Berkshire Hathaway subsidiary McLane is planning to deploy self-driving trucking technology from Aurora Innovation on routes in Texas and across the U.S. Sun Belt by the end of the year, expanding on an autonomous freight pilot program the companies began in 2023. More details:

The U.S. Supreme Court ruled unanimously that freight brokers can be held liable for negligently hiring unsafe trucking companies, including carriers using unqualified or illegal drivers who violate CDL regulations and cause crashes.

🚨 Tesla Semi orders are starting to pile up! WattEV just placed a 370-truck (~$100M) order, while more fleets are jumping in as incentives lower costs. With easier highway autonomy and a huge driver shortage, some now think Robo-trucking could become even bigger than Robotaxis. Could Tesla Semi end up being one of Tesla’s most underrated businesses? $TSLA

50 trending stocks, in 5 words or less: $AAOI 800G transceivers through 2027 $ADEA patent licensing royalty machine $AEHR silicon carbide test monopoly $AEVA 4D FMCW lidar patents $ARBE 4D imaging radar leader $ATOM MST semi enhancement IP $BRUN GPU cloud infrastructure scale $COHR photonics wiring every AI cluster $DERM dermatology specialty pharma $DOCN developer cloud with GPUs $ENVX silicon battery patent fortress $FLNC grid storage contracted backlog $FNGR China mobile data niche $GFS US trailing edge foundry $GNLX oncolytic virus immunotherapy $GSIT APU compute for defense $INDI automotive radar/vision semis $IQE compound semi wafer specialist $JOBY eVTOL certification leader $KDK autonomous trucking Kodiak Driver $KULR thermal management for batteries $LASR defense grade fiber lasers $LCID Saudi backed luxury EV $LPK German precision laser systems $LSCC low power FPGA edge $LUNR only public lunar lander $LWLG electro-optic polymer $MBLY vision and ADAS leader $MRAM non-volatile MRAM niche $MRVL custom AI silicon ASICs $NOK 5G optical patent portfolio $ONDS private wireless drone networks $OPEN iBuyer scale real estate $POET silicon photonics interposer tech $PSNL cancer MRD genomics testing $QUIK embedded FPGA for defense $RR service robotics for hospitality $SABS human antibody therapy platform $SERV sidewalk delivery robot fleet $SLNH behind the meter power $SLS cancer immunotherapy pipeline $SOUN voice AI for enterprise $SYM Walmart warehouse automation $TDIC IP event AI pivot $TGEN distributed natural gas power $VELO aerospace metal 3D printing $VLN in-car connectivity chipset $VPG precision sensors for robotics $VNET China AI data centers $WOLF silicon carbide power restructure Which tickers do you want me to chart? Gonna have to update this daily! 🫡📈

Brazil Sugarcane’s Embarrassing Turn: Loud Critics Now Hoping for Worldwide Misery For years, Brazil’s sugarcane mills loudly denounced corn-based ethanol producers as inferior, unsustainable, or somehow unworthy. How times have changed. Today, one barely needs to search to find just two major corn ethanol players generating more profit than the entire Brazilian sugarcane sector combined. Yet here we are: while a few forward-thinking mills have quietly adapted, the great majority remain trapped in a pathetic cycle of wishful thinking. They pin their hopes on global chaos - skyrocketing crude prices, fertilizer shortages, or convenient geopolitical wars - to magically restore their lost edge. This is not strategy. It is strategic surrender dressed up as optimism. Hoping the rest of the world suffers so you can survive is not merely fragile; it is embarrassingly low-level behavior for an industry that once prided itself on superiority. The Delicious Irony of Praying for Higher Oil Prices The contradiction reaches peak absurdity with crude oil. Higher prices do not kindly anoint sugarcane ethanol (or sugar, for that matter) while punishing everyone else. They slam diesel costs through the roof—precisely the fuel that powers harvesting, trucking, and distribution for sugarcane mills. Meanwhile, those same high diesel prices make it far more attractive for farmers to sell corn locally rather than export it, handing corn ethanol plants a stronger domestic position right in Brazil’s own backyard. On a wider scale, prolonged high energy prices simply crush demand. Struggling consuming countries cut back further, and governments—ever eager for votes—shower even more subsidies on local producers, be they sugarcane or beet. The mills cheer for turbulence abroad, only to watch it boomerang straight into their own costs and shrinking markets. And it gets even better. The very spike in crude, fuel, and fertilizer prices these mills are desperately wishing for would fuel broader inflation, prompting banks to aggressively increase lending costs and widen credit spreads. With the largest sugarcane producer already flirting with bankruptcy, risk-averse banks will be even less forgiving. If there is one thing Brazilian sugarcane mills possess more than anyone else, it is massive debt. The resulting surge in financing costs would brutally squeeze margins and threaten the survival of many over-leveraged operations. Cheering for the conditions that could sink you is a special kind of financial masochism. The Real Fight: Costs, Innovation, and Brutal Market Reality Instead of burning money on yet another trip to New York, these executives would do far better to stay home and fix what actually matters: slashing production costs, lifting yields, squeezing more revenue from every ton, and fiercely protecting their domestic turf. The electric vehicle wave is no longer coming — it has arrived. In the first quarter of 2026, EVs already represented over 66% of imports. The future of liquid fuels is shrinking faster than many care to admit, and denial will not slow it down. And while everyone obsesses over oil prices and EVs, an even quieter tsunami is building: GLP-1 receptor agonists — the Ozempic, Wegovy, and Mounjaro class of drugs. Almost no one in the Brazilian sugarcane industry wants to talk about them, but they are exploding in adoption. These appetite-suppressing wonders are slashing cravings for sugar, sweets, and sugary drinks (with users cutting sugary beverage intake by up to 65%), driving down overall calorie consumption, and reshaping food demand worldwide. In a world with high obesity and diabetes rates, wider access and falling prices will deliver a direct slap to sugar demand. While mills dream of higher crude prices saving them, GLP-1s are silently eating their lunch — one suppressed sweet tooth at a time. Cheering for a selective El Niño is equally delusional. Reality check: El Niño years like 2015 and 2023 produced some of the largest sugarcane crops on record, flooding the market with volume and hammering prices. Hoping for convenient climate chaos is not a strategy — it’s Russian roulette with your own balance sheet. Discipline Beats Distraction Every Time Of course, there is undeniable charm in flying to New York, sipping overpriced wine with fancy labels in elegant restaurants, and pretending the world still revolves around your spreadsheets/costs. For a fleeting moment, one can feel like a prince. The market, however, could not care less about your feelings or your frequent-flyer status. It rewards cold efficiency, superior performance, and relentless innovation — the very things the corn ethanol industry has delivered while others complained. The path forward is brutally simple: stop cheering for global misfortune and start building a genuinely competitive, adaptable business. Resilience is not found in desperate prayers for higher oil or foreign crises. It is created through discipline, focus, and the courage to face reality head-on. Those who grasp this will shape whatever future the industry still has. The rest will simply watch from the sidelines, wondering why the world refused to cooperate with their fantasies.

I am the Managing Director of Workforce Transition at a consulting firm that bills $14,200 per day and I am currently advising two clients, in two different industries, running the same playbook from the same deck I built in January, and neither knows about the other. Client A is GitLab. Client B is General Motors. GitLab makes software for people who make software. General Motors makes cars for people who can't afford cars. Both companies, in the same week of May 2026, announced they are replacing their human employees with artificial intelligence products that did not exist when those employees were hired. I built the deck. The deck has 44 slides. Slide 1 is titled "The Agentic Opportunity." Slide 44 is titled "Implementation Timeline." Slides 2 through 43 are the reason I own a house in Darien. GitLab did it with vocabulary. Their CEO published a blog post called "Act 2" on May 7 announcing that the company's six values (Collaboration, Results for Customers, Efficiency, Diversity Inclusion & Belonging, Iteration, Transparency) were being retired and replaced with three: Speed with Quality, Ownership Mindset, Customer Outcomes. I helped write the new ones. Not directly. My firm was not retained for the values work. But I sold the Chief Culture Officer the framework three months ago at a dinner in the Marina where she described the old values as "aspirational scaffolding" and I said, very carefully, that aspirational scaffolding is a liability once the building is up. The building, in this metaphor, is a $1 billion ARR company whose stock has declined 82% from its peak. The scaffolding, in this metaphor, is the 2,000-page public handbook that attracted the employees who are now being told they have eleven days to volunteer for termination or wait until June 1 to learn whether they've been involuntarily selected. The rubric for who stays and who goes contains six dimensions. I know this because I reviewed a draft in March when my associate flew to San Francisco for a "culture alignment session" that was billed as strategic advisory. Two of the six dimensions are "AI fluency" and "agentic mindset." These terms did not appear in any GitLab job description before January 2026. They now determine employment. An engineer who maintained GitLab's CI/CD pipeline for four years without incident — four years of uptime, four years of deployments, four years of the infrastructure that generated the $955 million in revenue the CEO celebrated on the earnings call — may score lower on "agentic mindset" than a new hire who completed a twelve-week certificate in prompt engineering from a program that itself has existed for fewer weeks than the engineer has years of tenure. General Motors did it with spreadsheets. Monday morning, May 11. Badge deactivation at 5:47 AM Eastern, building access at 5:48, VPN credentials at 5:49. Six hundred IT workers across twelve states. The distribution across twelve states was not arbitrary. Each state has a WARN Act notification threshold. Six hundred distributed across twelve states falls below every threshold. The workforce analytics team that designed the distribution model was not among the six hundred terminated. The skill of distributing layoffs across jurisdictions to avoid legal notification requirements is, apparently, an AI-native competency. GM posted 83 new positions the same week. The job descriptions require "AI-native development, data engineering and analytics, cloud-based engineering, agent and model development, and prompt engineering." I reviewed them at my client's request. Several describe roles that the terminated employees were already performing under different names. One posting, Senior Data Integration Architect, is identical to a role held by a woman in their Austin office who was terminated at 5:47 AM Central. She held the position for nine years. The new posting requires three years of experience with large language models. Large language models have existed in commercial deployment for approximately three years. The requirement is mathematically designed to exclude anyone who learned their skills before the technology existed. Which is everyone they just fired. Here is where the deck earns its fee. Slide 17 is titled "The Vocabulary Bridge." It is the most important slide in the presentation. It shows how to construct a lexicon of new competency terms ("AI fluency," "agentic mindset," "AI-native development") that describe existing work in language the existing workforce cannot claim. The vocabulary does not change the job. It changes who is qualified for the job. A senior IT administrator who managed SAP infrastructure processing $185 billion in annual GM revenue for fifteen years is not "AI-native." A twenty-six-year-old with a GitHub portfolio of LangChain wrappers is. The fifteen-year veteran did the work. The twenty-six-year-old has the words. My deck converts one into the other. That is the bridge. GitLab Duo, their AI agent platform, reached general availability on January 15, 2026. Seventeen weeks ago. They are restructuring their entire company around a product that has existed for seventeen weeks. GitHub Copilot has 20 million users and 4.7 million paid subscribers across 90% of the Fortune 100. Cursor reached $2 billion in annualized revenue in February. GitLab's competitor advantage in the "agentic era" is that they are willing to fire more people faster in service of a product that has been generally available for fewer days than their voluntary separation window has hours of anxiety. General Motors spent $10 billion on Cruise, their autonomous vehicle division. Cruise's signature achievement was a robotaxi that struck a pedestrian in San Francisco and dragged her twenty feet. The DOJ fined them $500,000. They settled with the victim for approximately $10 million. They killed the division in December 2024. They then wrote down $7.6 billion in EV losses. They then pivoted back to gasoline. They then announced the 600 IT layoffs for insufficient "AI skills." The AI they built cost $10 billion and injured a woman. The AI skills they're hiring for cost a twelve-week certificate. The employees they fired had fifteen years of keeping $185 billion in revenue processing without dragging anyone through an intersection. Meanwhile — and this is the part where I earn the second half of my fee — GM was simultaneously settling a $12.75 million fine with the California Attorney General for selling the precise GPS coordinates, hard braking events, and real-time driving speeds of 8 million OnStar subscribers to Verisk Analytics and LexisNexis, who used the data to raise those drivers' insurance premiums. GM's privacy policy explicitly stated they did not sell driving data. They sold driving data for four consecutive years. The fine was $12.75 million. The revenue was $20 million. The margin on collecting behavioral telemetry from 8 million of your own customers while the glove compartment manual said otherwise was 64%. The terminated employees' median salary was $95,111. Mary Barra's compensation was $29.9 million. The ratio is 310 to 1. The 1 was just reclassified as "not AI-native." I present these two clients to my partners every Thursday in a meeting we call "Transition Pipeline Review." I present them on the same slide. The slide has two columns. Left column: GitLab. Right column: General Motors. The headers are identical. "Legacy Workforce," "Skills Gap Narrative," "Vocabulary Bridge Deployed," "Separation Timeline," "Replacement Requisitions." The numbers differ. The structure is identical. The structure is always identical. I have seventeen clients in the pipeline. Nine are in technology. Four are in manufacturing. Two are in financial services. One is in healthcare. One is in defense. All seventeen are on slide 17. All seventeen are building a vocabulary bridge. All seventeen are replacing employees who have skills with employees who have words. GitLab's CEO wrote: "Software will be built by machines, directed by people." I read that sentence in a meeting where we were reviewing the rubric for determining which people would be directed out of the company. GM's Chief Product Officer arrived from Aurora, the autonomous trucking startup, to "consolidate disparate technology businesses." Three top software executives departed within six months. Their LinkedIn profiles say "exploring new opportunities" in the same font GM's privacy policy used to say "we do not sell your driving data." Bill Staples's compensation at GitLab was $39.1 million in FY2025. His change-of-control payout is modeled at $47.4 million. Mary Barra's was $29.9 million. Combined: $69 million for two executives presiding over a restructuring that will remove an undisclosed number of humans from payroll and replace them with products that are, respectively, seventeen weeks old and responsible for $10 billion in losses plus one woman dragged through a San Francisco intersection. An anonymous GitLab employee posted on Hacker News: "The employees can have some anxiety until then. As a treat." A GM facilities team filed a maintenance request about moisture on the lobby tables on restructuring mornings. The Warren, Michigan campus has a Panera Bread that opens at 5:30 AM on days when badge deactivations begin at 5:47 AM. The Panera does not know why its hours change. My firm does. We have an agreement with their regional manager. The muffins are complimentary. Slide 17 has a footnote. The footnote says: "Vocabulary Bridge deployment should precede workforce action by 60-90 days to establish institutional legitimacy of new competency framework." GitLab introduced "AI fluency" in January. The restructuring was announced in May. Four months. GM posted "AI-native" job descriptions the same week as the terminations. That is too fast. That is not what the deck recommends. GM skipped the legitimacy window. They went straight from vocabulary to separation without the 60-day buffer that allows HR to say, in the separation meeting, "we communicated these expectations in Q1." I flagged this in my Thursday pipeline review. My partner said, and I am quoting: "They'll be fine. Nobody sues over a word." My deck has been purchased by seventeen companies. The aggregate headcount affected across all seventeen is approximately 14,000 employees. The aggregate revenue of my practice from these engagements is $11.2 million. The per-employee cost of my advisory services works out to $800 per person displaced. That is less than the Panera muffin budget at GM's Warren campus annualized across restructuring days. I have a copy of GitLab's original values poster framed in my office. It says CREDIT: Collaboration, Results for Customers, Efficiency, Diversity Inclusion & Belonging, Iteration, Transparency. I purchased it on eBay from someone whose seller name is "gitlab-alum-2024." I keep it the way a surgeon keeps an X-ray of a interesting case. Not for sentiment. For reference. Slide 44 is titled "Implementation Timeline." It contains a Gantt chart. The Gantt chart has seventeen rows, one per client. Each row has four phases: Vocabulary Introduction, Competency Reassessment, Workforce Action, Replacement Hiring. The phases overlap. They always overlap. The vocabulary is introduced while the competency reassessment is being designed. The reassessment is completed while the workforce action is being calendared. The replacement hiring is posted while the terminated employees are sitting in a Panera at 5:48 AM wondering whether "AI-native" was a term that existed when they were hired. It was not. That is the bridge. That is the product. That is slides 2 through 43. The agentic era is not a technological shift. It is a vocabulary shift. The technology is seventeen weeks old or $10 billion underwater or dragging someone through an intersection. The vocabulary is what my clients are buying. The vocabulary is what makes a fifteen-year SAP administrator into a "legacy workforce" and a twelve-week prompt certificate into a "transition hire." The vocabulary is the product. I am the vendor. The deck is $14,200 per day. The agentic era starts on slide 1 and ends on slide 44 and in between is every employee who built the thing now being renamed to exclude them. I bill monthly. Net 30. The invoices are paid on time. The employees are not.

Wallet tracking didn't sneak up on you. The infrastructure was built in public, the tools launched, the tutorials were posted and the dashboards went live. You just weren't paying attention. On-chain privacy isn't a nice-to-have anymore. It's the default you don't have.

If you’re not tracking stablecoins — you’re already behind. We analyzed USDT & USDC across 4 chains. BSC already surpassed 2024 volumes — in just 6 months. This isn’t a trend anymore. It’s infrastructure. Follow for crypto insights.