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The Grand Cherokee is lined with wood paneling, its windshield is cracked, and chunks are cut out of its side-view mirrors like pierced ears. That\u2019s where the cameras go, a grinning Joydip Saha tells me from behind the wheel. The manager of Stellantis\u2019 hands-free driving project lovingly taps what he calls \u201cthe most broken-up car,\u201d jerry-rigged with a yellow box sitting on the dashboard that lets a human grab control. It\u2019s an industry-standard \u201ckill switch\u201d used in many prototype vehicles. In technical terms, the safety driver can hit the kill switch to disconnect power to the advanced driver assist system module, stopping the ADAS system from controlling the vehicle. Then, the driver has full control over the vehicle.\u00a0<\/p>\n
Another piece of equipment connected to the kill switch \u2014 the STLA AutoDrive L2++ system embedded in the vehicle \u2014 beeps when it needs him to take control, a bit like a dog wearing a smart collar.<\/p>\n
And it\u2019s confused. We are in the bowels of the Chrysler Technology Center in suburban Auburn Hills, Mich., navigating through the rabbit warren of a parking structure on the campus built by Lee Iacocca, the former Fortune posterboy who broke ground on the 500-acre site in 1986 and dedicated it in 1991, at a cost the company puts at about $1 billion. With the headquarters tower added in 1996, it spans 5.4 million square feet, the second-largest building in the U.S. by floor space, behind only the Pentagon.<\/p>\n
Stellantis still runs its North American engineering out of Iacocca\u2019s building, and the people who work there still say \u201call under one roof.\u201d Inside, it\u2019s a pure shot of early \u201890s design. Skinny escalators climb skyward around an octagonal skylight, like a Clinton-era MC Escher drawing.\u00a0<\/p>\n
The interior of the Chrysler Technical Center.<\/p>\n
courtesy of Stellantis<\/p>\n
The diamond-shaped parking garage attached to it is unique and confounding. Saha\u2019s development mule heads toward the wrong exit and Saha has to put his hands on the wheel Even he finds the garage complicated. Auburn Hills\u2019 suburban roads are much better for a test drive and I watch Saha\u2019s mule smoothly navigate an intersection where two Michiganders decide to both make illegal multi-lane changes within seconds of each other.\u00a0<\/p>\n
Saha, the global engineering manager who serves as the owner of Stellantis\u2019 L2++\/hands-free door-to-door supervised automated driving system, has been at this longer than most. He worked on the Chrysler Pacifica that Stellantis supplied for Waymo\u2019s first robotaxi in Arizona, then managed a group that integrated Level 4 autonomy with partners including Aurora and Lyft. He still test-drives every new software build himself, as often as twice a week, because he considers any problem a customer faces problems\u00a0 to be his responsibility. He said his team built the Cherokee\u2019s hands-free system in six weeks with the help of AI tools, when a similar project used to take a year or even 18 months.\u00a0<\/p>\n
He has a rule for AI, though: \u201cI will not let people use AI to architect stuff because they will forget how to debug stuff,\u201d he said. In a safety-critical business, he adds, engineers have to be able to answer every question.<\/p>\n
Joydip Saha<\/p>\n
courtesy of Stellantis<\/p>\n
Across two days of interviews at the technology center, engineers told Fortune that AI has turned yearlong projects into weeks and overnight simulations into minutes. Stellantis wants that speed to cut development time on its new computing and cockpit software, STLA Brain and STLA SmartCockpit as part of a general push to speed vehicle development from four years to 24 months, starting with two models in 2027. But nearly everyone who described a speed-up also described checking the machine\u2019s work. Stellantis also has problems bigger than time savings. The company has 14 brands, a European business that is losing money, and a second-quarter adjusted operating margin of 1.8%, while CEO Antonio Filosa has set a margin target of 7% for 2030.<\/p>\n
Wall Street isn\u2019t waiting. Stellantis is the member of Detroit\u2019s Big Three most exposed to Europe, which accounted for about 38% of its 2025 revenue. (GM sold its European brands, Opel and Vauxhall, in 2017 to PSA, one of the companies that later merged to form Stellantis.) Europe also leans much harder toward electric vehicles than truck-happy America: : battery-electric cars made up 17.4% of new EU registrations last year, according to ACEA, compared with 7.8% of U.S. sales, according to Cox Automotive.\u00a0<\/p>\n
Stellantis had also bet heavily on EVs in North America, and it took the biggest hit in Detroit after the $7,500 federal EV tax credit ended on Sept. 30, 2025. In February, Stellantis wrote down roughly \u20ac22.2 billion (about $26.5 billion), more than Ford\u2019s $19.5 billion charge in December or the $7.6 billion GM took across two charges. Stellantis shares fell 25% that day, and the reverberations are still being felt, with the stock down nearly 60% year-to-date.\u00a0<\/p>\n
Mel Roberts, the director of North American infotainment, who plans the features inside Stellantis vehicles five to eight years out, said AI was not her biggest surprise of the last several years. \u201cWhat I couldn\u2019t anticipate is just the complete collapse of the electrification ambitions and how that really did affect all of our future plans,\u201d she said. \u201cIt trickled into everything.\u201d<\/p>\n
Detroit\u2019s European giant<\/p>\n
Stellantis is the only one of Detroit\u2019s Big Three to be legally headquartered abroad, in the Netherlands. It\u2019s the result of a pandemic-era merger in 2021 between Fiat Chrysler and the PSA Group that brought iconic European brands such as Peugeot and Citro\u00ebn together with Fiat, Jeep and Ram. That gives it a distinctly international air, as Fortune met executives born in France, Mexico and Bangladesh within minutes of each other, along with a Michigander back from a few years stationed in Paris.\u00a0<\/p>\n
The mergers also left behind a machine built by committee. Ben Zawodni, manager of software engineering, is working to fold the hundreds of electronic control units, each a small computer with its own job, into a central \u201cbrain\u201d called, naturally, STLA Brain. Over the decades, he says, the car\u2019s architecture had evolved over time to really mirror the supply chain. \u201cWe were bolting on features.\u201d\u00a0<\/p>\n
Amanda French, who leads the company\u2019s platform teams, is tackling the same problem one layer down. Stellantis historically built separate platforms, each to a fixed size. Its new platform, STLA One, is built to stretch from small B-segment cars to midsize D-segment vehicles. The company says it is designed to grow into a mega platform supporting 30+ models and targeting more than 2 million units by 2035. Asked whether building it felt like playing with Legos, French responded, \u201cYeah, with a lot more people and emotions involved.\u201d\u00a0<\/p>\n
\u2018Not there yet\u2018<\/p>\n
Upstairs at the technical center, Chief Engineering & Technology Officer Ned Curic is a self-described \u201cintense\u201d but talkative and warm presence. He came to Stellantis by way of Amazon, with previous stints at Microsoft and Toyota. He explained that Stellantis is not where it needs to be. Some teams show \u201cphenomenal successes,\u201d he said. In building that culture, he said, \u201cas a whole organization, we are not there.\u201d<\/p>\n
Curic sounds exasperated with an industry that has piled on complexity. Cars now come with \u201cfive screens, like digital noise, like 350 features,\u201d he said, and automakers have historically tended to \u201cchecklist the heck out of the features\u201d without measuring how people actually use them. He said he learned from Toyota that \u201cthe highest quality part that you have in a car is the part that you don\u2019t have in a car.\u201d In Stellantis\u2019 research on drivers, for instance, he said most people preferred a mechanical stick to a button on a screen.<\/p>\n
Ned Curic, chief technology officer at Stellantis.<\/p>\n
courtesy of Stellantis<\/p>\n
At Amazon, Curic received Jeff Bezos\u2019 notorious emails forwarding on customer complaints. The body of each email was a single question mark. \u201cI never found it stressful,\u201d Curic said. \u201cNever.\u201d One executive would handle the problem, he explained, and the others would each write a couple of paragraphs to help.\u00a0<\/p>\n
From Amazon and Toyota, Curic also brought small teams from the \u201ctwo-pizza rule\u201d and single owners for each system, so engineers who once sat in separate groups can\u2019t blame each other when something breaks. \u201cIf you see something that\u2019s wrong, you just pick it up,\u201d he said. \u201cI own it.\u201d\u00a0<\/p>\n
The hardest idea he\u2019s selling is that \u201cthe best thing that you can do for your career is to make yourself redundant.\u201d He has done it himself several times by getting a team in good shape, leaving, and starting something new. For that to work, Curic said, the company has to make sure there is always a new opportunity for those people, and that leaders need maturity and confidence. Asked whether Detroit\u2019s long run of hard times makes people defensive about change, he replied that while there is always a bit of a fear, change is a lot more accepted, \u201dand actually sought after.\u201d<\/p>\n
The man telling engineers to make themselves redundant is also hiring them. At the Paris auto show in October, Curic told Bloomberg that Stellantis would add \u201cmultiple hundreds\u201d of engineers in Europe and the U.S. this year.<\/p>\n
The starting gun<\/p>\n
The pressure lands on engineers like Zawodni and French. Both of them are tackling Stellantis\u2019 tricky margins issue by simplifying the wiring for each vehicle to bring the manufacturing into alignment, cutting costs and boosting Stellantis\u2019 profits back to where they need to be. \u201cThe AIs aren\u2019t going to tell us what the new platforms are,\u201d Zawodni said.\u00a0<\/p>\n
Zawodni said he started working on consolidating the cars\u2019 central computing during COVID, when engineers went fully remote and Stellantis set up labs in India, Poland and North America that could be logged into from anywhere. A proof of concept for a global observability platform, which monitors software deep inside the car\u2019s computers, took a week. Before agentic coding tools, he remembered something like that would take six months. And defects that took two to three weeks to fix shrank to two to three days. \u201cWe knew that we had to really reimagine all of our time,\u201d Zawodni said. Did that scare him? \u201cHow exciting, right?\u201d<\/p>\n
French, a cheerful engineer from southern Indiana, lit up when the conversation turned to AI, though hers was a more measured take than Zawodni\u2019s. She said human judgment \u201ccannot be replaced,\u201d but AI helps her pull together requirements and bills of materials stored in regional systems that were never built to talk to each other, because Stellantis is \u201cmade up from a number of different companies.\u201d She compared AI to an interactive form of Cliffs Notes she wished for in school.\u00a0<\/p>\n
Zawodni said his team was not all as excited about the AI breakthroughs as he was. \u201cI think there was a starting gun, and that starting gun went off,\u201d he said. \u201cSome people heard it, and some people didn\u2019t.\u201d Of his own engineers, he calls it a mixed bag. \u201cEngineers are really afraid of losing their core skills,\u201d he said. They want to know why a semicolon in a coding language does what it does. He called that \u201ca valid curiosity,\u201d but argued that it doesn\u2019t get Stellantis to its goals. He wants them to become architects, and eventually chief architects.\u00a0<\/p>\n
The tools haven\u2019t lightened Zawodni\u2019s own load. \u201cAgentic tools, they\u2019ve made our work so much easier,\u201d he said. \u201cSo why am I working so much harder?\u201d He estimates he works at least twice as hard as before. \u201cI feel a tremendous sense of urgency.\u201d He said, \u201cI really hope that we can transition responsibly \u2026 especially our people.\u201d<\/p>\n
Choosing battles<\/p>\n
Anne Laliron, a French engineer who runs Stellantis\u2019 roughly 400-person tech research group, gave up her office after COVID so her team can always find her, and she lights up talking about their energy. Her job is deciding which big bets to make. Stellantis can\u2019t afford to do everything, so it designs battery cells in-house and partners with startups for the rest. \u201cIf you want to embrace everything,\u201d she said, \u201cyou are at risk of spreading your effort.\u201d<\/p>\n
Anne Laliron, SVP of Tech Research at Stellantis.<\/p>\n
courtesy of Stellantis<\/p>\n
For Stellantis, partnering is a way to punch above its weight. The company brings in Wayve, a British startup, for the perception software in its hands-free driving, works with the French startup Tiamat on sodium-ion batteries, with Zeta Energy on lithium-sulfur batteries, and owns a stake in the Chinese EV maker Leapmotor, selling its cars outside of China through the joint venture Leapmotor International. Laliron said the habit runs deep at Stellantis and is less common at other automakers. Curic wants a culture where \u201cit doesn\u2019t have to be invented here,\u201d and he said the learning with Leapmotor runs both ways: \u201cWe learned a lot\u2026 we also taught them a lot.\u201d Stellantis runs batteries the same way, Laliron said: design in-house, partner with startups, and leave mass production to its gigafactory partners.<\/p>\n
Their biggest bet sits on a stage nearby: a battery-electric Dodge Charger prototype carrying a solid-state battery from Factorial, a Massachusetts startup Stellantis has worked with since 2021. The two companies run it as one team, and Factorial co-founder Siyu Huang says the startup has done it with $250 million in capital, a fraction of what some competitors have spent. The car worked the first time they turned the key. But Huang puts the technology three to five years from automotive production, and Laliron cuts about 10% of her group\u2019s projects every year when they don\u2019t pan out. \u201cIt\u2019s always painful,\u201d she said.<\/p>\n
Still one car a day<\/p>\n
Elsewhere, the speed-ups are real, but still small next to Stellantis\u2019 problems. Arturo Guzman was among the first to bring AI into the company\u2019s aerodynamics work, about five years ago, after a startup struggled to explain it to him in a side conversation at a conference.<\/p>\n
Now he explains it to vice presidents, and he starts by taking the mystery out. \u201cThere\u2019s no miracles. There\u2019s no magic,\u201d he said. \u201cFor us being engineers, all this is a Python code.\u201d Run through his team\u2019s model, a design change to a Ram pickup\u2019s front splitter returns a drag estimate in about three minutes. The full simulation used to take 14 to 24 hours. He tells his directors it\u2019s like an intern. His younger engineers get a different metaphor: R2-D2 from Star Wars. \u201cYou just give it a task and come back and see what it did.\u201d<\/p>\n
Arturo Guzman, manager for aerodynamics.<\/p>\n
courtesy of Stellantis<\/p>\n
Guzman said the time his team saves goes to \u201cother stuff.\u201d His team now generates new guidelines, takes requests from across the company, and mines its simulation data for patents. \u201cNow I tell them, just send me the data,\u201d he said.<\/p>\n
Through the doors to the wind tunnel, the giant equipment runs at pretty much the same pace it always has. It still tests \u201ctypically, one car a day,\u201d said Steve Kubiak, a deadpan Michigander who started at Chrysler in 1992 and has supervised the tunnel for about 10 years. Asked whether the process has changed over time, he said, \u201cNo, it\u2019s always been the same.\u201d The analysis is speeding up even if the testing isn\u2019t. A colleague, Todd Lounsberry, gives AI the data from the last 20 runs of a test and asks what it sees. Asked how someone becomes the manager of a wind tunnel, Kubiak responded, \u201cFirst you get a wind tunnel.\u201d\u00a0<\/p>\n
Steve Kubiak, wind tunnel supervisor.<\/p>\n
courtesy of Stellantis<\/p>\n
Other engineers are keeping AI on a short leash. Mohammed Malik, who runs Stellantis\u2019 driving simulators from the Automotive Research & Development Centre in Windsor, Ontario, said his group is \u201ckeeping it in the box,\u201d but even so, technology has transformed his work. Malik at work is like a life-size, immersive game of Mario Kart, the classic racing game where Nintendo characters pick their car and track then try to dodge obstacles to the finish line.\u00a0<\/p>\n
His job has been transformed by his simulator more than by AI. Engineers used to tune a vehicle on a computer, build a prototype and only then find out how it felt. Now a driver can feel the computer model before anything is built, and Malik can swap springs on the fly. He can test 10 tires in an hour, something no prototype can do. His team has scanned about 20 roads, from racetracks to local streets, in 10-centimeter squares, and it trades models with colleagues in Brazil and Italy instead of shipping cars across oceans.<\/p>\n
Malik plays me a video of a full-size Stellantis body that lacks any wheels \u2014\u00a0instead it\u2019s suspended on what appear to be mechanical spider-legs, bobbing up and down, back and forth in front of a giant TV screen with a track. Asked whether he ever played Mario Kart, he said he has a track of his own, built by a student. \u201cYou can drive the Rainbow Road if you want,\u201d he beams from behind his bushy mustache.<\/p>\n
Mohammed Malik in action in Windsor, Ontario.<\/p>\n
courtesy of Stellantis<\/p>\n
AI\u2019s role is narrower. A simulator run produces thousands of channels of data, and when a car hits a bump and \u201cswirls a little bit,\u201d Malik asks AI which channel to look at. His ambition is much bigger: feed an agent every test driver\u2019s scorecards from every region, ask it \u201cwhat does it take to make a Jeep,\u201d and let it drive the simulator itself until the answer feels right. For now, he said, the company is moving at a very slow pace and wants some form of control. \u201cSome of the stuff we want to do, we can do today,\u201d he said. \u201cAnd some of the stuff we want to do, we cannot.\u201d<\/p>\n
The bigger surprise has been people\u2019s willingness, or lack thereof, to adapt. Veteran test drivers who spent 10 or 20 years in physical prototypes were slow to move to the simulator. Young engineers with racing setups in their basements took to it right away. Laliron has seen the same thing. Experienced engineers carry old failures with them, she said, and sometimes \u201ctheir brain is closing doors.\u201d<\/p>\n
Some people have made peace with work that is better but not faster. Roberts said her AI research tool returns 10 to 15 sources, and she has to check every one. \u201cI don\u2019t think it saves time,\u201d she said, though it makes her work more \u201crobust.\u201d\u00a0<\/p>\n
One more cycle<\/p>\n
Alison Rahm, the chief vehicle engineer for midsize and large SUVs, has seen this before. She is moving back to Michigan after two years running Stellantis\u2019 European car lineup from Paris, and she remembers a staff meeting in 1997, when her boss told the room they were getting something new called email. \u201cAll of us were in a total panic,\u201d she said. They went back to their desks and tried it anyway.<\/p>\n
AI now runs checks that people used to do by hand, Rahm said, like going down a list of about 1,000 engineering design practices. That frees engineers to ask whether the rules themselves are right. But she isn\u2019t ready to stop double-checking. For years after virtual crash testing arrived, she notes, engineers still crashed real cars into the walls to convince themselves the situations were right.\u00a0<\/p>\n
Asked how long it will take to trust AI the same way, Rahm paused. \u201cI think we need another life cycle to prove to ourselves that our assumptions were right.\u201d While cautioning that different products have different life cycles, she deliberated. \u201cI would say four years.\u201d That would land in 2030, the year Filosa has promised a 7% margin.<\/p>\n
Saha drives us back into Iacocca\u2019s garage, and puts his hands back on the wheel of the Cherokee as the diamond-shaped parking structure looms. The robot needs a guiding hand coming home.\u00a0<\/p>\n
Saha takes a long view on when the AI game will shake out. As we roll into a smooth parking job, he turns to me and says he\u2019s a Game of Thrones fan (his favorite character is Robb Stark). While he works in logic, he explains, he likes fantasy because he finds he needs \u201cto be a little bit philosophical\u201d with the other side of his brain. \u201cCreativity is very important.\u201d<\/p>\n
Saha says he\u2019s a Game of Thrones fan, more into fantasy than science fiction.<\/p>\n
courtesy of Stellantis<\/p>\n
Saha takes a long view on when the AI game will shake out. As we roll into a smooth parking job, he turns to me and says he\u2019s a Game of Thrones fan (his favorite character is Robb Stark). While he works in logic, he explains, he likes fantasy because he finds he needs \u201cto be a little bit philosophical\u201d with the other side of his brain. \u201cCreativity is very important.\u201d<\/p>\n
Humans have adapted and thrived to date by figuring out creative solutions, he said. \u201cWe were never the strongest animal in the world,\u201d he said, riffing a bit in the style of Game of Thrones writer George R.R. Martin. He suggests that several hundred years of industrialization led people sometimes to get used to process-oriented thinking. \u201cMy understanding is we\u2019re going to leave behind the process-oriented world because AI is going to help us. And my personal belief is that\u2019s actually good.\u201d\u00a0<\/p>\n
\u201cThere will be some loss,\u201d Saha said, as there is with any technological shift. But he pointed out that humans have adapted to the natural world through creativity over and over again. \u201cPeople are going to figure out how to tame AI, too.\u201d<\/p>\n
[This report has been updated to clarify Ned Curic and Joydip Saha\u2019s job titles with more specificity: Chief Engineering & Technology Officer and owner of L2++\/hands-free door-to-door supervised automated driving, respectively.]<\/p>\n
#career #redundant #Stellantis #push<\/p>\n","protected":false},"excerpt":{"rendered":"
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