Best of LinkedIn: Future Mobility & Market Evolution CW 07/ 08

00:00:00: brought to you by Thomas Allgaier and Frennus.

00:00:02: This edition highlights key LinkedIn posts on future mobility in market evolution, week seven and eight.

00:00:07: Frenness supports enterprises with market and competitive intelligence decoding disruptive technologies customer needs regulatory change and competitive moves.

00:00:16: so product teams and strategy leaders don't just react but shape the future of mobility

00:00:22: which is quite the mission statement to live up too.

00:00:26: it.

00:00:27: Honestly, looking at the feed for this deep dive in a week seven and eight of twenty-twenty six shaping.

00:00:33: The future feels A lot less like science fiction right now.

00:00:37: And um...a lot more Like just really heavy logistics.

00:00:40: Yeah it Really does.

00:00:41: that's exactly the vibe.

00:00:42: It Feels like the whole industry kind of woke up with a hangover from This massive cool tech party Right?

00:00:47: And suddenly they're realizing oh wait We have to actually operate these businesses In the real world.

00:00:51: Exactly I mean..the posts we are seeing this cycle.

00:00:54: they aren't about the next shiny sensor or some crazy AI breakthrough.

00:00:57: They're about, well... broken doors.

00:01:00: Rain

00:01:00: delays!

00:01:01: Yeah rain delays and bankruptcy filings.

00:01:05: it's just a very different conversation.

00:01:06: It

00:01:07: is the boring era of mobility And I actually mean that as a compliment.

00:01:10: We are finally talking unit economics in operational bottlenecks instead looking at concept art.

00:01:16: Well let us test this complement theory because uh Some reality check Pretty painful.

00:01:22: We have to start with this story, Josh Warnstein shared.

00:01:25: on the surface it sounds like a joke.

00:01:27: Oh!

00:01:27: The waymo door thing

00:01:29: Yes...the open-door problem.

00:01:30: But when you dig into the PNL impact It's a total disaster.

00:01:34: It really is.

00:01:35: So just give some context.

00:01:38: We have a Waymo Robo Taxi.

00:01:40: This is a vehicle estimated to cost around two hundred thousand dollars, right?

00:01:43: At least!

00:01:44: And it's arguably the most sophisticated artificial intelligence currently deployed in the physical world.

00:01:49: It navigates San Francisco traffic...it avoids pedestrians predicts movement

00:01:54: But if passenger gets out and leaves door slightly ajar

00:01:56: The car is bricked

00:01:58: Completely bricked.

00:01:58: It creates this critical error state ...and the car literally cannot move

00:02:03: Right.

00:02:03: And because the car doesn't have the hardware to just, you know close its own door Waymo was resorting to gig labor.

00:02:11: Orenstein pointed out they are using The Honk app or even Door Dash drivers and paying them up to twenty four dollars Just to drive over To the vehicle and shut the door

00:02:21: which is hilarious.

00:02:22: until You do the math on the unit economics

00:02:24: exactly I Was trying run the numbers On this.

00:02:26: say an average roto taxi ride Is what fifteen to twenty dollars in revenue.

00:02:31: give her take yeah

00:02:32: If you have to pay a gig worker twenty-four bucks to fix the simple user error, You haven't just lost profit on that one trip.

00:02:38: No...you've wiped out margin for next three or four trips easily.

00:02:41: And thats not even factoring in opportunity cost.

00:02:44: The car is sitting idle for twenty minutes waiting for the quote unquote door closer To arrive.

00:02:49: It's perfect example of how industry completely overlooked physical interface While obsessing over digital.

00:02:57: Warrenstein made this really cutting observation.

00:02:59: He said, Honda figured out power sliding doors in nineteen

00:03:03: ninety nine.

00:03:04: Nineteen ninety right?

00:03:04: It's a solved problem.

00:03:06: but the avi industry was just so obsessed with the brain.

00:03:11: you know The LADAR that compute That they entirely forgot the body.

00:03:15: and this isn't just a quirky Waymo design flaw it's a systemic issue.

00:03:20: Federico Ranero weighed-in on this exact thing And he argues This is actually the main bottleneck for the entire sector right now.

00:03:29: It all comes down to uptime.

00:03:31: Yeah, Reneva's point is crucial.

00:03:32: we're moving into a phase where Frankly, mostly good enough.

00:03:36: Right?

00:03:37: But the physical operations are dragging down the ROI.

00:03:40: if you have a fleet of five thousand cars You need a massive flexible workforce just to charge them and clean them And yes close the doors...you can't scale that with full-time software engineers Which

00:03:49: connects directly to what Augustine Friedel posted.

00:03:51: Yeah He coined this phrase That I think perfectly frames This whole deep dive.

00:03:55: he called it winner takes ops.

00:03:56: Winner takes ops.

00:03:57: I love that.

00:03:58: it's such a great pivot from the old Silicon Valley.

00:04:00: winner takes all mentality, which was always just based on who raised the most capital

00:04:04: or Who had the coolest algorithm?

00:04:06: Exactly Friedel is saying that capital isn't the moat anymore.

00:04:10: Everyone has access to good sensors.

00:04:12: now The real note Is can you build a depot?

00:04:15: Can you clean a spilled coffee out of the back seat in ten minutes so the car can get Back On The Road and generate revenue?

00:04:22: It sounds so mundane But if you can't do that, You don't have a business.

00:04:26: You just have very expensive science project.

00:04:29: And looking at the landscape it seems like Waymo and Tesla are taking two very diametrically opposed approaches to solving this winner-takes-offs challenge.

00:04:38: Oh,

00:04:38: completely!

00:04:39: Waymo is basically trying to engineer their way out of it with better hardware.

00:04:42: We saw those posts from Eddie M and Ilya Sigalovich about Waymo's sixth generation system.

00:04:47: Right the new sensor suite.

00:04:49: Yeah

00:04:49: they are investing heavily like twenty seven billion dollars heavily to drive a sensor cost down.

00:04:54: They've got the sweet under twenty thousand dollars now which is half of the previous generations.

00:04:58: That's

00:04:59: huge drop but they are still relying on a very hardware-heavy, expensive vehicle to guarantee what we call family travel safety.

00:05:07: Contrast that with Tesla!

00:05:09: Oh boy... yeah We had the data from Johnny Lu and Oleksandr Lubushin And frankly The gap between the Tesla narrative and actual operational data is getting really uncomfortable.

00:05:20: Uncomfortable

00:05:21: is definitely a polite way of putting it.

00:05:22: The narrative is unsupervised FSD full self driving.

00:05:27: But Lubushin pulled the NHTSA data from Austin, and the crash rates are honestly alarming.

00:05:34: Tesla Robo Taxis are crashing four times more often than human drivers...

00:05:38: Four Times More and eight times more than the national average.

00:05:42: That is a statistic that just stops you in your tracks!

00:05:44: If you are regulator or an insurance company, how do you even underwrite this risk?

00:05:49: James Sampson added context to Austin rollout specifically.

00:05:52: Service availability was only around nineteen percent.

00:05:55: Nineteen

00:05:55: percent?!

00:05:55: So four out of five time's you actually want car...you can't get one!

00:05:59: Basically

00:06:00: because of rain or fog..or system hesitating.

00:06:04: Samson points out that the gap between Tesla's stock valuation which basically assumes they have completely solved autonomy and The operational reality of a car.

00:06:11: That can't handle a foggy morning in Texas.

00:06:13: It's just widening by the day.

00:06:15: it really brings up the liability question, too If they are pushing this unsupervised angle But the car crashes four times more than a human.

00:06:24: who is liable?

00:06:25: Is it the owner?

00:06:26: Is it Tesla?

00:06:28: It feels like they are pushing the operational complexity onto the user, whereas Waymo is trying to internalize.

00:06:34: Even if its expensive

00:06:35: Exactly!

00:06:36: And we actually got a really interesting user perspective on that contrast.

00:06:39: Leonid Sarenko posted about taking a Tesla Robo taxi in San Francisco.

00:06:44: He noted it was definitely cheaper than Waymo which makes sense given the cheaper hardware.

00:06:48: But, but it still had a safety driver in the front seat and it dropped him off early because the road ahead was blocked.

00:06:55: And I just couldn't figure out how to reroute.

00:06:56: Wow Meanwhile Nico Rosberg who you know being a former F one champion knows thing or two about driving He took away Moan SF.

00:07:04: he was totally alone doing work in the back and he called The experience normal.

00:07:09: and this industry Normal is the holy grail.

00:07:12: boring as good.

00:07:13: if its boring It works.

00:07:15: Rosberg also threw in a quick side note about Germany, pointing out that regulations there are still forcing companies like they to use tele-driving instead of full autonomy.

00:07:24: Tele driving is fascinating.

00:07:26: it's almost like admitting defeat on the AI front at least temporarily.

00:07:30: It says the robot can't do it perfectly.

00:07:32: So let's just put a human in the simulator fifty miles away to drive The car over a five-g network,

00:07:38: it's a regulatory patch.

00:07:39: But you know while the West is endlessly arguing about teledriving versus full autonomy Versus open doors the Middle East and China are playing a completely different game.

00:07:48: Which leads us to the second major theme from the weeks seven and eight posts

00:07:53: that global divergence.

00:07:54: The updates out of the UAE were really striking.

00:07:57: We saw a post from Peggy Van de Plash and Yuri Damansky about Abu Dhabi, they aren't just running cute little pilots over there.

00:08:03: They are running commercial services with Uber in WeRide.

00:08:06: And the vibe is totally different.

00:08:08: It's not a scrappy startup trying to move fast and break things.

00:08:11: it's an infrastructure vibe.

00:08:12: Damanski called it methodical.

00:08:14: I think that was key word.

00:08:16: In US companies try build robots which can survive on chaotic human-centric roads.

00:08:23: In the UAE, they're building the roads and regulations to specifically accommodate robots.

00:08:28: It's an infrastructure first approach.

00:08:30: But there is a darker or at least much more complex economic layer here that Jamie Lane uncovered in his post.

00:08:37: Right!

00:08:40: Drivers are expensive, robots are cheap.

00:08:42: But in the UAE drivers often very low-wage immigrant labor.

00:08:46: they're already cheap.

00:08:47: So Lane asks does unit economics argument actually hold up

00:08:51: there?

00:08:51: That is such a brilliant question.

00:08:53: If you replace a low wage worker with highly complex high maintenance robotic vehicle Are you saving any money?

00:09:00: Layton connects this to the broader ecosystem.

00:09:02: You have a tech company in Guangzhou supplying cars, maybe using IP from a collapsed startup in San Francisco and then you've got seventy thousand migrant workers whose entire livelihoods depend on driving jobs.

00:09:13: So the efficiency they are chasing might actually be more about political goals or tech supremacy rather than pure profit margin.

00:09:21: It really challenges automatic assumption that automation is always cheaper

00:09:25: path.

00:09:25: It really does.

00:09:26: But there is one area where automation is undeniably winning on the profit front, and we almost completely ignore it because

00:09:55: quietly moving goods across China and other markets, And they are actually profitable in certain sectors.

00:10:00: Why is that?

00:10:00: Is their tech somehow vastly superior?

00:10:03: No the operational reality's just so much simpler.

00:10:06: think about it.

00:10:06: A box of vegetables doesn't complain if a car breaks too hard.

00:10:09: It doesn't leave the door open.

00:10:11: Exactly!

00:10:11: It does not leave the doors open...it doesn't sue you to get into minor fender bender.

00:10:16: Abdul Abdullah made very similar argument regarding autonomous trucks.

00:10:20: He believes trucks are going to scale way before urban robotaxis ever do because the environment mostly highways is simpler and The utilization is twenty four seven.

00:10:29: that makes perfect sense.

00:10:30: The operational constraints Are just so much lower, but when you try To bring that same tech into highly complex urban environments?

00:10:38: The friction spikes immediately.

00:10:40: Natalie Lung reported that New York Governor Hoshul Just halted a proposal for Robo taxi expansion outside of NYC.

00:10:47: A huge regulatory headwind for the West.

00:10:50: And contrast that approach with Hamburg, on just JARKS posted about Hamburg taking a partnership approach with FreeNOWS.

00:10:57: They aren't letting robo-taxes run wilds disrupt everything.

00:10:59: they are actively integrating autonomous taxes into the existing public transport network.

00:11:04: That

00:11:04: feels like The Mature Approach.

00:11:06: instead of disruption it's integration.

00:11:09: and speaking Of maturity we really need to pivot To micromobility because If robotaxis are currently in their awkward teenage years, it feels like scooters and e-bikes are finally entering adulthood.

00:11:20: Well some of them are!

00:11:22: The divergence between the winners & losers in micro mobility right now is incredibly stark.

00:11:26: Very true.

00:11:27: On the winner's side we have VOY technology Mathias Hermansen and Praven.

00:11:32: Joel Jones posted there twenty twenty five numbers And they're impressive.

00:11:36: Revenue was up thirty four percent And adjusted EBITDA Is up seventy percent.

00:11:41: Positive EBITDA in shared micro-mobility is a massive achievement.

00:11:45: I mean, for years the primary criticism was that these business models were fundamentally broken —that the scooters broke too fast to ever pay back their initial unit cost— but Voi seems to have actually solved The Winner Takes Ops puzzle!

00:11:57: How did they do it though?

00:11:58: Did he just massively raise prices on the

00:11:59: user?!

00:12:00: Not exactly... They shifted from being quote unquote scooter company…to becoming partner cities.

00:12:05: They secured long term contracts drastically improved vehicle durability, and they optimized that fleet rebalancing we were talking about earlier.

00:12:13: They essentially stopped treating it like a hyper-growth tech play and started treating it as public

00:12:18: utility."

00:12:19: Which is such contrast to Rand Power Bikes!

00:12:23: Horace Didier reported that they just filed for Chapter XI bankruptcy…and sold for just thirteen point two million dollars.

00:12:31: This was the company used to be at Unicorn.

00:12:33: It

00:12:33: highlights the brutal difference between service.

00:12:37: model.

00:12:38: Rad power was selling e-bikes directly to consumers.

00:12:41: That's a tough, tough business.

00:12:43: Margins are razor thin.

00:12:44: sitting on inventory kills your cash flow and once everyone who wants an E bike has bought one?

00:12:49: Your growth just stalls out!

00:12:50: Voie is selling the right itself which is recurring revenue

00:12:53: True but even The Surface model has its own operational kryptonite.

00:12:57: Enzo Lanieux posted about the weather situation in France.

00:13:00: Apparently extreme heavy rains wiped out millions of revenue In just forty six days

00:13:05: Millions And this exposes the core fragility of the model.

00:13:09: If it rains, utilization instantly drops fifty to eighty percent.

00:13:13: But your fixed costs-the warehouse rent The mechanic salaries The insurance one now Those stay exactly the same.

00:13:20: You can have best app interface in world but you cant code away rain.

00:13:24: So true Thomas Broughton raised another massive operational headache.

00:13:29: Parking He called a broken circle.

00:13:31: This is the user behavior problem all over again.

00:13:33: If the user doesn't park the scooter correctly, The city finds the operator not the user.

00:13:39: Broughton points out that the parking verification tech Is still really hit or miss.

00:13:43: it's another example where the Tech is ninety percent there.

00:13:46: but That last ten percent just verifying that the kickstand is down in the right spot can destroy the entire business

00:13:52: model.".

00:13:52: The solution to that seems a cultural Or at least structural.

00:13:55: Kirsten Heinkie post about Japan was Really eye-opening.

00:13:58: he describes A utility first culture Over There.

00:14:01: Japan is fascinating because they don't view cycling as some sort of micro-mobility disruption.

00:14:07: It's just how you get to the train.

00:14:09: Heineken noted that fifty seven percent of cyclists in Tokyo are women, often using those momotari bikes for shopping or carrying kids.

00:14:17: it's not about sport or performance like it often is on the west.

00:14:20: its fully integrated into the rail network

00:14:23: And we saw that exact same integration theme popping up in Switzerland.

00:14:28: Alexandra Klimt and Manuel Herzog posted about the city of Beale selecting Voi for safety-in-order, but the bigger news was OS Winane offering a twenty five percent discount on dot rides if you already hold to season train

00:14:41: ticket.".

00:14:42: That is The Magic Bullet right there!

00:14:43: True integration... When the scooter is just viewed as an extension of a train ticket, you solve your demand problem.

00:14:49: You aren't fighting for net new customers—you are just inheriting them directly from that train system last

00:14:54: mile.".

00:14:54: Which bleeds perfectly into our final theme… shared mobility and urban design!

00:14:59: Because if we're successfully integrating these things it actually changes It

00:15:04: does!

00:15:05: Gunnar Nurki dropped a stat that shows this is happening at scale.

00:15:08: Car-sharing parking spaces in public areas have gone up four hundred and ninety eight percent since twenty eighteen.

00:15:13: Wow,

00:15:14: That's massive reclining of public land... It

00:15:17: really is.

00:15:18: The working logic is one shared car replaces about ten private cars.

00:15:22: So you are trading one dedicated parking spot for nine spots worth open space or new bike lanes even housing.

00:15:29: But Brent Van Der Hiden reminds us that making the trade actually work is, again an ops nightmare.

00:15:35: He calls it orchestrating supply

00:15:37: Because demand isn't flat.

00:15:39: Everyone wants a shared car at five-zero p.m on Friday.

00:15:42: Nobody want one at three am Tuesday.

00:15:45: Managing those peak spikes without having thousands of expensive cars sitting idle Is a logistical high wire

00:15:50: act.

00:15:51: Proximus trying to force behavior change from corporate side Dorian and Drogfil share their new company policy And its bold Parking is no longer an entitlement.

00:16:00: I love this policy, they gave their employees a mobility budget.

00:16:04: you can spend it on a parking spot at the office if you really want to drive but If you bike or take the train You get to keep that money for other things.

00:16:12: It turns parking from a right into a product and when you put A price tag on it people start making very different choices

00:16:19: And Lars Christian Gruden Olsen points out That People are already Making Different Choices Because The Traditional Commuter Is Dead.

00:16:26: The nine-to-five Tuesday through Thursday commuter is an endangered species thanks to hybrid work.

00:16:32: The growth in public transport usage is now coming from leisure and social trips, not the morning grind.

00:16:38: that completely changes how cities need to plan transit.

00:16:41: we don't need to optimize purely for rush hour anymore.

00:16:45: We need to optimized for all day flexibility

00:16:47: which brings us to the geometry problem.

00:16:50: Damien Yao posted about the Auckland-Harbour Bridge debate.

00:16:53: They were fighting over a nine dollar toll, and Yao basically stepped in and said you're all asking the wrong question.

00:16:58: He argued for lane reallocation instead.

00:17:01: It's pure math.

00:17:03: A general traffic lane moves above three thousand people an hour maximum.

00:17:10: If you have a bridge with strictly limited physical space, why are you prioritizing the least geometrically efficient mode of transport?

00:17:18: It's not about inventing new tech.

00:17:20: it is about having political courage to reallocate concrete.

00:17:23: we already had.

00:17:25: So looking back at all posts from these two weeks... We've got two hundred thousand dollar robots being defeated by open doors!

00:17:31: Scooters becoming profitable by acting more like trains and cities realizing that a bucket paint to redesign a lane might be powerful than an app.

00:17:40: It all comes back to that boring era theme.

00:17:42: The core technology is here, it works mostly but the companies that are actually winning in twenty-twenty six aren't the ones with the flashiest demo video.

00:17:50: they're the one's mastering the mundane things closing doors cleaning cars integrating with train schedules and managing the P&L of a rainy Tuesday.

00:17:59: operations at the new strategy

00:18:01: exactly.

00:18:02: And Here Is A Final Thought For You To Take Away.

00:18:04: We've talked a lot today about efficiency, optimization and algorithms deciding routes in rebalancing fleets.

00:18:11: But as we move toward this fully orchestrated mobility where an algorithm decides if a car is available what the surge price is and where it goes... ...we are quietly handing over the basic right to move.

00:18:23: If the algorithm decides that certain neighborhood just isn't profitable because of quote-unquote operational reality What happens with people who live there?

00:18:33: Do we accidentally create algorithmic mobility deserts just because the ops are too hard?

00:18:37: That is the hidden cost of The Winner.

00:18:39: Takes Ops model.

00:18:40: Yeah, who actually defines the parameters with that algorithm?

00:18:43: Who owns the logic of our logistics?

00:18:45: a great question to end on.

00:18:47: if you enjoyed this episode new episodes drop every two weeks.

00:18:50: Also check out other additions on electrification and battery technology next-gen vehicle intelligence And commercial fleet insights.

00:18:57: Thanks for joining us

00:18:58: thanks for listening and don't forget to subscribe so you never miss a deep dive.