AI LLM Systems Are Allegedly Susceptible to Used Car Sales Tactics
May 27, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
Obviously I believe everything I read on the Internet. When the information is presented with academic rigor and journalistic flair, I am going to believe what’s presented.
The robot wants an SUV but the used car dealer sells the idea of a sports car. Thanks, MidJourney. Good enough.
I read “You Can Persuade AI Models to Accept Falsehoods As Truth, Study Shows.” (The story may be paywalled so heads up.) The write up says (with flair, of course):
What happens when AI systems are gently pushed toward falsehoods? Do they resist, or do they comply?… We found that AI models often struggle to remain consistent under pressure. Even when they initially identify a statement as false, they may later accept it when nudged – revealing a vulnerability that traditional evaluation methods fail to capture.
Yep, the old nudge play. I remember a pretty far out MBA from the University of Chicago who extolled the brilliance of the nudge method. I pointed out to this technofascist a 1962 book called Propaganda by Jacques Ellul. Yep, I got the dead eye stare and a sniff.
The cited article from the Conversation offers:
An AI model’s willingness to reinforce falsehoods may seem harmless when chatting about movies, but in areas such as health, law or public policy, the tendency can have serious consequences. Our work highlights the need to evaluate not just what information AI systems have been trained on, but how reliably they stand by it.
I agree. I noted this statement in the write up:
How to design AI systems that remain both helpful and resistant to falsehoods under wide-ranging conversation remains an open challenge.
The issue, however, is that used car sales tactics can be applied to certain AI models so that the outputs are distorted. The amusing characteristic of hallucination is well known. But now a user can input or poison the prompt/query so that the outputs are no longer congruent with whatever the model presents as accurate. I think the AI manipulation angle or what I call used car dealer sales tactics may be an oversimplification of a more complex and problematic facet of LLMs anchored in the Google “Attention Is All You Need” foundation.
Nudges are great.
Stephen E Arnold, May 27, 2026
Alpha Compute Emits Another Financial Message: Is It Actual Factual?
May 25, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
On May 21, 2026, the quite interesting and busy outfit Alpha Compute released this content marketing item via GlobeNewswire by Notified: “Alpha Compute Corp. Provides Mid-Q2 2026 Update. ALPHA-01 Completed and ALPHA-02 Underway of B300s located in Swedish Data Center, $16.1 million in Annual Revenue.”
The title suggests a fairly involved mix of information. The release locations for the content marketing item is Road town, Tortola, British Virgin Islands. This location for a NASDAQ-listed company is one of bits of information I found interesting. In my notes for my new Telegram-centric monograph, I have Alpha Compute’s location as Las Vegas. I will have to figure out whether the company is in the British Virgin Islands or in a rent-a-office or Enzo Villani’s property in a residential enclave in Vegas.
An analyst tries to penetrate the fog surrounding a basic news story about a financial transaction. Thanks, MidJourney. Good enough.
The main idea in the content marketing item, in my opinion, is that Alpha Compute has made “financial progress.” I don’t want to be a Debbie Downer, but the content marketing story claims millions in revenue and hundreds of GPUs cranking away in a data center in Canada. But I was not able to find the answers to these questions in the content marketing story:
- A named customer;
- A named Canadian data center operator;
- Any NVIDIA, Dell, data-center, or customer confirmation;
- Any photographs of the facility;
- Any independent verification of the data center;
- Any disclosed invoices;
- Any disclosed bank receipt for the $7.5 million upfront payment;
- Any workload metrics, utilization logs, wallet/payment flows, or customer-use data.
In short, the GlobeNewswire story did not contain facts to back up the “news.”
The write does state that the money is from “a $32 million, two-year agreement.” The cash reported in the content marketing story is a $16.1 million up front payment. (Why an upfront payment to lease machine time? In my experience, pay-as-you is more common, but I am not an expert is the resale and provision of AI compute.
The May 12, 2026, SEC exhibit says the upfront payment was “expected” and would secure capacity for two years. The the May 21, 2026 Alpha Compute new release says the payment was “due.” My hunch is that there is a deal. Alpha Compute may annualize the two-year $32.2 million agreement into $16.1 million annual recurring revenue. I assume the cash is in the Alpha Compute bank, but it may be a sales metric. I don’t know.
The May 21, 2026 content marketing story reports a $26.6 million GPU lease liability. I interpreted this to mean that the GPUs may be financed leased, not purchased with cash. Under lease accounting, it is possible for some interesting accounting methods that would allow a right-of-use asset and matching lease liability. This would increase both assets and liabilities without requiring hard cash upfront. Again, I simply don’t have the information to verify the numbers. The money is “expected.” On April 22 and 29, 2026, Alpha Compute disclosed a binding term sheet for a $31.9 million non-recourse loan facility secured by B300 GPUs. But the definitive documentation is apparently still in a bureaucratic process. I don’t think this is the same as cash. Again, I just don’t know from the information available.
The information I would like to see (and maybe a potential investor in a penny stock would like to review) is:
- A customer name, not a “frontier” outfit
- A related-party disclosure
- A contract exhibit or a short summary of material terms
- A payment receipt
- The name of the data-center operator, not just a country
- A customer confirmation
- A revenue-recognition note in an Alpha Compute 6-K / 20-F
- A footnote pointing to a related third-party
- A cash-flow statement showing payment received
- Some accounts receivable / deferred revenue detail
- Who paid the “$7.5 million”; for example, the frontier outfit, a business partner, or a commercial financing firm.
After reading the content marketing item, I noted that the wording of the cited story does not emphasize Telegram. Alpha Compute seems to have pivoted away from its original business idea of selling AI compute to Telegram to support Telegram’s AI requirements. Second, the cited document uses catnip-like revenue words before providing evidence of cash. “Contracted revenue,” “projected revenue,” “pipeline,” and “payment due” do not lower my interest in verifying the information in the content marketing story. Finally, who is the customer. The anonymity approach strikes me as material. Specific named entities are omitted from the write up.
Net net: The business of Alpha Compute evokes questions. The lingo in this content marketing piece uses more SEC-type jargon. But public information omits customer identity, payment receipt, and other key data points. The Globe Newswire content marketing item could be actual factual, semi-real, or a carefully-shaped information item designed to improve the “look and feel” of the Alpha Compute organization. I will be looking for information in subsequent SEC filings and “news” stories for data about cash, deferred revenue, receivables, lease liabilities, and related-party disclosures. As I stated, Alpha Compute is “interesting.”
Stephen E Arnold, May 25, 2026
AI in the Enterprise: A Work in Progress
May 22, 2026
![green-dino_thumb_thumb[3]](https://www.arnoldit.com/wordpress/wp-content/uploads/2026/05/green-dino_thumb_thumb3-2.gif "green-dino_thumb_thumb[3]")
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I read “Nearly Every Enterprise Is Investing in AI, But Only 5% Say Their Data Is Ready.” I have to tell you that the information in the story is a replay of feedback I heard when enterprise search was the next big thing. Companies spent big money because marketers with slide decks and a canned demo showed how one could find exactly the information needed to answer a critical business question. The only thing missing was a vaudeville orchestra and a second act. After the boos started, enterprise search just chugged along the Information Highway. I could trot out the reasons for failure, but why not chase down a copy of “Successful Enterprise Search Management.” We did a reasonable job of explaining the problems. One of the major ones is that enterprise information is a bit of challenge. Without money, people, and time, it would undermine many enterprise search systems. Why? Employees and authorized users like contractors could not find the information that was supposed to be available to address business issues.
Thanks, MidJourney. Good enough.
I have said that artificial intelligence is little more than a variant of search and retrieval. Instead of clicking and reading documents, one uses the output of a query in the form of a generative content object. The big advance that would provide information relevant to a prompt or a query was software systems that would do the hard work humans don’t like to do. Just take the output and use it. Computers don’t make mistakes, right?
The main point of the Computerworld article is to remind the article’s readers that smart software seems smart, but in a number of ways it is not just dumb. It is a problem. The article reports:
According to a new AI Momentum Survey from Dun & Bradstreet, 97% of organizations report active AI initiatives, but just 5% say their data is ready to support them.
What data problems in 2026 with SGML, XML, HTML, Markdown, DOCX, etc. etc. plague enterprises? The same issues that caused enterprise search to run aground usually the day the new system was turned on. Other issues are:
- 44 percent report privacy and compliance issues
- 40 percent data quality
- 38 percent report a lack of integration
People want AI to work. But consider the issues: Hallucinating and making up information. The idea of creating a local large language model is a good one. However, the options for following this path are what one might call fluid. Every day I receive information about a new system. The most recent approach is from Fireworks. Most software works. Agents work. Most queries work. The problem is that the entire edifice is based on a technical approach that generates made up information.
That is a problem on top of the old problem of search and retrieval.
From my point of view, AI systems are okay for testing. But I am not certain today’s smart software is up to some of the tasks the marketers insist are no brainers. The write up includes this passage:
it’s relatively easy for enterprises to launch copilots, chat interfaces, or departmental AI tools using general-purpose models and get “impressive results in a controlled environment.” But far fewer are able to deploy AI into production workflows, where accuracy, accountability, explainability, interoperability, and consistency directly impact business decisions. This includes areas like onboarding, compliance, risk management, and customer operations.
I want to end this blog post with a comment about data. Information updates flow constantly in an organization and the world. Some information is classified. Other information is in silos and available only to specialists in a research unit. Important pricing information may exist on a sales professionals laptop. The myth that everything is available is nuts and wildly out of whack with how organizations work.
AI is a utility. It is not fire or the wheel.
Stephen E Arnold, May 22, 2026
Should You Be Afraid of Self-Driving Vehicles? Just in the Rain
May 21, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
When I commuted from Berkeley to San Mateo, at work people would say, “I don’t know why my car can’t creep along and just avoid a wreck.” The task struck some as trivial. Straight shot. Bumper to bumper. That was in 1986. It is 2026, and where are we with the self driving thing?
Cats know that full self driving vehicles can be problematic. Thanks, Midjourney. Good enough.
“Waymo Recalls Thousands of Self-Driving Cars after Glitch Led to Creek Accident” encapsulates the problem. The article reports:
Waymo issued a voluntary recall of around 3,800 robotaxis after a software glitch allowed one of its self-driving vehicles to drive into a flooded road.
Water. Self driving cars have killed beloved cats, some people, and the crazy promises about full self driving electric cars that can drive into water. Nope.
The write up says:
The NHTSA confirmed that approximately 3,791 vehicles are affected by the recall, citing that “the software may allow the vehicle to slow and then drive into standing water on higher speed roadways.” The agency warned that when a vehicle enters a flooded road, it risks losing control, “increasing the risk of a crash or injury.”
This self driving car was a next big thing. Quantum computers were the next big thing. AI is the next big thing. Is there a common thread among these next big things? Yes, none of the next big things work reliably. What’s reliable is the marketing? The venture funding? And the dead cat in the Mission District in San Francisco.
Several observations seem to be warranted:
- Can one trust Silicon Valley companies pitching the “next big thing”? I don’t.
- Are the next big things just goals based on memories of Star Trek and Star Wars? Pretty much I think.
- Will these ideas become more reliable? Yes. Just not at the speed the hype artists promise.
Net net: Waymo is Googley. AI companies are trying to be the “winner” and mostly based on one set of methods which have the charming characteristic of hallucinating. And the quantum thing? Well, you won’t have a quantum computer laptop any time soon.
Decades of effort and self driving cars struggle with water. Yeah.
Stephen E Arnold, May 21, 2026
Enzo and Some AlphaTON-Alpha Compute Razzle Dazzle
May 20, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I have a new post about a Telegram-centric company. The title of the article is “Enzo Villani: An AI Play with LA Style.”
Censorship is all the rage. We continue to try to work around blocks on our Telegram write ups. We have posted a new one about AlphaTON Capital aka as Alpha Compute. One of the figures who is front and center since the interesting reverse merger dumped the Uzbeki financial manager is Enzo Villani. He is a former dignitary at the hard working outfit the US Securities & Exchange Commission. In the last decade when crypto was gaining and then losing momentum for some investors, Mr. Villani was engaged in a number of financial projects. Our new write up lists some of them. We also describe Mr. Villani as a strategic decider. Tactical actions appear to fall upon the strong shoulders of the Russian Yuri Mitin and Brittany Kaiser, the former executive at the remarkable Cambridge Analytica services firm. You should be able to find a version of this write up based on my continuing research for my monograph “The Telegram Labyrinth.” Navigate to this destination.
These Telegram posts have been blocked by BearBlog, a low profile outfit not small enough to be influenced by mystical fortunes and the layoff- and innovation centric LinkedIn. Locating these posts in Yandex is a hit and miss operation. Part 2 of the Villani essay will roll out next week. Its focus is on a company that is what appears to be a variant of BusinessSetup.online in Dubai, just operating in London, England.
Stephen E Arnold, May 20, 2026
Real News from Real AI: Believe It, Citizens
May 15, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
If you don’t listen to the oracles of the New World Order, you may have missed out on the revelation about smart software.
Thanks, MidJourney. Not what i prompted, but good enough.
What is the pronouncement that caused Benzinga to leap into information action? In a nutshell, “Chamath Palihapitiya warns power crunch could cripple OpenAI and Anthropic.” But there’s more: “[Mr. Pahlihapitiya says Elon Musk holds massive AI leverage.”Yep, that Elon.
The write up recycles a podcast and says:
To the extent that OpenAI missed, I think what that is is an insight into not enough compute capacity today and that problem is only getting worse,” Palihapitiya said, referring to the report about ChatGPT–parent missing revenue targets. He pointed to a growing mismatch between announced AI infrastructure projects and what is actually being built, warning that many large-scale power and data center developments remain stalled by permitting delays and regulatory hurdles. “Less than half of it is actually being built,” he said. “Most of it is stuck in red tape.”
Is this good news or bad news?
Palihapitiya said this environment could heavily benefit major cloud and infrastructure providers, including Oracle Corp, Amazon.com, Inc., Meta Platforms, Inc., Microsoft Corp, and Alphabet Inc.’s Google. He also suggested Musk and his AI ambitions could be especially well-positioned. “If I were Elon now, I’d be running all over this market,” Palihapitiya said, adding that Musk’s compute access could create opportunities for strategic partnerships, including with Anthropic. “He and Dario [Amodei] should do a deal tomorrow,” he said.
Then Benzinga’s output, partially produced with AI (I mean who knew?) throws in some intellectual support for the “Grok wins” thesis; to wit:
Previously, Deepwater Asset Management’s Gene Munster argued that Musk’s SpaceX is uniquely positioned to dominate the full AI value chain through its “sovereign AI” strategy — an end-to-end ecosystem controlling models, chips, data centers and global distribution without depending on outside providers. Munster said this vertically integrated approach, powered by assets such as Starlink, xAI’s Grok, proprietary X data and potential in-house chip production, could give Musk unmatched control over every layer of AI infrastructure.
Okay, this is a pro-Elon output. What’s interesting is that Mr. Musk’s testimony in the “you are stealing from a non-profit trial” provided some substantive information about the Grok AI system. The argument that Mr. Musk has control of the components in the AI stack is interesting; however, wants for factual support. I mention this because the full self driving seems to have been and remains a work in progress. Also, the Mars venture has been reframed as a jaunt to the moon. There is also the probably irrelevant legal issue in France related to Grok output. As a result, Benzinga, venture types, and AI are mashed up into an “Elon wins” marketing push.
I am not convinced. I am not looking forward to AI generated or AI assisted news reports. I am not enthralled by the arguments of a wealthy podcaster. As a dinobaby, I am truly glad I am old.
Stephen E Arnold, May 15, 2026
AI Zaps Your Mind and Your Wallet
May 13, 2026
Maybe we don’t have to wait for the robot revolution to arrive, because maybe we’ll bring it upon ourselves with the way AI is harming our cognitive processes. Straight from the NeoCivilization substack comes the article, “AI Is Weaponizing Your Own Biases Against You: New Research from MIT & Stanford.” The new research from two estimable institutions suggests that AI panders to its users even when those users are a few cans short of a six pack. I do like the notion of pandering, however. Someone it fits the social norms of 2026.
According to the write up:
“The scientists built a mathematical model of human-AI interaction. They started with a hypothetical person who makes decisions based purely on dry facts and logic. The research showed that as soon as the AI detects the user leaning toward a particular version of events even a false one it starts supplying arguments in favor and quietly omitting those against. A positive feedback loop emerges. The person puts forward a hypothesis, the AI confirms it, the person’s confidence grows, and they offer an even more extreme version. The AI confirms that too. In the end, even the most critically minded user can slip into a “delusional spiral” after just 10–15 turns of dialogue, completely losing touch with reality. They mathematically proved that AI acts as an amplifier of cognitive biases.”
This not just an echo chamber. The hallucinating misinformation machines amplify. Just like the electrical systems at a Foo Fighters’ live performance. Yep, AI channels the Foo cats.
This charming features of the BAIT (Big AI Tech) outfits’ smart software appears to reinforce a user’s delusions. LLMs appear to showcase the AI’s mind dysfunction feature. How often does this benefit make its way to users. My interpretation of the results of the research is that AI chatbots were agreeing with the user’s erroneous statements 49% of the time. My reaction: It is more likely the frontier LLM wizards will probably pump up that percentage. More wrongs are likely to be right in the bizarro world of BAIT outfits. Chatbots are designed to be likable and helpful. The Reinforcement Learning from Human Feedback (RLHF) is used to train Claude and ChatGPT and it priorities user satisfaction above everything else. Thus, outputs that produce interesting outcomes like mental delusions.
Where are the ethical compasses at the BAIT outfits pointing? My thought is revenue. Whatever the user wants and will pump in his or her credit card data is a positive input. The BAIT score is not safety; it is revenue. If self harm or social deviance sells, pump up the parameters that deliver. Regulation or revenue? It seems that revenue is job one along with doing everything possible to become the big winner in the AI monopoly game.
Whitney Grace, May 12, 2026
SAT Time. Robots, Boot Yourselves
May 12, 2026
ScienceDaily reports that, “Scientists Built The Hardest AI Test Ever And the Results Surprising” or, in other words, they decided to put through AI through standardized testing. The hardest test in the world for AI was designed by nearly 1000 researchers. It is called “Humanity’s Last Exam” (HLE) and it’s 2500 questions. The subjects covered are specialized academic fields, ancient languages, natural sciences, humanities, and mathematics. The test was made to remind us that intelligence is more than pattern recognition and memorization. It is about specialized expertise, context, and depth.
HLE’s questions were tested against the Big AI Tech (BAIT) chatbots. If any of them answered a question correctly, that specific question was removed. That ensured the test remained difficult and right at the edge of the chatbots’ capabilities. Here’s what that accomplished:
“Early testing confirmed that the strategy worked. Even powerful AI models struggled with the exam. GPT-4o achieved a score of 2.7 percent, while Claude 3.5 Sonnet reached 4.1 percent. OpenAI’s o1 model performed somewhat better with 8 percent. The most capable systems so far, including Gemini 3.1 Pro and Claude Opus 4.6, have reached accuracy levels between about 40 percent and 50 percent.”
Why did this particular test return what seem to be shocking results? Most of the AI tests are a bit like the butcher in Campinas, Brazil, in 1953. My mother would specify an amount of meat and the friendly person behind the counter used a thumb to prove that the amount order was indeed on the scale.
Was this intentional? You bet your life as Groucho Marx once said. Fiddling data is the name of the game in some fancy software systems. Oh, the results don’t look right. Let’s change this threshold value. Oh, the model is providing information about self harm. Let’s filter that before displaying a result. You get the idea. AI absolutely has to be shaped. Why? It outputs errors. It makes up information. It presents content to make the human dependent or over confident or captured by wonky outputs.
Making AI appear smart is about making money and gaining control. Creating tests that prove how smart AI is works until someone says, “Hey, let’s make a test that does not pander to the big AI tech companies.”
Whitney Grace, May 12, 2026
Microsoft Management: Big Bet, Big Money, and Big Problem
May 6, 2026
Every Microsoft user knows it. Even Microsoft knows it. Finally Microsoft admits that Copilot stinks worse than Windows Vista and ME says How To Geek in “The Uncomfortable Truth About Copilot: Microsoft Knows It’s Useless”. It’s hard enough getting work done in today’s work environment with all the constant dings, alerts, and honks. What makes it harder is an AI assistant waving at you from the corner of your screen. It’s a distraction. You don’t need it. Now Microsoft knows you don’t need it and promises, “Gee, we will do better.”
Sure, Copilot is the spawn of Bob and Clippy.
Who wants smart software in an ASCII editor, a basic photo editor, or a utility to capture a screenshot. Folks, this was a Microsoft management failure. A big bet and the insertion of AI incentives into the minds of people just as baffled about smart software as you and I are.
I don’t think that Microsoft’s admission of its colossal misstep will change people’s thinking about the company or its astute management team overnight. In 2022, Microsoft pulled a marketing fast one on the Google. The Google fumbled into Code Red or something. The race to Silicon Valley excess (not success) was on.
In 2026, Microsoft’s management wizards have figured out that its own actions are causing computer users to embrace Linux and the Apple line up of incredibly similar range of computers.
Microsoft even warns users, despite all the marketing that AI was the future, that Copilot will make mistakes:
There’s a massive chasm between how Microsoft markets Copilot and how its lawyers describe the service in the dark corners of the legal text. The Microsoft Terms of Use (updated in October 2024) legally defines Copilot as being “for entertainment purposes only.” The terms explicitly state that the AI “can make mistakes” and warn: “Don’t rely on Copilot for important advice.” When called out on this, a Microsoft spokesperson told PCMag that the “entertainment” phrasing was just “legacy language” from the Bing Chat days. While the company promises to update the text, the contradiction is hard to ignore.”
I am not sure stating this well-known fact will have much impact. I quite like my Macbooks. I have a friend who is definitely into Linux on a four year old computer. “It’s fast,” he told me.
Adobe is now learning that subscription revenue created an opportunity for its competitors to attack. Microsoft wants subscription and loyalty (plus a credit card) to enjoy the benefits of Bob and Clippy’s shotgun marriage. The cited article says:
“It’s a bold move to hike the price for a feature while simultaneously scrubbing its most forced integrations and warning users that it shouldn’t be used for important work. You’re paying more for a service that Microsoft is removing from its own apps because it was deemed “unnecessary.” This cycle of forced adoption followed by a quiet retreat leaves the user holding the bill for a product that doesn’t really have a clear purpose.”
I wonder if the use of the word “bold” was a mental lapse. I was thinking that either “dumb” or “stupid” would work in the sentence. Didn’t Microsoft post a notice that one should not use Bob and Clippy’s juvenile delinquent for serious work? Yeah. Microsoft did to that. Maybe “inept” would be a possibility instead of bold.
My colleagues and I have picked up the acronym from our fearless leader. Mr. Arnold calls these AI outfits BAIT firms. That means big AI tech companies are trying to capture fish who think that fluff is real tune. Believe me. AI output is recycled Bob and Clippy stuff.
Whitney Grace, May 6, 2026
Yep, Prime Time AI: Real Life Is Not Marketing Blabber
May 5, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I was scanning outputs of my trusty news reader. I thought a tweet from X.com looked interesting. Plus, if it were useful and short, the combo would be a bonus for me. I clicked and my browser displayed: “An AI Agent Just Destroyed Our Production Data. It Confessed in Writing.” No short snappy message. This puppy was a 2,300 word howl. The main point of this tweet, in my opinion, AI cannot be trusted.
That’s been my perception, but this long tweet is painful and in many ways illustrative of the crazy “If we build it, they will come” approach to smart software. Over-promising, under delivering, marketing jibber jabber, weaponized use cases, and endless attempts to remake the human world in the image of some weird Silicon Valley zeitgeist.
The basic story is that a fellow runs a company for small businesses. Examples of the clients include car rental outfits, customer information, and payment tracking. The firm used the Anthropic Claude system for a number of functions. One of these is routine maintenance. To make a long story short, the fancy software packaged by another smart software surfer deleted the service firm’s production database. The backups allegedly were on the drive containing the production database. Bottomline: Data deleted. PocketOS was offline. Its customers out of luck.
Surprisingly, the author of the tweet was able to connect with an outfit called Railway. Here’s what the vendor said:
Within 10 minutes I had notified Railway’s CEO, Jake Cooper (@JustJake), and their head of solutions, Mahmoud (@thisismahmoud), publicly on X. Jake replied: “Oh my. That 1000% shouldn’t be possible. We have evals for this.” It is now 30+ hours since the deletion. Railway still cannot tell me whether infrastructure-level recovery is possible.
The most interesting segment in the tweet is the text of the output the smart software provided after nuking the customer database. I won’t reproduce it because the smart software used objectionable language and did a “Senator, thank you for that question” and did zero to remediate the problem. Smart, right?
The tweet mentions a number of vendors; for example, Anthropic’s latest and greatest version of Claude, an outfit named Railway, and a company called Cursor. Frankly I am not sure how these firm’s fit into the database deletion problem. The write up includes some smarmy lingo about how the smart software does not do bad thinks like take out a production database. Yeah, I believe everything I read on the Internet. I would wager the author of this long screed on X.com is going to be a bit more skeptical going forward.
It seems to me that each of the vendors acted in a way that was far from smart. How do I know? The production database was disappeared. That’s not supposed to happen unless the server is in a data center near Internet City in Dubai. The write up ends with a request for a “real” journalist to contact the owner of the business which had a digital bullet shot through his back end.
I am not a real journalist, so I won’t bother the fellow. I do have some general observations:
- Regulations related to the commercial use of AI might be an idea worth considering
- Assembling a business from diverse software components, wrappers, and plumbing becomes more dicey when smart software is added to the mix. My thought is to do the Tandem Computer thing: Total redundancy. I still operate in this inefficient, old-fashioned manner. It costs more, but when the shaft enters the buttock, I just punch my ConnectPro and use the hot backup machine. Then I get the arrow removed and go see the horrible legal professional whom I pay to protect me.
- Keep the names of the companies who precipitated this business disaster in mind. You may want to avoid these folks like a dead rat in an Amtrak compartment.
Net net: Smart software fails. That’s in the DNA of the tensor approach the “frontier folks” rely upon. If you like surprises, you will love smart software.
Stephen E Arnold, May 2, 2026
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