmW

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Chat with Miles Clements about building Linear For me companies are like design problems: you have context, constraints & goals unique to you. Then you look for a solution that has a good fit to your unique problems. The company problem also evolve over times the solution Directly applying what others have done doesn’t work that well, yet there is lot emphasis on playbooks, pattern matching and playing copying what other companies are doing in industry. https://lnkd.in/ghxjJwYU

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With the progress of Waymo and the Tesla event yesterday, something I wrote about in 2021 could become true as soon as 2027. In some industries (like ride sharing), marketplaces are just an intermediary step to aggregate independent suppliers. Ultimately, companies will figure out how to provide the service themselves at scale, and we'll have a few very large "super-suppliers". But in other industries (like e-commerce) where the consumer values creativity, consolidated suppliers won't be able to provide all of the new and interesting things that customers want, and we'll still need independent suppliers. Those industries will stay in marketplace mode much longer.

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I spent over half a decade working with driverless cars. I see massive potential for these vehicles to reshape NYC real estate. Waymo recently raised $5.6 billion in a Series C round led by Alphabet and supported by many other leading companies. Meaning the future of this technology feels closer than ever. These are the biggest Opportunities & Challenges Driverless cars present in the NYC market: 1. Reduced need for parking could free up valuable urban space, converting parking lots into housing, retail, or green areas. 2. Easier commutes may drive up outer borough property values, balancing Manhattan and other more densely populated areas of the City 3. NYC’s notorious traffic, pushback from unions on automation, unpredictable weather, and high foot traffic require advanced tech and regulatory adaptation. The next steps will be crucial as real estate, tech, and policy leaders navigate how driverless cars might reimagine our cities. How do you think driverless tech will impact real estate in NYC? P.S This is me in a driverless car back in 2017

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The REAL high EV (expected value) exit may not be working at #bayarea #vc #startups it is being a #whistleblower at them :) https://lnkd.in/esWrjGds

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E-bike fares are hitting $15.59 for a half-hour ride in NYC, which is putting the affordability of these services into question. The whole point is to create more accessible transport options and when the prices go up, only a smaller segment of society will be able to afford them. Higher operational expenses and limited public funding are driving these increased costs. On the other hand, we have cities like Los Angeles which have overcome these hurdles and are keeping their programmes affordable through public investment. The key to sustaining and growing these programmes will be continued support for infrastructure and funding. #Micromobility #UrbanTransport

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